irAE_plotting.m 145 KB

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  1. clear;
  2. load('flags_combined.mat');
  3. load('suv_percentilesSLOthenUWM.mat');
  4. load('normal_range.mat');
  5. %Remove patient ae8 bc he never got a PET2 scan
  6. %Remove non melanoma pats from MSN
  7. %Remove 5345_11 (ind=13) for bad timing
  8. 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];
  9. bowel_SUVperc_COMBINED = bowel_SUVperc_COMBINED(ind, :,:);
  10. lung_SUVperc_COMBINED = lung_SUVperc_COMBINED(ind, :,:);
  11. thyroid_SUVperc_COMBINED = thyroid_SUVperc_COMBINED(ind, :,:);
  12. days = days(ind, :);
  13. flags = flags(ind,:);
  14. patients = patients(ind);
  15. thyroid_ind = [1:16,18:22, 24:31, 33:37, 39:49, 52:63, 65:70]; %TODO
  16. thyroid_ind = [1:58]; %keep all
  17. %
  18. % pet = load_nii('Z:\_Data\IRAE\ae9\ae9_1\Processed\ae9_1_PET_notCropped_2mmVoxel.nii.gz');
  19. % mask = load_nii('Z:\_Data\DLorganseg\deepmedic\output\IRAE\predictions\FS_IRAE_train60_QTII_Labelmasks5\predictions\pred_ae9_1_Segm.nii.gz');
  20. % thyroid_SUVperc_COMBINED(36,1,75) = prctile(pet.img(mask.img==4),75); %manual fix for ae9_1 thyroid
  21. %
  22. % pet = load_nii('Z:\_Data\IRAE\ae15\ae15_5\Processed\ae15_5_PET_notCropped_2mmVoxel.nii.gz');
  23. % mask = load_nii('Z:\_Data\DLorganseg\deepmedic\output\IRAE\predictions\FS_IRAE_train60_QTII_Labelmasks5\predictions\pred_ae15_5_Segm.nii.gz');
  24. % thyroid_SUVperc_COMBINED(41,5,75) = prctile(pet.img(mask.img==4),75); %manual fix for ae15_5 thyroid
  25. clear ind
  26. % Number of scans weirdness 16 vs 17 - not an error. For patient with most
  27. % scans (ae37) baseline scan is scan2.
  28. %% FINAL PLOTS (4)
  29. version = 'v4'; %appended to figure names
  30. % Plot Boxplots rawMAXSUVOPT _ FINAL
  31. figure('pos',[100,100, 1200,400],'Color','w');
  32. percentile_grid = [5:5:100];
  33. for i=1:3
  34. switch i
  35. case 1
  36. suv_perc = bowel_SUVperc_COMBINED;
  37. organ = 'Bowel';
  38. irae_flag = flags(:,2);
  39. baseline_ind = flags(:,1);
  40. irae_days = flags(:,3);
  41. suvopt = 95;
  42. scan_days = days;
  43. case 2
  44. suv_perc = lung_SUVperc_COMBINED;
  45. organ = 'Lung';
  46. irae_flag = flags(:,4);
  47. baseline_ind = flags(:,1);
  48. irae_days = flags(:,5);
  49. suvopt = 95;
  50. scan_days = days;
  51. case 3
  52. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  53. organ = 'Thyroid';
  54. irae_flag = flags(thyroid_ind,6);
  55. baseline_ind = flags(thyroid_ind,1);
  56. irae_days = flags(thyroid_ind,7);
  57. suvopt = 75;
  58. scan_days = days(thyroid_ind,:);
  59. end
  60. clear organ_MAX
  61. for j=1:size(scan_days,1);
  62. n_scans = sum(days(j,:)~=0);
  63. % Take MAX over time points
  64. organ_MAX(j,:) = squeeze(max(suv_perc(j,[baseline_ind(j)+1:baseline_ind(j)+n_scans-1],:),[],2));
  65. end
  66. % Compute ROC stats for every SUV percentile 1-100
  67. for j=1:numel(percentile_grid)
  68. [~,~,~,temp_AUC,~] = perfcurve(irae_flag,organ_MAX(:,percentile_grid(j)),1);
  69. AUC_organ(j) = temp_AUC;
  70. end
  71. [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
  72. p = ranksum(organ_MAX(find(~irae_flag),percentile_grid(ImaxAUC_organ)),organ_MAX(find(irae_flag),percentile_grid(ImaxAUC_organ)))
  73. % Plot: AUC vs SUV percentile
  74. subplot(1,3,i)
  75. h = boxplot(organ_MAX(:,percentile_grid(ImaxAUC_organ)), irae_flag, ...
