Adding rest of files

Instruction_Manual.txt

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+MATLAB:
+
+irAE_plotting  - is the main file for plotting and analysis of SUV data
+
+flags_combined.mat - matlab matrics that has :
+        days - a matrix with lines (patients) and columns (consecutive patient image), values are days from treatment start to image 
+        flags - first column (baseline_index); then in pairs: bowel, thyroid, lungs
+                1st column in pair - 0-->no irAE, 1--> clinical diagnosis of irAE was made;
+                2nd column in pair - days from treatment start that clinical diagnosis was made (0 if no diagnosis was made)
+                
+normal_range.mat - is a matriy that contains values of 95%CI; lines - organs (bowel, lungs, thyroid); 1st column is min value of 95%CI, 2nd column max value of 95%CI
+
+suv_percentilesSLOthenUWM -  has three separate 3D tables - one for each organ; lines (patients), columns (consecutive patient image), 3rd dimension is the SUV% that was extracted. So (1,1,20) is value for 1st patient, 1st image, 20th percentile. The values are the SUV% extracted from organ segmentations made with DeepMedic
+
+PYTHON:
+
+GEN_CSV_anon - script that ganerates csv (needed input for SUV extraction); 
+
+cases_retroMManon.csv - csv file (excel) that has inputs for SUV extraction; each line is one input (for patient and visit one input) - it has path to PET and path to Segmentation
+
+extract_SUV_from_mask - script that has csv file as input (path to PET and segmentaation) and extracts SUV percentiles that are then saved in excel file (could be done also without csv with just path)

README.txt

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+ Author: Martin Horvat, October 2022
+
+I. Online resources:
+
+  A. Minutes of the meetings:
+
+    https://docs.google.com/document/d/10vQ1hQK9TbRgyw8s8O_KXbIIqJ8lp8AsJKMbpaviFuA/edit?usp=sharing
+
+
+  B. Repository
+
+    https://med1.fmf.uni-lj.si/owncloud/index.php/apps/files/?dir=/Optimisation%20Group&fileid=689823
+
+  prepared by Strašek, Katja <Katja.Strasek@fmf.uni-lj.si>
+

data/cases_retroMManon.csv

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+,ID,Visit,Image,Mask
+0,NIX-LJU-D2002-IRAE-A000,VISIT_0,C:/Users/strah/OneDrive/Namizje/Raziskave/Melanoma/Retrospective/Patients\Patient001\NIX-LJU-D2002-IRAE-A000-VISIT_0_PET_notCropped_2mmVoxel.nii.gz,C:/Users/strah/OneDrive/Namizje/Raziskave/Melanoma/Retrospective/Patients\Patient001\NIX-LJU-D2002-IRAE-A000-VISIT_0_Segm_v5.nii.gz

matlab/distinguishable_colors.m

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+function colors = distinguishable_colors(n_colors,bg,func)
+% DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct
+%
+% When plotting a set of lines, you may want to distinguish them by color.
+% By default, Matlab chooses a small set of colors and cycles among them,
+% and so if you have more than a few lines there will be confusion about
+% which line is which. To fix this problem, one would want to be able to
+% pick a much larger set of distinct colors, where the number of colors
+% equals or exceeds the number of lines you want to plot. Because our
+% ability to distinguish among colors has limits, one should choose these
+% colors to be "maximally perceptually distinguishable."
+%
+% This function generates a set of colors which are distinguishable
+% by reference to the "Lab" color space, which more closely matches
+% human color perception than RGB. Given an initial large list of possible
+% colors, it iteratively chooses the entry in the list that is farthest (in
+% Lab space) from all previously-chosen entries. While this "greedy"
+% algorithm does not yield a global maximum, it is simple and efficient.
+% Moreover, the sequence of colors is consistent no matter how many you
+% request, which facilitates the users' ability to learn the color order
+% and avoids major changes in the appearance of plots when adding or
+% removing lines.
+%
+% Syntax:
+%   colors = distinguishable_colors(n_colors)
+% Specify the number of colors you want as a scalar, n_colors. This will
+% generate an n_colors-by-3 matrix, each row representing an RGB
+% color triple. If you don't precisely know how many you will need in
+% advance, there is no harm (other than execution time) in specifying
+% slightly more than you think you will need.
+%
+%   colors = distinguishable_colors(n_colors,bg)
+% This syntax allows you to specify the background color, to make sure that
+% your colors are also distinguishable from the background. Default value
+% is white. bg may be specified as an RGB triple or as one of the standard
+% "ColorSpec" strings. You can even specify multiple colors:
+%     bg = {'w','k'}
+% or
+%     bg = [1 1 1; 0 0 0]
+% will only produce colors that are distinguishable from both white and
+% black.
+%
+%   colors = distinguishable_colors(n_colors,bg,rgb2labfunc)
+% By default, distinguishable_colors uses the image processing toolbox's
+% color conversion functions makecform and applycform. Alternatively, you
+% can supply your own color conversion function.
+%
+% Example:
+%   c = distinguishable_colors(25);
+%   figure
+%   image(reshape(c,[1 size(c)]))
+%
+% Example using the file exchange's 'colorspace':
+%   func = @(x) colorspace('RGB->Lab',x);
+%   c = distinguishable_colors(25,'w',func);
+
+% Copyright 2010-2011 by Timothy E. Holy
+
+  % Parse the inputs
+  if (nargin < 2)
+    bg = [1 1 1];  % default white background
+  else
+    if iscell(bg)
+      % User specified a list of colors as a cell aray
+      bgc = bg;
+      for i = 1:length(bgc)
+	bgc{i} = parsecolor(bgc{i});
+      end
+      bg = cat(1,bgc{:});
+    else
+      % User specified a numeric array of colors (n-by-3)
+      bg = parsecolor(bg);
+    end
+  end
+  
+  % Generate a sizable number of RGB triples. This represents our space of
+  % possible choices. By starting in RGB space, we ensure that all of the
+  % colors can be generated by the monitor.
+  n_grid = 30;  % number of grid divisions along each axis in RGB space
+  x = linspace(0,1,n_grid);
+  [R,G,B] = ndgrid(x,x,x);
+  rgb = [R(:) G(:) B(:)];
+  if (n_colors > size(rgb,1)/3)
+    error('You can''t readily distinguish that many colors');
+  end
+  
+  % Convert to Lab color space, which more closely represents human
+  % perception
+  if (nargin > 2)
+    lab = func(rgb);
+    bglab = func(bg);
+  else
+    C = makecform('srgb2lab');
+    lab = applycform(rgb,C);
+    bglab = applycform(bg,C);
+  end
+
+  % If the user specified multiple background colors, compute distances
+  % from the candidate colors to the background colors
+  mindist2 = inf(size(rgb,1),1);
+  for i = 1:size(bglab,1)-1
+    dX = bsxfun(@minus,lab,bglab(i,:)); % displacement all colors from bg
+    dist2 = sum(dX.^2,2);  % square distance
+    mindist2 = min(dist2,mindist2);  % dist2 to closest previously-chosen color
+  end
+  
+  % Iteratively pick the color that maximizes the distance to the nearest
+  % already-picked color
+  colors = zeros(n_colors,3);
+  lastlab = bglab(end,:);   % initialize by making the "previous" color equal to background
+  for i = 1:n_colors
+    dX = bsxfun(@minus,lab,lastlab); % displacement of last from all colors on list
+    dist2 = sum(dX.^2,2);  % square distance
+    mindist2 = min(dist2,mindist2);  % dist2 to closest previously-chosen color
+    [dummy,index] = max(mindist2);  % find the entry farthest from all previously-chosen colors
+    colors(i,:) = rgb(index,:);  % save for output
+    lastlab = lab(index,:);  % prepare for next iteration
+  end
+end
+
+function c = parsecolor(s)
+  if ischar(s)
+    c = colorstr2rgb(s);
+  elseif isnumeric(s) && size(s,2) == 3
+    c = s;
+  else
+    error('MATLAB:InvalidColorSpec','Color specification cannot be parsed.');
+  end
+end
+
+function c = colorstr2rgb(c)
+  % Convert a color string to an RGB value.
+  % This is cribbed from Matlab's whitebg function.
+  % Why don't they make this a stand-alone function?
+  rgbspec = [1 0 0;0 1 0;0 0 1;1 1 1;0 1 1;1 0 1;1 1 0;0 0 0];
+  cspec = 'rgbwcmyk';
+  k = find(cspec==c(1));
+  if isempty(k)
+    error('MATLAB:InvalidColorString','Unknown color string.');
+  end
+  if k~=3 || length(c)==1,
+    c = rgbspec(k,:);
+  elseif length(c)>2,
+    if strcmpi(c(1:3),'bla')
+      c = [0 0 0];
+    elseif strcmpi(c(1:3),'blu')
+      c = [0 0 1];
+    else
+      error('MATLAB:UnknownColorString', 'Unknown color string.');
+    end
+  end
+end