  76. 'Labels',{['NC (n=' num2str(sum(irae_flag==0)) ')'],['AE (n=' num2str(sum(irae_flag==1)) ')']},...
  77. 'Symbol','o');
  78. set(h,{'linew','Color'},{1.5,[0.00,0.45,0.74]})
  79. h = findobj(gcf,'tag','Outliers');
  80. for iH = 1:length(h)
  81. h(iH).MarkerEdgeColor = 'k';
  82. h(iH).MarkerSize = 4;
  83. end
  84. set(gca,'XTickLabel',{['NC (n=' num2str(sum(irae_flag==0)) ')'],['AE (n=' num2str(sum(irae_flag==1)) ')']},'FontSize',12)
  85. hold on;
  86. set(gca,'YGrid','on');
  87. ylabel(['MAX (SUV_{' num2str(suvopt) '%}) [g/mL]'],'FontSize',14);
  88. ylim([0, 10]);
  89. %text(1.5, 7.4, ['SUV_{OPT%}=' num2str(percentile_grid(ImaxAUC_organ)) '%'],'FontSize',12,'HorizontalAlignment','center');
  90. text(1.5, 8.4, ['p = ' sprintf('%.4f',p)],'FontSize',12,'HorizontalAlignment','center');
  91. title(organ, 'FontSize',16,'FontName','Arial');
  92. end
  93. export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\boxplots_rawMAXSUVOPT_FINAL_' version '.png']);
  94. % PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE (Frelau Fig 3) _ FINAL
  95. figure('pos',[100,100,700,900],'Color','w');
  96. set(0,'DefaultAxesTitleFontWeight','normal');
  97. for i=1:3
  98. switch i
  99. case 1
  100. suv_perc = bowel_SUVperc_COMBINED;
  101. organ = 'Bowel';
  102. irae_flag = flags(:,2);
  103. irae_days = flags(:,3);
  104. suvopt = 95;
  105. scan_days = days;
  106. my_ylim = [0,10];
  107. case 2
  108. suv_perc = lung_SUVperc_COMBINED;
  109. organ = 'Lung';
  110. irae_flag = flags(:,4);
  111. irae_days = flags(:,5);
  112. suvopt = 95;
  113. scan_days = days;
  114. my_ylim = [0,5];
  115. case 3
  116. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  117. organ = 'Thyroid';
  118. irae_flag = flags(thyroid_ind,6);
  119. irae_days = flags(thyroid_ind,7);
  120. suvopt = 75;
  121. scan_days = days(thyroid_ind,:);
  122. my_ylim = [0,5];
  123. end
  124. disp(['Starting ' organ '...']);
  125. cc = 0.8.*distinguishable_colors(sum(irae_flag));
  126. subplot(3,1,i);
  127. hold on; box on;
  128. cc_counter = 0;
  129. for j=1:size(scan_days,1);
  130. n_scans = sum(scan_days(j,:)~=0);
  131. if irae_flag(j)==1
  132. cc_counter = cc_counter + 1;
  133. 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');
  134. if irae_days(j)>0 %if we have a date, plot it with a vertical line
  135. %scatter(irae_days(j)./30, max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
  136. plot([irae_days(j)./30 irae_days(j)./30], [my_ylim(1), my_ylim(2)], 'Color', l.Color, 'LineStyle','--','HandleVisibility','off');
  137. end
  138. end
  139. end
  140. % extra vertical line for 1 pt with 2x Colitis (ae10 @ day 774)
  141. if i==1
  142. plot([774./30 774./30], [my_ylim(1), my_ylim(2)], 'Color', 'k', 'LineStyle','--','HandleVisibility','off');
  143. end
  144. %dummies for legend
  145. plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0 0]);
  146. plot(-500, -100, '--','Color',[0 0 0]);
  147. %scatter(-500, -500,'v','MarkerEdgeColor',[0 0 0],'MarkerFaceColor',[0 0 0]);
  148. 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);
  149. legend('AE','Clin dx','95%CI, NC');
  150. xlim([-6,48]);
  151. set(gca,'YGrid','on');
  152. ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
  153. ylim(my_ylim);
  154. xlabel('Time on ICI [months]','FontSize',12);
  155. xticks([-6:3:48]);
  156. title(organ, 'FontSize',16,'FontName','Arial');
  157. end