matlab/irAE_plotting.m

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+clear;
+load('flags_combined.mat');
+load('suv_percentilesSLOthenUWM.mat');
+load('normal_range.mat');
+
+
+%Remove patient ae8 bc he never got a PET2 scan
+%Remove non melanoma pats from MSN
+%Remove 5345_11 (ind=13) for bad timing
+ind = [1,2,3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,34,35,36,37,39,40,41,42,43,45,46,47,48,49,50,52,54,57,58,60,63,64,65,66,67,68,71];
+bowel_SUVperc_COMBINED = bowel_SUVperc_COMBINED(ind, :,:);
+lung_SUVperc_COMBINED = lung_SUVperc_COMBINED(ind, :,:);
+thyroid_SUVperc_COMBINED = thyroid_SUVperc_COMBINED(ind, :,:);
+days = days(ind, :);
+flags = flags(ind,:);
+patients = patients(ind);
+
+thyroid_ind = [1:16,18:22, 24:31, 33:37, 39:49, 52:63, 65:70]; %TODO
+thyroid_ind = [1:58]; %keep all
+% 
+% pet = load_nii('Z:\_Data\IRAE\ae9\ae9_1\Processed\ae9_1_PET_notCropped_2mmVoxel.nii.gz');
+% mask = load_nii('Z:\_Data\DLorganseg\deepmedic\output\IRAE\predictions\FS_IRAE_train60_QTII_Labelmasks5\predictions\pred_ae9_1_Segm.nii.gz');
+% thyroid_SUVperc_COMBINED(36,1,75) = prctile(pet.img(mask.img==4),75); %manual fix for ae9_1 thyroid
+% 
+% pet = load_nii('Z:\_Data\IRAE\ae15\ae15_5\Processed\ae15_5_PET_notCropped_2mmVoxel.nii.gz');
+% mask = load_nii('Z:\_Data\DLorganseg\deepmedic\output\IRAE\predictions\FS_IRAE_train60_QTII_Labelmasks5\predictions\pred_ae15_5_Segm.nii.gz');
+% thyroid_SUVperc_COMBINED(41,5,75) = prctile(pet.img(mask.img==4),75); %manual fix for ae15_5 thyroid
+
+
+
+clear ind
+
+
+% Number of scans weirdness 16 vs 17 - not an error. For patient with most
+% scans (ae37) baseline scan is scan2.
+
+%% FINAL PLOTS (4)
+version = 'v4'; %appended to figure names
+% Plot Boxplots rawMAXSUVOPT _ FINAL 
+
+figure('pos',[100,100, 1200,400],'Color','w');
+percentile_grid = [5:5:100];
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);            
+            baseline_ind = flags(:,1);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            baseline_ind = flags(:,1);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            baseline_ind = flags(thyroid_ind,1);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+    end
+    clear organ_MAX
+    for j=1:size(scan_days,1);
+        n_scans = sum(days(j,:)~=0);
+        % Take MAX over time points
+        organ_MAX(j,:) = squeeze(max(suv_perc(j,[baseline_ind(j)+1:baseline_ind(j)+n_scans-1],:),[],2));
+    end
+    
+    % Compute ROC stats for every SUV percentile 1-100
+    for j=1:numel(percentile_grid)
+        [~,~,~,temp_AUC,~] = perfcurve(irae_flag,organ_MAX(:,percentile_grid(j)),1);
+        AUC_organ(j) = temp_AUC;
+    end
+    
+    [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
+    p = ranksum(organ_MAX(find(~irae_flag),percentile_grid(ImaxAUC_organ)),organ_MAX(find(irae_flag),percentile_grid(ImaxAUC_organ)))
+    % Plot: AUC vs SUV percentile
+    subplot(1,3,i)
+    h = boxplot(organ_MAX(:,percentile_grid(ImaxAUC_organ)), irae_flag, ...
+        'Labels',{['NC (n=' num2str(sum(irae_flag==0)) ')'],['AE (n=' num2str(sum(irae_flag==1)) ')']},...
+        'Symbol','o');
+    set(h,{'linew','Color'},{1.5,[0.00,0.45,0.74]})
+    h = findobj(gcf,'tag','Outliers');
+    for iH = 1:length(h)
+        h(iH).MarkerEdgeColor = 'k';
+        h(iH).MarkerSize = 4;
+    end
+    set(gca,'XTickLabel',{['NC (n=' num2str(sum(irae_flag==0)) ')'],['AE (n=' num2str(sum(irae_flag==1)) ')']},'FontSize',12)
+    hold on;
+    set(gca,'YGrid','on');
+    ylabel(['MAX (SUV_{' num2str(suvopt) '%}) [g/mL]'],'FontSize',14);
+    ylim([0, 10]);
+    %text(1.5, 7.4, ['SUV_{OPT%}=' num2str(percentile_grid(ImaxAUC_organ)) '%'],'FontSize',12,'HorizontalAlignment','center');
+    text(1.5, 8.4, ['p = ' sprintf('%.4f',p)],'FontSize',12,'HorizontalAlignment','center');
+    
+    title(organ, 'FontSize',16,'FontName','Arial');
+end
+export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\boxplots_rawMAXSUVOPT_FINAL_' version '.png']);
+
+
+
+
+% PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE (Frelau Fig 3) _ FINAL
+figure('pos',[100,100,700,900],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,10];
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,5];
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+            my_ylim = [0,5];
+    end
+    disp(['Starting ' organ '...']);
+
+    cc = 0.8.*distinguishable_colors(sum(irae_flag));
+    
+    subplot(3,1,i);
+    hold on; box on;
+    cc_counter = 0;
+    for j=1:size(scan_days,1);
+        n_scans = sum(scan_days(j,:)~=0);
+        if irae_flag(j)==1
+            cc_counter = cc_counter + 1;
+            l = plot(scan_days(j,1:n_scans)./30, suv_perc(j,1:n_scans,suvopt),'-','LineWidth',1.5, 'Color', cc(cc_counter,:),'HandleVisibility','off');
+            if irae_days(j)>0 %if we have a date, plot it with a vertical line
+                %scatter(irae_days(j)./30, max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
+                plot([irae_days(j)./30 irae_days(j)./30], [my_ylim(1), my_ylim(2)], 'Color', l.Color, 'LineStyle','--','HandleVisibility','off');
+            end
+        end
+    end
+    % extra vertical line for 1 pt with 2x Colitis (ae10 @ day 774)
+    if i==1
+        plot([774./30 774./30], [my_ylim(1), my_ylim(2)], 'Color', 'k', 'LineStyle','--','HandleVisibility','off');
+    end
+    %dummies for legend
+    plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0 0]);
+    plot(-500, -100, '--','Color',[0 0 0]);
+    %scatter(-500, -500,'v','MarkerEdgeColor',[0 0 0],'MarkerFaceColor',[0 0 0]);
+    patch([-100, 1400, 1400, -100],[norm_95CI(i,1),norm_95CI(i,1),norm_95CI(i,2),norm_95CI(i,2)],[0.6, 0.6, 0.6],'FaceAlpha',0.2);
+    legend('AE','Clin dx','95%CI, NC');
+    xlim([-6,48]);
+    set(gca,'YGrid','on');
+    ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
+    ylim(my_ylim);
+    xlabel('Time on ICI [months]','FontSize',12);
+    xticks([-6:3:48]);
+    title(organ, 'FontSize',16,'FontName','Arial');
+end
+export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_PATCH_RAW_FINAL_' version '.png'])
+
+
+
+
+% Plot AUCvsSUV rawMAXSUVOPT _ FINAL
+
+figure('pos',[100,100, 1200,400],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+percentile_grid = [5:5:100];
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);            
+            baseline_ind = flags(:,1);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            baseline_ind = flags(:,1);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            baseline_ind = flags(thyroid_ind,1);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+    end
+    clear organ_MAX
+
+    for j=1:size(scan_days,1);
+        n_scans = sum(days(j,:)~=0);
+        % Take MAX over time points
+        organ_MAX(j,:) = squeeze(max(suv_perc(j,[baseline_ind(j)+1:baseline_ind(j)+n_scans-1],:),[],2));
+    end
+    
+    % Compute ROC stats for every SUV percentile 1-100
+    for j=1:numel(percentile_grid)
+        [~,~,~,temp_AUC,~] = perfcurve(irae_flag,organ_MAX(:,percentile_grid(j)),1);
+        AUC_organ(j) = temp_AUC;
+    end
+    
+    [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
+
+    % Plot: AUC vs SUV percentile
+    subplot(1,3,i)
+    plot(percentile_grid, AUC_organ, 'LineWidth',1.5);
+    hold on; grid on;
+    plot([0,100], [0.5, 0.5],'k-');
+    xlabel('SUV percentile','FontSize',12);
+    ylabel('AUROC','FontSize',14);
+    ylim([0.4, 1]);
+    text(2,0.97, ['SUV_{OPT%} = SUV_{' num2str(percentile_grid(ImaxAUC_organ)) '%}'], 'FontSize',12,'HorizontalAlignment','left')
+    title(organ, 'FontSize',16,'FontName','Arial');
+end
+export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\AUCvsSUV_rawMAXSUVOPT_FINAL_' version '.png']);
+
+
+% Plot ROC curve @ SUVOPT _ FINAL
+
+figure('pos',[100,100, 1200,400],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);            
+            baseline_ind = flags(:,1);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            baseline_ind = flags(:,1);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            baseline_ind = flags(thyroid_ind,1);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+    end
+    clear organ_MAX
+
+    for j=1:size(scan_days,1);
+        n_scans = sum(days(j,:)~=0);
+        % Take MAX over time points
+        organ_MAX(j,:) = squeeze(max(suv_perc(j,[baseline_ind(j)+1:baseline_ind(j)+n_scans-1],:),[],2));
+    end
+    
+    % Compute ROC stats for every SUV percentile 1-100
+    [X,Y,T,temp_AUC] = perfcurve(irae_flag,organ_MAX(:,suvopt),1);
+    % Find indice that maximizes Youden's index (Sens + Spec - 1)
+    [~,ii] = max((1-X)+Y-1);
+    
+    % Plot: ROC curve for SUVopt
+    subplot(1,3,i)
+    plot(1-X, Y, 'LineWidth',1.5);
+    hold on; grid on;
+    scatter(1-X(ii), Y(ii), 30,'Marker','o','MarkerEdgeColor','k','MarkerFaceColor',[0.00,0.45,0.74], 'LineWidth',1.5);
+    plot([0,1], [1, 0],'k-');
+    xlabel('Specificity','FontSize',14);
+    set(gca, 'XDir','reverse');
+    ylabel('Sensitivity','FontSize',14);
+    ylim([0, 1]);
+    title(organ, 'FontSize',16,'FontName','Arial');
+    %text(0.1, 0.3, ['SUV_{OPT%}: SUV_{' num2str(suvopt) '%}'], 'FontSize',12,'HorizontalAlignment','right');
+    text(0.1, 0.2, ['AUROC = ' num2str(round(temp_AUC,2))],'FontSize',12,'HorizontalAlignment','right');
+    text(0.1, 0.1, ['T_{OPT} = ' num2str(round(T(ii),1)) ' g/mL'],'FontSize',12,'HorizontalAlignment','right');
+
+end
+export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\ROC_FINAL_' version '.png']);
+
+
+%% PT 4982_15 - for Fig 5 - PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE - 
+figure('pos',[100,100, 700,300],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+for i=2
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,10];
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,5];
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+            my_ylim = [0,5];
+    end
+    disp(['Starting ' organ '...']);
+
+    cc = 0.8.*distinguishable_colors(sum(irae_flag));
+    
+    hold on; grid on; box on;
+    cc_counter = 0;
+    for j=11
+        n_scans = sum(scan_days(j,:)~=0);
+        if irae_flag(j)==1
+            cc_counter = cc_counter + 1;
+            l = plot(scan_days(j,1:n_scans), suv_perc(j,1:n_scans,suvopt),'-','LineWidth',1.5, 'Color', 0.1+((cc_counter-1)./sum(irae_flag)).*[0 0.9 0],'HandleVisibility','off');
+            if irae_days(j)>0
+                scatter(irae_days(j), max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
+            end
+        else
+            patchline(scan_days(j,1:n_scans), suv_perc(j,1:n_scans,suvopt),'LineStyle','-','LineWidth',0.5, 'EdgeColor', 'k', 'EdgeAlpha',0.1,'HandleVisibility','off');
+        end
+    end
+    
+    %dummies for legend
+    plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
+    scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
+    plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
+    patch([-100, 1400, 1400, -100],[norm_95CI(i,1),norm_95CI(i,1),norm_95CI(i,2),norm_95CI(i,2)],[0.6, 0.6, 0.6],'FaceAlpha',0.2);
+
+    legend('AE','Clin dx', 'NC', '95%CI NC');
+    xlim([-100,1400]);
+    ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
+    xlabel('Time post tx start [days]','FontSize',12);
+    xticks([-100:100:1400]);
+    title(organ, 'FontSize',16,'FontName','Arial');
+    ylim(my_ylim);
+
+end
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_4982_15_RAW.png')
+
+
+%% PT ae6 - for Fig 5 - PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE - 
+figure('pos',[100,100, 700,600],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+for i=1:2
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,10];
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,5];
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+            my_ylim = [0,5];
+    end
+    disp(['Starting ' organ '...']);
+
+    cc = 0.8.*distinguishable_colors(sum(irae_flag));
+    subplot(2,1,i)
+    hold on; grid on; box on;
+    cc_counter = 0;
+    for j=35
+        n_scans = sum(scan_days(j,:)~=0);
+        if irae_flag(j)==1
+            cc_counter = cc_counter + 1;
+            l = plot(scan_days(j,1:n_scans), suv_perc(j,1:n_scans,suvopt),'-','LineWidth',1.5, 'Color', 0.1+((cc_counter-1)./sum(irae_flag)).*[0 0.9 0],'HandleVisibility','off');
+            if irae_days(j)>0
+                scatter(irae_days(j), max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
+            end
+        else
+            patchline(scan_days(j,1:n_scans), suv_perc(j,1:n_scans,suvopt),'LineStyle','-','LineWidth',0.5, 'EdgeColor', 'k', 'EdgeAlpha',0.1,'HandleVisibility','off');
+        end
+    end
+    
+    %dummies for legend
+    plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
+    scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
+    plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
+    patch([-100, 1400, 1400, -100],[norm_95CI(i,1),norm_95CI(i,1),norm_95CI(i,2),norm_95CI(i,2)],[0.6, 0.6, 0.6],'FaceAlpha',0.2);
+
+    legend('AE','Clin dx', 'NC', '95%CI NC');
+    xlim([-100,1400]);
+    ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
+    xlabel('Time post tx start [days]','FontSize',12);
+    xticks([-100:100:1400]);
+    title(organ, 'FontSize',16,'FontName','Arial');
+    ylim(my_ylim);
+end
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_ae6_RAW.png')
+
+
+%% PT A022/7339_11 - for Fig 7 - PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE - 
+figure('pos',[100,100, 700,600],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+for i=3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,10];
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+            my_ylim = [0,5];
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+            my_ylim = [0,5];
+    end
+    disp(['Starting ' organ '...']);
+
+    cc = 0.8.*distinguishable_colors(sum(irae_flag));
+    subplot(2,1,1)
+    hold on; grid on; box on;
+    cc_counter = 0;
+    for j=23
+        n_scans = sum(scan_days(j,:)~=0);
+        if irae_flag(j)==1
+            cc_counter = cc_counter + 1;
+            l = plot(scan_days(j,1:n_scans), suv_perc(j,1:n_scans,suvopt),'-','LineWidth',1.5, 'Color', 0.1+((cc_counter-1)./sum(irae_flag)).*[0 0.9 0],'HandleVisibility','off');
+            if irae_days(j)>0
+                scatter(irae_days(j), max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
+            end
+        else
+            patchline(scan_days(j,1:n_scans), suv_perc(j,1:n_scans,suvopt),'LineStyle','-','LineWidth',0.5, 'EdgeColor', 'k', 'EdgeAlpha',0.1,'HandleVisibility','off');
+        end
+    end
+    
+    %dummies for legend
+    plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
+    scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
+    plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
+    patch([-100, 1400, 1400, -100],[norm_95CI(i,1),norm_95CI(i,1),norm_95CI(i,2),norm_95CI(i,2)],[0.6, 0.6, 0.6],'FaceAlpha',0.2);
+
+    legend('AE','Clin dx', 'NC', '95%CI NC');
+    xlim([-100,1400]);
+    ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
+    xlabel('Time post tx start [days]','FontSize',12);
+    xticks([-100:100:1400]);
+    title(organ, 'FontSize',16,'FontName','Arial');
+    ylim(my_ylim);
+end
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_a022_RAW.png')
+
+
+
+%% PLOT SUVOPT vs TIME with markers for CLINICAL DX of IRAE - all pts as line, normalized to PET1 SUVOPT (Frelau fig 3)
+figure('pos',[100,100, 700,900],'Color','w');
+set(0,'DefaultAxesTitleFontWeight','normal');
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+            suvopt = 95;
+            scan_days = days;
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+            suvopt = 95;
+            scan_days = days;
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
+            organ = 'Thyroid';
+            irae_flag = flags(thyroid_ind,6);
+            irae_days = flags(thyroid_ind,7);
+            suvopt = 75;
+            scan_days = days(thyroid_ind,:);
+    end
+    disp(['Starting ' organ '...']);
+
+    cc = 0.8.*distinguishable_colors(sum(irae_flag));
+    
+    subplot(3,1,i);
+    hold on; grid on; box on;
+    cc_counter = 0;
+    for j=1:size(scan_days,1);
+        n_scans = sum(scan_days(j,:)~=0);
+        if irae_flag(j)==1
+            cc_counter = cc_counter + 1;
+            l = plot(scan_days(j,1:n_scans), 100.*(suv_perc(j,1:n_scans,suvopt)./suv_perc(j,1,suvopt)-1),'-','LineWidth',1.5, 'Color', 0.1+((cc_counter-1)./sum(irae_flag)).*[0 0.9 0],'HandleVisibility','off');
+            if irae_days(j)>0
+                scatter(irae_days(j), 100.*(max(suv_perc(j,1:n_scans,suvopt))./suv_perc(j,1,suvopt)-1),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
+            end
+        else
+            patchline(scan_days(j,1:n_scans), 100.*(suv_perc(j,1:n_scans,suvopt)./suv_perc(j,1,suvopt)-1),'LineStyle','-','LineWidth',0.5, 'EdgeColor', 'k', 'EdgeAlpha',0.1,'HandleVisibility','off');
+        end
+    end
+    
+    %dummies for legend
+    plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
+    scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
+    plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
+    %patch([-100, 1400, 1400, -100],[norm_95CI(i,1),norm_95CI(i,1),norm_95CI(i,2),norm_95CI(i,2)],[0.6, 0.6, 0.6],'FaceAlpha',0.2);
+
+    legend('AE','Clin dx', 'NC');
+    xlim([-100,1400]);
+    ylabel(['\Delta SUV_{' num2str(suvopt) '%} [%]'],'FontSize',14);
+    xlabel('Time post tx start [days]','FontSize',12);
+    xticks([-100:100:1400]);
+    ylim([-100, 250]);
+    title(organ, 'FontSize',16,'FontName','Arial');
+end
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_ALLPTS_NORM.png')
+
+
+
+
+
+
+
+%% Plot Boxplots dMAXSUVOPT
+
+figure('pos',[100,100, 1200,400],'Color','w');
+percentile_grid = [5:5:100];
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED;
+            organ = 'Thyroid';
+            irae_flag = flags(:,6);
+            irae_days = flags(:,7);
+    end
+    
+    for j=1:58
+        n_scans = sum(days(j,:)~=0);
+        d_organ(j,1:n_scans,:) = 100.*(suv_perc(j, flags(j,1)+[0:n_scans-1], :)./suv_perc(j, flags(j,1), :) - 1);
+
+        % Take MAX over time points
+        d_organ_MAX(j,:) = squeeze(max(d_organ(j,2:n_scans,:),[],2));
+    end
+    
+    % Compute ROC stats for every SUV percentile 1-100
+    for j=1:numel(percentile_grid)
+        [~,~,~,temp_AUC,~] = perfcurve(irae_flag,d_organ_MAX(:,percentile_grid(j)),1);
+        AUC_organ(j) = temp_AUC;
+    end
+    
+    [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
+
+    % Plot: AUC vs SUV percentile
+    subplot(1,3,i)
+    boxplot(d_organ_MAX(:,percentile_grid(ImaxAUC_organ)), irae_flag, 'Labels',{'NC','AE'});
+    hold on; grid on;
+    ylabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
+    ylim([-50, 300]);
+    text(1.5, 250, ['AUROC=' num2str(round(maxAUC_organ,2))],'HorizontalAlignment','center');
+    text(1.5, 220, ['SUV_{OPT%}=' num2str(percentile_grid(ImaxAUC_organ)) '%'] ,'HorizontalAlignment','center');
+    title(organ, 'FontSize',16,'FontName','Arial');
+end
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\boxplots_dMAX_SUVOPT.png');
+
+
+
+%% Plot AUCvsSUV dMAXSUVOPT
+
+figure('pos',[100,100, 1200,400],'Color','w');
+percentile_grid = [5:5:100];
+
+for i=1:3
+    switch i
+        case 1
+            suv_perc = bowel_SUVperc_COMBINED;
+            organ = 'Bowel';
+            irae_flag = flags(:,2);
+            irae_days = flags(:,3);
+        case 2
+            suv_perc = lung_SUVperc_COMBINED;
+            organ = 'Lung';
+            irae_flag = flags(:,4);
+            irae_days = flags(:,5);
+        case 3
+            suv_perc = thyroid_SUVperc_COMBINED;
+            organ = 'Thyroid';
+            irae_flag = flags(:,6);
+            irae_days = flags(:,7);
+    end
+    
+    for j=1:58
+        n_scans = sum(days(j,:)~=0);
+        d_organ(j,1:n_scans,:) = 100.*(suv_perc(j, flags(j,1)+[0:n_scans-1], :)./suv_perc(j, flags(j,1), :) - 1);
+
+        % Take MAX over time points
+        d_organ_MAX(j,:) = squeeze(max(d_organ(j,2:n_scans,:),[],2));
+    end
+    
+    % Compute ROC stats for every SUV percentile 1-100
+    for j=1:numel(percentile_grid)
+        [~,~,~,temp_AUC,~] = perfcurve(irae_flag,d_organ_MAX(:,percentile_grid(j)),1);
+        AUC_organ(j) = temp_AUC;
+    end
+    
+    [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
+
+    % Plot: AUC vs SUV percentile
+    subplot(1,3,i)
+    plot(percentile_grid, AUC_organ, 'LineWidth',1);
+    hold on; grid on;
+    plot([0,100], [0.5, 0.5],'k-');
+    xlabel('SUV percentile','FontSize',14);
+    ylabel('AUC','FontSize',14);
+    ylim([0.4, 1]);
+    text(2,0.98, ['Optimal %ile: ' num2str(percentile_grid(ImaxAUC_organ))], 'FontSize',12,'HorizontalAlignment','left')
+    title(organ, 'FontSize',16,'FontName','Arial');