  158. export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_PATCH_RAW_FINAL_' version '.png'])
  159. % Plot AUCvsSUV rawMAXSUVOPT _ FINAL
  160. figure('pos',[100,100, 1200,400],'Color','w');
  161. set(0,'DefaultAxesTitleFontWeight','normal');
  162. percentile_grid = [5:5:100];
  163. for i=1:3
  164. switch i
  165. case 1
  166. suv_perc = bowel_SUVperc_COMBINED;
  167. organ = 'Bowel';
  168. irae_flag = flags(:,2);
  169. baseline_ind = flags(:,1);
  170. irae_days = flags(:,3);
  171. suvopt = 95;
  172. scan_days = days;
  173. case 2
  174. suv_perc = lung_SUVperc_COMBINED;
  175. organ = 'Lung';
  176. irae_flag = flags(:,4);
  177. baseline_ind = flags(:,1);
  178. irae_days = flags(:,5);
  179. suvopt = 95;
  180. scan_days = days;
  181. case 3
  182. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  183. organ = 'Thyroid';
  184. irae_flag = flags(thyroid_ind,6);
  185. baseline_ind = flags(thyroid_ind,1);
  186. irae_days = flags(thyroid_ind,7);
  187. suvopt = 75;
  188. scan_days = days(thyroid_ind,:);
  189. end
  190. clear organ_MAX
  191. for j=1:size(scan_days,1);
  192. n_scans = sum(days(j,:)~=0);
  193. % Take MAX over time points
  194. organ_MAX(j,:) = squeeze(max(suv_perc(j,[baseline_ind(j)+1:baseline_ind(j)+n_scans-1],:),[],2));
  195. end
  196. % Compute ROC stats for every SUV percentile 1-100
  197. for j=1:numel(percentile_grid)
  198. [~,~,~,temp_AUC,~] = perfcurve(irae_flag,organ_MAX(:,percentile_grid(j)),1);
  199. AUC_organ(j) = temp_AUC;
  200. end
  201. [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
  202. % Plot: AUC vs SUV percentile
  203. subplot(1,3,i)
  204. plot(percentile_grid, AUC_organ, 'LineWidth',1.5);
  205. hold on; grid on;
  206. plot([0,100], [0.5, 0.5],'k-');
  207. xlabel('SUV percentile','FontSize',12);
  208. ylabel('AUROC','FontSize',14);
  209. ylim([0.4, 1]);
  210. text(2,0.97, ['SUV_{OPT%} = SUV_{' num2str(percentile_grid(ImaxAUC_organ)) '%}'], 'FontSize',12,'HorizontalAlignment','left')
  211. title(organ, 'FontSize',16,'FontName','Arial');
  212. end
  213. export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\AUCvsSUV_rawMAXSUVOPT_FINAL_' version '.png']);
  214. % Plot ROC curve @ SUVOPT _ FINAL
  215. figure('pos',[100,100, 1200,400],'Color','w');
  216. set(0,'DefaultAxesTitleFontWeight','normal');
  217. for i=1:3
  218. switch i
  219. case 1
  220. suv_perc = bowel_SUVperc_COMBINED;
  221. organ = 'Bowel';
  222. irae_flag = flags(:,2);
  223. baseline_ind = flags(:,1);
  224. irae_days = flags(:,3);
  225. suvopt = 95;
  226. scan_days = days;
  227. case 2
  228. suv_perc = lung_SUVperc_COMBINED;
  229. organ = 'Lung';
  230. irae_flag = flags(:,4);
  231. baseline_ind = flags(:,1);
  232. irae_days = flags(:,5);
  233. suvopt = 95;
  234. scan_days = days;
  235. case 3
  236. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  237. organ = 'Thyroid';
  238. irae_flag = flags(thyroid_ind,6);
  239. baseline_ind = flags(thyroid_ind,1);
  240. irae_days = flags(thyroid_ind,7);
  241. suvopt = 75;
  242. scan_days = days(thyroid_ind,:);
  243. end
  244. clear organ_MAX
  245. for j=1:size(scan_days,1);
  246. n_scans = sum(days(j,:)~=0);
  247. % Take MAX over time points
  248. organ_MAX(j,:) = squeeze(max(suv_perc(j,[baseline_ind(j)+1:baseline_ind(j)+n_scans-1],:),[],2));
  249. end
  250. % Compute ROC stats for every SUV percentile 1-100
  251. [X,Y,T,temp_AUC] = perfcurve(irae_flag,organ_MAX(:,suvopt),1);