+end
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\AUCvsSUV_dMAXSUVOPT.png');
+
+
+%% LUNG - USING MAX (N=65 NC vs N=5 AE)
+xlims = [-100, 1200]; %for SUV longitudinal plots - in days
+
+% Compute relative lung change for all patients, all percentiles
+for i=1:58
+    n_scans = sum(days(i,:)~=0);
+    d_lung(i,1:n_scans,:) = 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], :)./lung_SUVperc_COMBINED(i, flags(i,1), :) - 1);
+    
+    % Take MAX over time points
+    d_lung_MAX(i,:) = squeeze(max(d_lung(i,2:n_scans,:),[],2));
+end
+
+% Compute ROC stats for every SUV percentile 1-100
+for i=1:100
+    [~,~,~,temp_AUC,~] = perfcurve(flags(:,4),d_lung_MAX(:,i),1);
+    AUC_lung(i) = temp_AUC;
+end
+
+% Determine optimal percentile SUVxx that maximizes AUC
+[maxAUC_lung, ImaxAUC_lung] = max(AUC_lung);
+
+%redo AUC to get X, Y for optimal SUVxx
+[OPT_X_lung,OPT_Y_lung,OPT_T_lung,OPT_AUC_lung] = perfcurve(flags(:,4),d_lung_MAX(:,ImaxAUC_lung),1);
+
+% determine threshold that maximizes sum of sens and spec
+t = 1-OPT_X_lung+OPT_Y_lung;
+[~,ii] = max(t);
+
+OPT_OPT_T_lung = OPT_T_lung(ii);
+OPT_ROCPT_lung = [1-OPT_X_lung(ii), OPT_Y_lung(ii)];
+
+% Compute mean and sd for NC patients for plotting normal range
+d_lung_NC = d_lung(flags(:,4)==0,:,:);
+
+mu_lung_NC = squeeze(mean(d_lung_NC(:,2,:), 1));
+sigma_lung_NC = squeeze(std(d_lung_NC(:,2,:), 1));
+
+% Plot: AUC vs SUV percentile
+figure('pos',[200, 800, 400, 400], 'Color','w');
+plot([1:100], AUC_lung, 'LineWidth',2);
+hold on; grid on;
+plot([0,100], [0.5, 0.5],'k-');
+xlabel('SUV percentile','FontSize',14);
+ylabel('AUC','FontSize',14);
+ylim([0.4, 1]);
+text(10,0.9, ['Optimal %ile: ' num2str(ImaxAUC_lung)], 'FontSize',12)
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_AUCvsSUVperc.png');
+
+% Plot: Paired boxplots for SUVxx that produce highest AUC
+figure('pos',[700, 800, 300, 400], 'Color','w');
+boxplot(d_lung_MAX(:,ImaxAUC_lung), flags(:,4), 'Labels',{'NC (n=65)','AE (n=5)'});
+ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
+grid on;
+lines = findobj(gcf, 'type', 'line');
+set(lines,'LineWidth',1.5);
+hold on;
+plot([0,3], [OPT_OPT_T_lung, OPT_OPT_T_lung], 'k-');
+p_lung = ranksum(d_lung_MAX(find(~flags(:,4)), ImaxAUC_lung) ,d_lung_MAX(find(flags(:,4)), ImaxAUC_lung));
+text(1.5, 180, ['p = 3e-4'],'HorizontalAlignment','center');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_boxplots.png');
+
+% Plot: ROC curve for SUVxx that produced highest AUC
+figure('pos',[1100, 800, 400, 400], 'Color','w');
+plot(1-OPT_X_lung, OPT_Y_lung,'LineWidth',2);
+hold on; grid on;
+scatter(OPT_ROCPT_lung(1), OPT_ROCPT_lung(2), 'ro');
+set(gca, 'XDir','reverse');
+xlabel('Specificity','FontSize',14);
+ylabel('Sensitivity','FontSize',14);
+text(0.05, 0.25, ['AUC = ' num2str(round(OPT_AUC_lung,3))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.2, ['Sens = ' num2str(round(OPT_ROCPT_lung(2),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.15, ['Spec = ' num2str(round(OPT_ROCPT_lung(1),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.08, ['T_{opt} = +' num2str(round(OPT_OPT_T_lung,1)) '%'],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_ROC.png');
+
+% Plot: Longitudinal SUVxx with normal range 
+figure('pos',[200, 200, 800, 400], 'Color','w');
+xlims = [-100, 1000];
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+hold on; grid on;
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung) + 2.*sigma_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)+ 2.*sigma_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',0.5);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung) - 2.*sigma_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)- 2.*sigma_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',0.5);
+
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+2.*sigma_lung_NC(ImaxAUC_lung), '+2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-2.*sigma_lung_NC(ImaxAUC_lung), '-2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+for i=1:58
+    if flags(i,4) == 1;
+        n_scans = sum(days(i,:)~=0);
+        if i<=30
+            plot(days(i, 1:n_scans), ...
+                100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
+                ':o',...
+                'LineWidth',2,...
+                'Color','k');
+        else
+            plot(days(i, 1:n_scans), ...
+                100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
+                '-.o',...
+                'LineWidth',2,...
+                'Color','r');
+        end
+        hold on; grid on;
+    end
+end
+xlim([xlims(1) xlims(2)]);
+ylim([-50, 220]);
+box on;
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_SUVLong_CI.png');
+
+% Plot: Longitudinal SUVxx with optimal threshold
+figure('pos',[1200, 200, 800, 400], 'Color','w');
+xlims = [-100, 1000];
+hold on; grid on;
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [OPT_OPT_T_lung, OPT_OPT_T_lung], '-','Color','k', 'LineWidth',2);
+
+for i=1:58
+    if flags(i,4) == 1;
+        n_scans = sum(days(i,:)~=0);
+        if i<=30
+            plot(days(i, 1:n_scans), ...
+                100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
+                ':o',...
+                'LineWidth',2,...
+                'Color','k');
+        else
+            plot(days(i, 1:n_scans), ...
+                100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
+                '-.o',...
+                'LineWidth',2,...
+                'Color','r');
+        end
+        hold on; grid on;
+    end
+end
+xlim([xlims(1) xlims(2)]);
+ylim([-50, 220]);
+box on;
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_SUVLong_TOPT.png');
+
+% PLOT - logistic regression for % prob AE
+[log_reg_lung, gof_lung, output_lung] = fit(d_lung_MAX(:,ImaxAUC_lung), flags(:,4),'1./(1+exp(-k.*(x-x0)))','start',[1 50]);
+
+log_reg_lung
+figure('pos',[100,100, 500, 200], 'Color','w');
+scatter(d_lung_MAX(:,ImaxAUC_lung), flags(:,4));
+hold on; box on; grid on;
+plot(log_reg_lung, d_lung_MAX(:,ImaxAUC_lung), flags(:,4));
+xticks([-50:25:225]);
+xlim([-50, 225]);
+yticks([0:0.2:1]);
+xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
+ylabel('AE (y/n)','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_Logreg.png');
+
+%% PLOT - individual SUVopt vs time with tx and dx start/stops
+% pat 608/13
+i=18;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 240];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+%irAE diagnosis
+plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+
+% Imm Supp tx patch GREEN
+tx = patch([136 198 198 136], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% Death
+plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG2 608\_13');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_608_13.png');
+
+
+% pat 4982/15
+i=11;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 1200];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 299 299 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([376 xlims(2) xlims(2) 376], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+%irAE diagnosis
+plot([245 245], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+
+% Imm Supp tx patch GREEN
+tx = patch([309 xlims(2) xlims(2) 309], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG2 4982\_15');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_4982_15.png');
+
+
+
+% pat 112_14
+i=1;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 280];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 201 201 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([232 232], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([201 xlims(2) xlims(2) 201], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG4 112\_14');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_112_14.png');
+
+
+% pat 2278_07
+i=5;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 1500];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 218 218 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([191 191], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([225 830 830 225], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% ICI tx patch BLUE
+tx = patch([560 590 590 560], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([590 590], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% ICI tx patch BLUE
+tx = patch([1447 xlims(2) xlims(2) 1447], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG2 2279\_07');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_2278_07.png');
+
+
+% pat AE6
+i=36;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-20, 450];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([273 273], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitis ae6');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_ae6.png');
+
+
+
+%% PLOT - individual SUVopt vs time with tx and dx start/stops
+% pat 608/13
+i=18;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1600];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+%irAE diagnosis
+plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+
+% Imm Supp tx patch GREEN
+tx = patch([136 198 198 136], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% Death
+plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG2 608\_13');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_608_13_fixedtime.png');
+
+
+% pat 4982/15
+i=11;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1600];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 299 299 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([376 xlims(2) xlims(2) 376], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+%irAE diagnosis
+plot([245 245], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+
+% Imm Supp tx patch GREEN
+tx = patch([309 xlims(2) xlims(2) 309], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG2 4982\_15');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_4982_15_fixedtime.png');
+
+
+
+% pat 112_14
+i=1;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1600];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 201 201 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([232 232], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([201 xlims(2) xlims(2) 201], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG4 112\_14');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_112_14_fixedtime.png');
+
+
+% pat 2278_07