  252. % Find indice that maximizes Youden's index (Sens + Spec - 1)
  253. [~,ii] = max((1-X)+Y-1);
  254. % Plot: ROC curve for SUVopt
  255. subplot(1,3,i)
  256. plot(1-X, Y, 'LineWidth',1.5);
  257. hold on; grid on;
  258. scatter(1-X(ii), Y(ii), 30,'Marker','o','MarkerEdgeColor','k','MarkerFaceColor',[0.00,0.45,0.74], 'LineWidth',1.5);
  259. plot([0,1], [1, 0],'k-');
  260. xlabel('Specificity','FontSize',14);
  261. set(gca, 'XDir','reverse');
  262. ylabel('Sensitivity','FontSize',14);
  263. ylim([0, 1]);
  264. title(organ, 'FontSize',16,'FontName','Arial');
  265. %text(0.1, 0.3, ['SUV_{OPT%}: SUV_{' num2str(suvopt) '%}'], 'FontSize',12,'HorizontalAlignment','right');
  266. text(0.1, 0.2, ['AUROC = ' num2str(round(temp_AUC,2))],'FontSize',12,'HorizontalAlignment','right');
  267. text(0.1, 0.1, ['T_{OPT} = ' num2str(round(T(ii),1)) ' g/mL'],'FontSize',12,'HorizontalAlignment','right');
  268. end
  269. export_fig(['C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\ROC_FINAL_' version '.png']);
  270. %% PT 4982_15 - for Fig 5 - PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE -
  271. figure('pos',[100,100, 700,300],'Color','w');
  272. set(0,'DefaultAxesTitleFontWeight','normal');
  273. for i=2
  274. switch i
  275. case 1
  276. suv_perc = bowel_SUVperc_COMBINED;
  277. organ = 'Bowel';
  278. irae_flag = flags(:,2);
  279. irae_days = flags(:,3);
  280. suvopt = 95;
  281. scan_days = days;
  282. my_ylim = [0,10];
  283. case 2
  284. suv_perc = lung_SUVperc_COMBINED;
  285. organ = 'Lung';
  286. irae_flag = flags(:,4);
  287. irae_days = flags(:,5);
  288. suvopt = 95;
  289. scan_days = days;
  290. my_ylim = [0,5];
  291. case 3
  292. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  293. organ = 'Thyroid';
  294. irae_flag = flags(thyroid_ind,6);
  295. irae_days = flags(thyroid_ind,7);
  296. suvopt = 75;
  297. scan_days = days(thyroid_ind,:);
  298. my_ylim = [0,5];
  299. end
  300. disp(['Starting ' organ '...']);
  301. cc = 0.8.*distinguishable_colors(sum(irae_flag));
  302. hold on; grid on; box on;
  303. cc_counter = 0;
  304. for j=11
  305. n_scans = sum(scan_days(j,:)~=0);
  306. if irae_flag(j)==1
  307. cc_counter = cc_counter + 1;
  308. 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');
  309. if irae_days(j)>0
  310. scatter(irae_days(j), max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
  311. end
  312. else
  313. 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');
  314. end
  315. end
  316. %dummies for legend
  317. plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
  318. scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
  319. plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
  320. 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);
  321. legend('AE','Clin dx', 'NC', '95%CI NC');
  322. xlim([-100,1400]);
  323. ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
  324. xlabel('Time post tx start [days]','FontSize',12);
  325. xticks([-100:100:1400]);
  326. title(organ, 'FontSize',16,'FontName','Arial');
  327. ylim(my_ylim);
  328. end
  329. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_4982_15_RAW.png')
  330. %% PT ae6 - for Fig 5 - PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE -
  331. figure('pos',[100,100, 700,600],'Color','w');
  332. set(0,'DefaultAxesTitleFontWeight','normal');
  333. for i=1:2
  334. switch i
  335. case 1
  336. suv_perc = bowel_SUVperc_COMBINED;