+i=5;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1600];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 218 218 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([191 191], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([225 830 830 225], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% ICI tx patch BLUE
+tx = patch([560 590 590 560], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([590 590], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% ICI tx patch BLUE
+tx = patch([1447 xlims(2) xlims(2) 1447], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitisG2 2279\_07');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_2278_07_fixedtime.png');
+
+
+% pat AE6
+i=36;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1600];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung) mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([273 273], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('pneumonitis ae6');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_ae6_fixedtime.png');
+
+
+
+
+%% BOWEL - USING MAX (N=64 NC vs N=6 AE)
+xlims = [-100, 1200]; %for SUV longitudinal plots - in days
+
+% Compute relative bowel change for all patients, all percentiles
+for i=1:58
+    n_scans = sum(days(i,:)~=0);
+    d_bowel(i,1:n_scans,:) = 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], :)./bowel_SUVperc_COMBINED(i, flags(i,1), :) - 1);
+    
+    % Take MAX over time points
+    d_bowel_MAX(i,:) = squeeze(max(d_bowel(i,2:n_scans,:),[],2));
+end
+
+% Compute ROC stats for every SUV percentile 1-100
+for i=1:100
+    [~,~,~,temp_AUC,~] = perfcurve(flags(:,2),d_bowel_MAX(:,i),1);
+    AUC_bowel(i) = temp_AUC;
+end
+
+% Determine optimal percentile SUVxx that maximizes AUC
+[maxAUC_bowel, ImaxAUC_bowel] = max(AUC_bowel);
+
+%redo AUC to get X, Y for optimal SUVxx
+[OPT_X_bowel,OPT_Y_bowel,OPT_T_bowel,OPT_AUC_bowel] = perfcurve(flags(:,2),d_bowel_MAX(:,ImaxAUC_bowel),1);
+
+%pick optimal operating pt by sum of sensitivity and specificity
+t = 1-OPT_X_bowel+OPT_Y_bowel;
+[~,ii] = max(t);
+
+OPT_OPT_T_bowel = OPT_T_bowel(ii);
+OPT_ROCPT_bowel = [1-OPT_X_bowel(ii), OPT_Y_bowel(ii)];
+
+% Compute mean and sd for NC patients for plotting normal range
+d_bowel_NC = d_bowel(flags(:,2)==0,:,:);
+
+mu_bowel_NC = squeeze(mean(d_bowel_NC(:,2,:), 1));
+sigma_bowel_NC = squeeze(std(d_bowel_NC(:,2,:), 1));
+
+% Plot: AUC vs SUV percentile
+figure('pos',[200, 800, 400, 400], 'Color','w');
+plot([1:100], AUC_bowel, 'LineWidth',2);
+hold on; grid on;
+plot([0,100], [0.5, 0.5],'k-');
+xlabel('SUV percentile','FontSize',14);
+ylabel('AUC','FontSize',14);
+ylim([0.4, 1]);
+text(10,0.9, ['Optimal %ile: ' num2str(ImaxAUC_bowel)], 'FontSize',12)
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_AUCvsSUVperc.png');
+
+% Plot: Paired boxplots for SUVxx that produce highest AUC
+figure('pos',[700, 800, 300, 400], 'Color','w');
+boxplot(d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2), 'Labels',{'NC (n=64)','AE (n=6)'});
+ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
+grid on;
+lines = findobj(gcf, 'type', 'line');
+set(lines,'LineWidth',1.5);
+hold on;
+plot([0,3], [OPT_OPT_T_bowel, OPT_OPT_T_bowel], 'k-');
+p_bowel = ranksum(d_bowel_MAX(find(~flags(:,2)), ImaxAUC_bowel) ,d_bowel_MAX(find(flags(:,2)), ImaxAUC_bowel));
+text(1.5, 180, ['p = 1e-3'],'HorizontalAlignment','center');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_boxplots.png');
+
+% Plot: ROC curve for SUVxx that produced highest AUC
+figure('pos',[1100, 800, 400, 400], 'Color','w');
+plot(1-OPT_X_bowel, OPT_Y_bowel,'LineWidth',2);
+hold on; grid on;
+scatter(OPT_ROCPT_bowel(1), OPT_ROCPT_bowel(2), 'ro');
+set(gca, 'XDir','reverse');
+xlabel('Specificity','FontSize',14);
+ylabel('Sensitivity','FontSize',14);
+text(0.05, 0.25, ['AUC = ' num2str(round(OPT_AUC_bowel,3))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.2, ['Sens = ' num2str(round(OPT_ROCPT_bowel(2),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.15, ['Spec = ' num2str(round(OPT_ROCPT_bowel(1),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.08, ['T_{opt} = +' num2str(round(OPT_OPT_T_bowel,1)) '%'],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_ROC.png');
+
+% Plot: Longitudinal SUVxx with normal range 
+figure('pos',[200, 200, 800, 400], 'Color','w');
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+hold on; grid on;
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel) + 2.*sigma_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)+ 2.*sigma_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',0.5);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel) - 2.*sigma_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)- 2.*sigma_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',0.5);
+
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+2.*sigma_bowel_NC(ImaxAUC_bowel), '+2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-2.*sigma_bowel_NC(ImaxAUC_bowel), '-2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+for i=1:58
+    if flags(i,2) == 1;
+        n_scans = sum(days(i,:)~=0);
+        if i<=30
+            plot(days(i, 1:n_scans), ...
+                100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
+                ':o',...
+                'LineWidth',2,...
+                'Color','k');
+        else
+            plot(days(i, 1:n_scans), ...
+                100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
+                '-.o',...
+                'LineWidth',2,...
+                'Color','r');
+        end
+        hold on; grid on;
+    end
+end
+xlim([xlims(1) xlims(2)]);
+ylim([-60, 140]);
+box on;
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_SUVLong_CI.png');
+
+% Plot: Longitudinal SUVxx with optimal threshold
+figure('pos',[1200, 200, 800, 400], 'Color','w');
+xlims = [-100, 1000];
+hold on; grid on;
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [OPT_OPT_T_bowel, OPT_OPT_T_bowel], '-','Color','k', 'LineWidth',2);
+
+for i=1:58
+    if flags(i,2) == 1;
+        n_scans = sum(days(i,:)~=0);
+        if i<=30
+            plot(days(i, 1:n_scans), ...
+                100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
+                ':o',...
+                'LineWidth',2,...
+                'Color','k');
+        else
+            plot(days(i, 1:n_scans), ...
+                100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
+                '-.o',...
+                'LineWidth',2,...
+                'Color','r');
+        end
+        hold on; grid on;
+    end
+end
+xlim([xlims(1) xlims(2)]);
+ylim([-60, 140]);
+box on;
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_SUVLong_TOPT.png');
+
+% PLOT - logistic regression for % prob AE
+[log_reg_bowel, gof_bowel, output_bowel] = fit(d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2),'1./(1+exp(-k.*(x-x0)))','start',[1 50]);
+log_reg_bowel
+figure('pos',[100,100, 500, 200], 'Color','w');
+scatter(d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2));
+hold on; box on; grid on;
+plot(log_reg_bowel, d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2));
+xticks([-50:50:400]);
+yticks([0:0.2:1]);
+xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
+ylabel('AE (y/n)','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_Logreg.png');
+
+
+% PLOT - logistic regression for % prob AE
+ind = [1,3:10,12:58];
+[log_reg_bowel2, gof_bowel2, output_bowel2] = fit(d_bowel_MAX(ind,ImaxAUC_bowel), flags(ind,2),'1./(1+exp(-k.*(x-x0)))','start',[1 50]);
+
+figure('pos',[100,100, 500, 200], 'Color','w');
+scatter(d_bowel_MAX(ind,ImaxAUC_bowel), flags(ind,2));
+hold on; box on; grid on;
+plot(log_reg_bowel2, d_bowel_MAX(ind,ImaxAUC_bowel), flags(ind,2));
+xticks([-50:50:400]);
+yticks([0:0.2:1]);
+xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
+ylabel('AE (y/n)','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_Logreg_no_outliers.png');
+
+
+%% Individual patients with colitis AE
+
+% pat 5490_15
+i=15;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 150];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 65 65 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([65 110 100 65], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 5490\_15');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5490_15.png');
+
+%% pat 5003_16
+i=12;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 320];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 196 196 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([173 173], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([196 238 238 196], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% ICI tx patch BLUE
+tx = patch([238 308 308 238], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 5003\_16');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5003_16.png');
+
+
+%% pat ae6
+i=36;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 450];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([195 195], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG3 ae6');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae6.png');
+
+
+
+%% pat ae10
+i=39;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 760 760 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([32 32], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+plot([774 774], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 ae10');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae10.png');
+
+
+%% AE 11
+i=40;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 350];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 296 296 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([302 302], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG3 ae11');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae11.png');
+
+
+
+
+%% AE 17
+i=46;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 550];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 155 155 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([231 231], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 ae17');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae17.png');
+
+
+
+
+
+
+%% Individual patients, same xlims
+% pat 5490_15
+i=15;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 65 65 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([65 110 100 65], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 5490\_15');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5490_15_fixedtime.png');
+
+% pat 5003_16
+i=12;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 196 196 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([173 173], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([196 238 238 196], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% ICI tx patch BLUE
+tx = patch([238 308 308 238], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 5003\_16');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5003_16_fixedtime.png');
+
+
+% pat ae6
+i=36;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([195 195], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG3 ae6');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae6_fixedtime.png');
+
+
+
+% pat ae10
+i=39;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 760 760 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([32 32], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+plot([774 774], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 ae10');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae10_fixedtime.png');
+
+
+% AE 11
+i=40;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 296 296 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([302 302], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG3 ae11');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae11_fixedtime.png');
+
+
+
+
+% AE 17
+i=46;
+n_scans = sum(days(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 1000];
+ylims = [-40, 220];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel) mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 155 155 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([231 231], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('colitisG2 ae17');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae17_fixedtime.png');
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+%% thyroid - USING MAX (N=59 NC vs N=11 AE)
+xlims = [-350, 1200]; %for SUV longitudinal plots - in days
+
+thyroid_ind = [1:16,18:22, 24:31, 33:37, 39:49, 52:63, 65:70];
+thyroid_ind = [1:58];
+thyroid_SUVperc_COMBINED = thyroid_SUVperc_COMBINED(thyroid_ind, :, :);
+flags_thyroid = flags(thyroid_ind,:);
+patients_thyroid = patients(thyroid_ind);
+days_thyroid = days(thyroid_ind,:);
+% Compute relative thyroid change for all patients, all percentiles
+for i=1:numel(thyroid_ind)
+    n_scans = sum(days_thyroid(i,:)~=0);
+    d_thyroid(i,1:n_scans,:) = 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], :)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), :) - 1);
+    
+    % Take MAX over time points
+    d_thyroid_MAX(i,:) = squeeze(max(d_thyroid(i,2:n_scans,:),[],2));
+end
+
+% Compute ROC stats for every SUV percentile 1-100
+for i=1:100
+    [~,~,~,temp_AUC,~] = perfcurve(flags_thyroid(:,6),d_thyroid_MAX(:,i),1);
+    AUC_thyroid(i) = temp_AUC;
+end
+
+% Determine optimal percentile SUVxx that maximizes AUC
+[maxAUC_thyroid, ImaxAUC_thyroid] = max(AUC_thyroid);
+
+%redo AUC to get X, Y for optimal SUVxx
+[OPT_X_thyroid,OPT_Y_thyroid,OPT_T_thyroid,OPT_AUC_thyroid] = perfcurve(flags_thyroid(:,6),d_thyroid_MAX(:,ImaxAUC_thyroid),1);
+
+t = 1-OPT_X_thyroid+OPT_Y_thyroid;
+[~,ii] = max(t);
+
+OPT_OPT_T_thyroid = OPT_T_thyroid(ii);
+OPT_ROCPT_thyroid = [1-OPT_X_thyroid(ii), OPT_Y_thyroid(ii)];
+
+% Compute mean and sd for NC patients for plotting normal range
+d_thyroid_NC = d_thyroid(flags_thyroid(:,6)==0,:,:);
+
+mu_thyroid_NC = squeeze(mean(d_thyroid_NC(:,2,:), 1));
+sigma_thyroid_NC = squeeze(std(d_thyroid_NC(:,2,:), 1));
+
+% Plot: AUC vs SUV percentile
+figure('pos',[200, 800, 400, 400], 'Color','w');
+plot([1:100], AUC_thyroid, 'LineWidth',2);
+hold on; grid on;
+plot([0,100], [0.5, 0.5],'k-');
+xlabel('SUV percentile','FontSize',14);
+ylabel('AUC','FontSize',14);
+ylim([0.4, 1]);
+text(10,0.9, ['Optimal %ile: ' num2str(ImaxAUC_thyroid)], 'FontSize',12)
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_AUCvsSUVperc.png');
+
+% Plot: Paired boxplots for SUVxx that produce highest AUC
+figure('pos',[700, 800, 300, 400], 'Color','w');
+boxplot(d_thyroid_MAX(:,ImaxAUC_thyroid), flags_thyroid(:,6), 'Labels',{['NC (n=' num2str(sum(flags_thyroid(:,6)==0)) ')'],['AE (n=' num2str(sum(flags_thyroid(:,6)==1)) ')']});
+ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
+grid on;
+lines = findobj(gcf, 'type', 'line');
+set(lines,'LineWidth',1.5);
+hold on;
+plot([0,3], [OPT_OPT_T_thyroid, OPT_OPT_T_thyroid], 'k-');
+ylim([-60, 250]);
+p_thyroid = ranksum(d_thyroid_MAX(find(~flags_thyroid(:,6)), ImaxAUC_thyroid) ,d_thyroid_MAX(find(flags_thyroid(:,6)), ImaxAUC_thyroid));
+text(1.5, 180, ['p = 6e-6'],'HorizontalAlignment','center');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_boxplots.png');
+
+% Plot: ROC curve for SUVxx that produced highest AUC
+figure('pos',[1100, 800, 400, 400], 'Color','w');
+plot(1-OPT_X_thyroid, OPT_Y_thyroid,'LineWidth',2);
+hold on; grid on;
+scatter(OPT_ROCPT_thyroid(1), OPT_ROCPT_thyroid(2), 'ro');
+set(gca, 'XDir','reverse');
+xlabel('Specificity','FontSize',14);
+ylabel('Sensitivity','FontSize',14);
+text(0.05, 0.25, ['AUC = ' num2str(round(OPT_AUC_thyroid,3))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.2, ['Sens = ' num2str(round(OPT_ROCPT_thyroid(2),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.15, ['Spec = ' num2str(round(OPT_ROCPT_thyroid(1),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+text(0.05, 0.08, ['T_{opt} = +' num2str(round(OPT_OPT_T_thyroid,1)) '%'],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_ROC.png');
+
+% Plot: Longitudinal SUVxx with normal range 
+figure('pos',[200, 200, 800, 400], 'Color','w');
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+hold on; grid on;
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid) + 2.*sigma_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)+ 2.*sigma_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',0.5);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid) - 2.*sigma_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)- 2.*sigma_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',0.5);
+
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+2.*sigma_thyroid_NC(ImaxAUC_thyroid), '+2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-2.*sigma_thyroid_NC(ImaxAUC_thyroid), '-2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+for i=1:numel(thyroid_ind)
+    if flags_thyroid(i,6) == 1;
+        n_scans = sum(days_thyroid(i,:)~=0);
+        if i<=28
+            plot(days_thyroid(i, 1:n_scans), ...
+                100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1), ...
+                ':o',...
+                'LineWidth',2,...
+                'Color','k');
+        else
+            plot(days_thyroid(i, 1:n_scans), ...
+                100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1), ...
+                '-.o',...
+                'LineWidth',2,...
+                'Color','r');
+        end
+        hold on; grid on;
+    end
+end
+xlim([xlims(1) xlims(2)]);
+ylim([-60, 250]);
+box on;
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_SUVLong_CI.png');
+
+% Plot: Longitudinal SUVxx with optimal threshold
+figure('pos',[1200, 200, 800, 400], 'Color','w');
+hold on; grid on;
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [OPT_OPT_T_thyroid, OPT_OPT_T_thyroid], '-','Color','k', 'LineWidth',2);
+
+for i=1:numel(thyroid_ind)
+    if flags_thyroid(i,6) == 1;
+        n_scans = sum(days_thyroid(i,:)~=0);
+        if i<=28
+            plot(days_thyroid(i, 1:n_scans), ...
+                100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1), ...
+                ':o',...
+                'LineWidth',2,...
+                'Color','k');
+        else
+            plot(days_thyroid(i, 1:n_scans), ...
+                100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1), ...
+                '-.o',...
+                'LineWidth',2,...
+                'Color','r');
+        end
+        %scatter(flags_thyroid(i,7), d_thyroid_MAX(i, ImaxAUC_thyroid), 'bo','filled');
+        hold on; grid on;
+    end
+end
+xlim([xlims(1) xlims(2)]);
+ylim([-60, 250]);
+box on;
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_SUVLong_TOPT.png');
+
+% PLOT - logistic regression for % prob AE
+[log_reg_thyroid, gof_thyroid, output_thyroid] = fit(d_thyroid_MAX(:,ImaxAUC_thyroid), flags_thyroid(:,6),'1./(1+exp(-k.*(x-x0)))','start',[1 50]);
+log_reg_thyroid
+figure('pos',[100,100, 500, 200],'Color','w');
+scatter(d_thyroid_MAX(:,ImaxAUC_thyroid), flags_thyroid(:,6));
+hold on; box on; grid on;
+plot(log_reg_thyroid, d_thyroid_MAX(:,ImaxAUC_thyroid), flags_thyroid(:,6));
+xticks([-50:25:225]);
+yticks([0:0.2:1]);
+xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
+ylabel('AE (y/n)','FontSize',14);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_Logreg.png');
+
+
+%% Individual patients with thyroid AE
+% use days_thyroid, patients_thyroid
+%% pat 5345_11
+i=13;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-320, 1200];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([225 225], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([108 xlims(2) xlims(2) 108], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 5345\_11');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_5345_11.png');
+
+%% pat 7339_11
+i=22;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-60, 300];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 7339\_11');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7339_11.png');
+
+
+%% pat 6756_12
+i=19;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-60, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([630 630], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([675 xlims(2) xlims(2) 675], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 6756\_12');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_6756_12.png');
+
+
+%% pat 608_13
+i=17;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-60, 240];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+% Death
+plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([140 198 198 140], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 608\_13');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_608_13.png');
+
+
+
+
+%% pat 7359_09
+i=23;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-80, 1050];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([108 108], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([15 xlims(2) xlims(2) 15], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 7359\_09');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7359_09.png');