  337. organ = 'Bowel';
  338. irae_flag = flags(:,2);
  339. irae_days = flags(:,3);
  340. suvopt = 95;
  341. scan_days = days;
  342. my_ylim = [0,10];
  343. case 2
  344. suv_perc = lung_SUVperc_COMBINED;
  345. organ = 'Lung';
  346. irae_flag = flags(:,4);
  347. irae_days = flags(:,5);
  348. suvopt = 95;
  349. scan_days = days;
  350. my_ylim = [0,5];
  351. case 3
  352. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  353. organ = 'Thyroid';
  354. irae_flag = flags(thyroid_ind,6);
  355. irae_days = flags(thyroid_ind,7);
  356. suvopt = 75;
  357. scan_days = days(thyroid_ind,:);
  358. my_ylim = [0,5];
  359. end
  360. disp(['Starting ' organ '...']);
  361. cc = 0.8.*distinguishable_colors(sum(irae_flag));
  362. subplot(2,1,i)
  363. hold on; grid on; box on;
  364. cc_counter = 0;
  365. for j=35
  366. n_scans = sum(scan_days(j,:)~=0);
  367. if irae_flag(j)==1
  368. cc_counter = cc_counter + 1;
  369. 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');
  370. if irae_days(j)>0
  371. scatter(irae_days(j), max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
  372. end
  373. else
  374. 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');
  375. end
  376. end
  377. %dummies for legend
  378. plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
  379. scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
  380. plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
  381. 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);
  382. legend('AE','Clin dx', 'NC', '95%CI NC');
  383. xlim([-100,1400]);
  384. ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
  385. xlabel('Time post tx start [days]','FontSize',12);
  386. xticks([-100:100:1400]);
  387. title(organ, 'FontSize',16,'FontName','Arial');
  388. ylim(my_ylim);
  389. end
  390. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_ae6_RAW.png')
  391. %% PT A022/7339_11 - for Fig 7 - PLOT SUV95 vs TIME with markers for CLINICAL DX of IRAE -
  392. figure('pos',[100,100, 700,600],'Color','w');
  393. set(0,'DefaultAxesTitleFontWeight','normal');
  394. for i=3
  395. switch i
  396. case 1
  397. suv_perc = bowel_SUVperc_COMBINED;
  398. organ = 'Bowel';
  399. irae_flag = flags(:,2);
  400. irae_days = flags(:,3);
  401. suvopt = 95;
  402. scan_days = days;
  403. my_ylim = [0,10];
  404. case 2
  405. suv_perc = lung_SUVperc_COMBINED;
  406. organ = 'Lung';
  407. irae_flag = flags(:,4);
  408. irae_days = flags(:,5);
  409. suvopt = 95;
  410. scan_days = days;
  411. my_ylim = [0,5];
  412. case 3
  413. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  414. organ = 'Thyroid';
  415. irae_flag = flags(thyroid_ind,6);
  416. irae_days = flags(thyroid_ind,7);
  417. suvopt = 75;
  418. scan_days = days(thyroid_ind,:);
  419. my_ylim = [0,5];
  420. end
  421. disp(['Starting ' organ '...']);
  422. cc = 0.8.*distinguishable_colors(sum(irae_flag));
  423. subplot(2,1,1)
  424. hold on; grid on; box on;
  425. cc_counter = 0;
  426. for j=23
  427. n_scans = sum(scan_days(j,:)~=0);
  428. if irae_flag(j)==1
  429. cc_counter = cc_counter + 1;
  430. 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');
  431. if irae_days(j)>0
  432. scatter(irae_days(j), max(suv_perc(j,1:n_scans,suvopt)),'v','MarkerEdgeColor',l.Color,'MarkerFaceColor',l.Color,'HandleVisibility','off');
  433. end
  434. else
  435. 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');
  436. end
  437. end