+
+
+
+%% pat 1127_06
+i=2;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-140, 720];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([83 83], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([17 xlims(2) xlims(2) 17], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 1127\_06');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_1127_06.png');
+
+
+%% pat ae6
+i=33;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 550];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([76 76], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae6');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae6.png');
+
+
+
+
+%% pat ae15
+i=40;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-30, 400];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([27 27], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae15');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae15.png');
+
+
+
+%% pat ae20
+i=45;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-100, 700];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 357 357 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae20');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae20.png');
+
+
+%% pat ae40
+i=58;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 300];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 111 111 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+%plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae40');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae40.png');
+
+
+%% pat ae41
+i=58;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-50, 550];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 217 217 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+%plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae41');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae41.png');
+
+
+
+
+
+
+
+%% Individual patients with thyroid AE - _fixedtime
+% use days_thyroid, patients_thyroid
+%% pat 5345_11
+i=13;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([225 225], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([108 xlims(2) xlims(2) 108], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 5345\_11');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_5345_11_fixedtime.png');
+
+%% pat 7339_11
+i=22;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 7339\_11');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7339_11_fixedtime.png');
+
+
+%% pat 6756_12
+i=19;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([630 630], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([675 xlims(2) xlims(2) 675], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 6756\_12');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_6756_12_fixedtime.png');
+
+
+%% pat 608_13
+i=17;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+% Death
+plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([140 198 198 140], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 608\_13');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_608_13_fixedtime.png');
+
+
+
+
+%% pat 7359_09
+i=23;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([108 108], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([15 xlims(2) xlims(2) 15], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 7359\_09');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7359_09_fixedtime.png');
+
+
+
+%% pat 1127_06
+i=2;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([83 83], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([17 xlims(2) xlims(2) 17], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 1127\_06');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_1127_06_fixedtime.png');
+
+
+%% pat ae6
+i=33;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([76 76], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+% Imm Supp tx patch GREEN
+tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae6');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae6_fixedtime.png');
+
+
+
+
+%% pat ae15
+i=40;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([27 27], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae15');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae15_fixedtime.png');
+
+
+
+%% pat ae20
+i=45;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 357 357 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae20');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae20_fixedtime.png');
+
+
+%% pat ae40
+i=58;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 111 111 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+%plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae40');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae40_fixedtime.png');
+
+
+%% pat ae41
+i=58;
+n_scans = sum(days_thyroid(i,:)~=0);
+figure('pos',[100,100, 500, 400],'Color','w');
+xlims = [-300, 1500];
+ylims = [-50, 250];
+xlim(xlims);
+ylim(ylims);
+% patch for NC +-sigma
+patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
+    [mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid) mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid)],...
+    [0.95 0.95 0.95]);
+% text for mu, sigma
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
+
+hold on; box on; grid on;
+% y axis and mu
+plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
+plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
+
+% SUVopt
+plot(days_thyroid(i, 1:n_scans), 100.*(thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1)+[0:n_scans-1], ImaxAUC_thyroid)./thyroid_SUVperc_COMBINED(i, flags_thyroid(i,1), ImaxAUC_thyroid) - 1),...
+    'LineWidth',2,...
+    'Marker','o');
+
+% ICI tx patch BLUE
+tx = patch([0 217 217 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
+tx.FaceAlpha = 0.1;
+tx.EdgeAlpha = 0;
+
+% irAE diagnosis
+%plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
+
+ylabel('change SUV_{OPT%} [%]','FontSize',14);
+xlabel('Time [days]','FontSize',14);
+title('thyroidG2 ae41');
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae41_fixedtime.png');
+
+
+
+
+
+
+
+
+
+%% Normal N=15 subcohort
+patient_ids_norm = {'376_17', '1414_15', '1705_16', '4082_15', '4091_14', '4620_17', '5546_16','5706_16', '6368_17', '6799_98', '7037_17',   '7093_08', '7481_15',  '8022_16', '8285_09'};
+
+% PATIENT 5706_16 has to be excluded from normals for Lung and Thyroid
+% PATIENT 7093_08 has to be excluded from normals for Thyroid
+nc0_ind_thyroid = [];
+
+for i=1:numel(patient_ids_norm);
+    for j=1:numel(patients_thyroid);
+        if strcmp(patient_ids_norm{i}, patients_thyroid{j});
+            nc0_ind_thyroid(i) = j;
+        end
+    end
+end
+nc0_ind_thyroid = nc0_ind_thyroid(nc0_ind_thyroid>0);
+% Compute mean and sd for NC patients for plotting normal range
+d_thyroid_NC0 = d_thyroid(nc0_ind_thyroid,:,:);
+
+mu_thyroid_NC0 = squeeze(mean(d_thyroid_NC0(:,2,:), 1));
+sigma_thyroid_NC0 = squeeze(std(d_thyroid_NC0(:,2,:), 1));
+
+
+figure('pos',[700, 800, 300, 400], 'Color','w');
+boxplot([d_thyroid_MAX(nc0_ind_thyroid,ImaxAUC_thyroid); ...
+         d_thyroid_MAX(flags_thyroid(:,6)==0,ImaxAUC_thyroid); ...
+         d_thyroid_MAX(flags_thyroid(:,6)==1,ImaxAUC_thyroid)], ...
+        [1.*ones(1, numel(d_thyroid_MAX(nc0_ind_thyroid,ImaxAUC_thyroid))), ...
+         2.*ones(1, numel(d_thyroid_MAX(flags_thyroid(:,6)==0,ImaxAUC_thyroid))), ...
+         3.*ones(1, numel(d_thyroid_MAX(flags_thyroid(:,6)==1,ImaxAUC_thyroid)))], ...
+         'Labels',{['NC0 (n=' num2str(numel(nc0_ind_thyroid)) ')'],...
+                   ['NC (n=' num2str(sum(flags_thyroid(:,6)==0)) ')'],...
+                   ['AE (n=' num2str(sum(flags_thyroid(:,6)==1)) ')']});
+ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
+grid on;
+lines = findobj(gcf, 'type', 'line');
+set(lines,'LineWidth',1.5);
+hold on;
+plot([0,4], [OPT_OPT_T_thyroid, OPT_OPT_T_thyroid], 'k-');
+ylim([-60, 250]);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_boxplots3.png');
+
+
+% Lung
+nc0_ind = [];
+
+for i=1:numel(patient_ids_norm);
+    for j=1:numel(patients);
+        if strcmp(patient_ids_norm{i}, patients{j});
+            nc0_ind(i) = j;
+        end
+    end
+end
+nc0_ind = nc0_ind(nc0_ind>0);
+% Compute mean and sd for NC patients for plotting normal range
+d_lung_NC0 = d_lung(nc0_ind,:,:);
+
+mu_lung_NC0 = squeeze(mean(d_lung_NC0(:,2,:), 1));
+sigma_lung_NC0 = squeeze(std(d_lung_NC0(:,2,:), 1));
+
+
+figure('pos',[700, 800, 300, 400], 'Color','w');
+boxplot([d_lung_MAX(nc0_ind,ImaxAUC_lung); ...
+         d_lung_MAX(flags(:,4)==0,ImaxAUC_lung); ...
+         d_lung_MAX(flags(:,4)==1,ImaxAUC_lung)], ...
+        [1.*ones(1, numel(d_lung_MAX(nc0_ind,ImaxAUC_lung))), ...
+         2.*ones(1, numel(d_lung_MAX(flags(:,4)==0,ImaxAUC_lung))), ...
+         3.*ones(1, numel(d_lung_MAX(flags(:,4)==1,ImaxAUC_lung)))], ...
+         'Labels',{['NC0 (n=' num2str(numel(nc0_ind)) ')'],...
+                   ['NC (n=' num2str(sum(flags(:,4)==0)) ')'],...
+                   ['AE (n=' num2str(sum(flags(:,4)==1)) ')']});
+ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
+grid on;
+lines = findobj(gcf, 'type', 'line');
+set(lines,'LineWidth',1.5);
+hold on;
+plot([0,4], [OPT_OPT_T_lung, OPT_OPT_T_lung], 'k-');
+ylim([-60, 250]);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_boxplots3.png');
+
+% Bowel
+% Compute mean and sd for NC patients for plotting normal range
+d_bowel_NC0 = d_bowel(nc0_ind,:,:);
+
+mu_bowel_NC0 = squeeze(mean(d_bowel_NC0(:,2,:), 1));
+sigma_bowel_NC0 = squeeze(std(d_bowel_NC0(:,2,:), 1));
+
+
+figure('pos',[700, 800, 300, 400], 'Color','w');
+boxplot([d_bowel_MAX(nc0_ind,ImaxAUC_bowel); ...
+         d_bowel_MAX(flags(:,2)==0,ImaxAUC_bowel); ...
+         d_bowel_MAX(flags(:,2)==1,ImaxAUC_bowel)], ...
+        [1.*ones(1, numel(d_bowel_MAX(nc0_ind,ImaxAUC_bowel))), ...
+         2.*ones(1, numel(d_bowel_MAX(flags(:,2)==0,ImaxAUC_bowel))), ...
+         3.*ones(1, numel(d_bowel_MAX(flags(:,2)==1,ImaxAUC_bowel)))], ...
+         'Labels',{['NC0 (n=' num2str(numel(nc0_ind)) ')'],...
+                   ['NC (n=' num2str(sum(flags(:,2)==0)) ')'],...
+                   ['AE (n=' num2str(sum(flags(:,2)==1)) ')']});
+ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
+grid on;
+lines = findobj(gcf, 'type', 'line');
+set(lines,'LineWidth',1.5);
+hold on;
+plot([0,4], [OPT_OPT_T_bowel, OPT_OPT_T_bowel], 'k-');
+ylim([-60, 400]);
+export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_boxplots3.png');
+

matlab/maxbowel.m

@@ -0,0 +1,17 @@
+load('suv_percentilesSLOthenUWM.mat');
+SUV95 = bowel_SUVperc_COMBINED(:,:,95);
+trans_mat = transpose(SUV95);
+M = max(trans_mat)
+maxSUVbowel = transpose(M)
+
+load('flags_combined.mat');
+flags = flags(:,2)
+        
+ NC = maxSUVbowel(flags == 0) 
+ AE = maxSUVbowel(flags == 1) 
+ 
+ hist(NC)
+ hold on
+ hist(AE)
+ 
+        

python/extract_suv_from_mask.py

@@ -0,0 +1,115 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Sep 29 14:51:09 2022
+
+@author: katja
+"""
+
+import numpy
+import os
+import pandas as pd
+import nibabel
+import csv
+import matplotlib.pyplot as plt
+
+def organ_percentile(img, mask, level, p):
+#ORGAN_PERCENTILE - computes suv_x the pth percentile of the distribution of
+#   image intensity values in img from within some ROI mask
+#
+#   Inputs:
+#       img - image. ndarray
+#       mask - ROI mask. Must be same dimension as img. Must be binary ndarray
+#       p - percentile. Between 0-100
+#
+#   Outputs:
+#       suv_x - percentile of distribution. Defined by:
+#
+#                 suv_x
+#           p/100 = ∫ H(x) dx
+#                   0
+#
+#       where H(x) is the normalized distribution of image values within mask
+    #img = np.array(img)
+    #mask = np.array(mask)
+
+    h = img[mask == level]
+    print("Extracting SUV% for organ", level)
+    
+    #histo=[]
+    # col=["red", "green", "yellow","pink", "brown", "darkblue", "black", "purple"]
+    # i=level
+    # plt.hist(h, color= col[i-1],bins=50, range=(0,6))
+    # plt.title("Histogram of SUV values for "+ str(level))
+    # plt.show()
+    suv_x = numpy.percentile(h, p)
+
+    return suv_x
+
+    
+def main():  
+    
+    path = r"C:/Users/strah/OneDrive/Namizje/Raziskave/Melanoma/Retrospective/"           #path to folder in which patient images are
+    inputCSV = os.path.join(path, 'cases_retroMManon.csv')                          #input csv file that has the path to each patient image
+    
+    #Returns concatinated sequnces of evenly spaced numbers over a specified interval - for SUV percentile
+    pv=numpy.concatenate((numpy.linspace(10,50,5),
+            numpy.linspace(55,80,6),  
+            numpy.linspace(82,90,5),
+            numpy.linspace(91,100,10)))
+    
+    pvi=pv.astype(int)      #have to be indigers to be able to append to name
+    col_names = ["SUV" + str(x) for x in pvi]
+    
+    flists = []
+                    
+    with open(inputCSV, 'r') as inFile:                                         #goes trough the whole csv file and makes an flist (list) 
+        cr = csv.DictReader(inFile, lineterminator='\n')
+        flists = [row for row in cr]
+        
+    alldata=[]
+
+    histo=[]
+    for idx, entry in enumerate(flists, start=1):                               #
+        PET = entry['Image']
+        Seg = entry['Mask']
+        Visit = entry['Visit']
+        ID = entry['ID']
+    
+        #open PET image and segmentation
+        niPET=nibabel.load(PET)
+        niSeg=nibabel.load(Seg)
+        
+        print(" Processing Patient, Visit , (Image: , Mask:)", idx, len(flists), Visit, entry['Image'], entry['Mask'])
+        #In nnU-Net (organ segmentation are numbered): 
+        #1 liver  #DM
+        #2 spleen  #DM
+        #3 lungs #DM
+        #4 thyroid #DM
+        #5 bowel  # DM 16
+        #6 pancreas
+        #7 bladder
+        #8 kidneys
+    
+        #extract SUV percentiles from PET image with mask - segmentation
+        for level in [1,2,3,4,5,6,7,8]:
+            v=organ_percentile(niPET.get_fdata(),niSeg.get_fdata(),level,pv)
+            mat=[level,ID, Visit]
+            mat=numpy.concatenate((mat,v))
+            alldata.append(mat)
+
+    # plt.hist(histo, bins=5, range=(0,6))
+    # plt.title("Histogram of SUV values for Spleen")
+    # plt.show()
+            #print("Percentile, value: ", mat)
+    #print(alldata)
+    # plt.hist(h, bins=50, range=(0,6))
+    # plt.show()
+    Names=["Organ", "PatientID", "Visit"]
+    Names=numpy.concatenate((Names,col_names))
+    #make a dataframe to write the data than in excel - that can be read by another script
+    df=pd.DataFrame(alldata,columns=Names)
+    df.to_excel('C:/Users/strah/OneDrive/Namizje/Raziskave/Melanoma/Retrospective/percentilesAnon.xlsx', index=None) #path to where you want to save excel
+    print("Done.")
+
+if __name__ == '__main__':
+  main()

python/gen_csv_anon.py

@@ -0,0 +1,57 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Mar 10 13:38:24 2022
+
+@author: katja
+"""
+
+from __future__ import print_function
+
+import os
+import glob
+import pandas as pd
+
+
+head = ['ID','Visit','Image','Mask']
+
+#Initialize datadict
+datadict = pd.DataFrame([], columns=head)
+
+path = r"C:/Users/strah/OneDrive/Namizje/Raziskave/Melanoma/Retrospective/Patients/*/*.nii.gz"
+print("path: ", path)
+
+outDir = r'C:/Users/strah/OneDrive/Namizje/Raziskave/Melanoma/Retrospective'
+
+PETNames = [] 
+MaskNames = [] 
+
+for filename in glob.iglob(path, recursive=True):
+    file=os.path.basename(filename)
+    print(file)
+    name = file.split('.')[0]
+    modal= "_".join(name.split('_')[2:])
+    print(modal)
+    if (modal =='PET_notCropped_2mmVoxel'):
+        PETNames.append(filename)
+    elif (modal == 'Segm_v5'):
+        MaskNames.append(filename)
+        
+j=0
+
+for (PETname,MaskName) in zip(PETNames,MaskNames):
+    base = os.path.basename(PETname)
+    print(PETname)
+    name = base.split('.')[0]
+    ID= "-".join(name.split('-')[0:5])
+    allelse="-".join(name.split('-')[5:])
+    Visit="_".join(allelse.split('_')[0:2])
+    print(Visit)
+   
+    #MaskName = os.path.join(MaskDir,'*-label.nrrd')
+    
+    print('Now processing:', ID)
+    
+    datadict.loc[j] = [ID, Visit, PETname, MaskName]
+    j+=1
+
+datadict.to_csv(os.path.join(outDir, 'cases_retroMManon.csv'))

refs/references.txt

@@ -0,0 +1,5 @@
+Filippi 2022 - the role of FDG-PET/CT in oncology
+Hribernik 2021 - use of SUV% as a quantitative imaging biomarkers for irAE in malignant melanoma - retrospective study UW+OI, colitis,                      pneumonitis, thyroidits
+Huff 2021 - development of image intensity histograms - SUV% as biomarkers; digital reference objects, aplication to colitis
+Costa, 2021 - patterns of response to immunotherapy and criteria (RECIST...)
+