  438. %dummies for legend
  439. plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
  440. scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
  441. plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
  442. 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);
  443. legend('AE','Clin dx', 'NC', '95%CI NC');
  444. xlim([-100,1400]);
  445. ylabel(['SUV_{' num2str(suvopt) '%} [g/mL]'],'FontSize',14);
  446. xlabel('Time post tx start [days]','FontSize',12);
  447. xticks([-100:100:1400]);
  448. title(organ, 'FontSize',16,'FontName','Arial');
  449. ylim(my_ylim);
  450. end
  451. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_a022_RAW.png')
  452. %% PLOT SUVOPT vs TIME with markers for CLINICAL DX of IRAE - all pts as line, normalized to PET1 SUVOPT (Frelau fig 3)
  453. figure('pos',[100,100, 700,900],'Color','w');
  454. set(0,'DefaultAxesTitleFontWeight','normal');
  455. for i=1:3
  456. switch i
  457. case 1
  458. suv_perc = bowel_SUVperc_COMBINED;
  459. organ = 'Bowel';
  460. irae_flag = flags(:,2);
  461. irae_days = flags(:,3);
  462. suvopt = 95;
  463. scan_days = days;
  464. case 2
  465. suv_perc = lung_SUVperc_COMBINED;
  466. organ = 'Lung';
  467. irae_flag = flags(:,4);
  468. irae_days = flags(:,5);
  469. suvopt = 95;
  470. scan_days = days;
  471. case 3
  472. suv_perc = thyroid_SUVperc_COMBINED(thyroid_ind,:,:);
  473. organ = 'Thyroid';
  474. irae_flag = flags(thyroid_ind,6);
  475. irae_days = flags(thyroid_ind,7);
  476. suvopt = 75;
  477. scan_days = days(thyroid_ind,:);
  478. end
  479. disp(['Starting ' organ '...']);
  480. cc = 0.8.*distinguishable_colors(sum(irae_flag));
  481. subplot(3,1,i);
  482. hold on; grid on; box on;
  483. cc_counter = 0;
  484. for j=1:size(scan_days,1);
  485. n_scans = sum(scan_days(j,:)~=0);
  486. if irae_flag(j)==1
  487. cc_counter = cc_counter + 1;
  488. 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');
  489. if irae_days(j)>0
  490. 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');
  491. end
  492. else
  493. 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');
  494. end
  495. end
  496. %dummies for legend
  497. plot(-500, -100, '-','LineWidth',1.5, 'Color',[0 0.6 0]);
  498. scatter(-500, -500,'v','MarkerEdgeColor',[0 0.7 0],'MarkerFaceColor',[0 0.6 0]);
  499. plot(-500, -500,'LineStyle','-','LineWidth',0.5, 'Color', [0.8 0.8 0.8]);
  500. %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);
  501. legend('AE','Clin dx', 'NC');
  502. xlim([-100,1400]);
  503. ylabel(['\Delta SUV_{' num2str(suvopt) '%} [%]'],'FontSize',14);
  504. xlabel('Time post tx start [days]','FontSize',12);
  505. xticks([-100:100:1400]);
  506. ylim([-100, 250]);
  507. title(organ, 'FontSize',16,'FontName','Arial');
  508. end
  509. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\SUVOPT_vs_time_ALLPTS_NORM.png')
  510. %% Plot Boxplots dMAXSUVOPT
  511. figure('pos',[100,100, 1200,400],'Color','w');
  512. percentile_grid = [5:5:100];
  513. for i=1:3
  514. switch i
  515. case 1
  516. suv_perc = bowel_SUVperc_COMBINED;
  517. organ = 'Bowel';
  518. irae_flag = flags(:,2);
  519. irae_days = flags(:,3);
  520. case 2
  521. suv_perc = lung_SUVperc_COMBINED;
  522. organ = 'Lung';
  523. irae_flag = flags(:,4);
  524. irae_days = flags(:,5);
  525. case 3
  526. suv_perc = thyroid_SUVperc_COMBINED;
  527. organ = 'Thyroid';
  528. irae_flag = flags(:,6);
  529. irae_days = flags(:,7);
  530. end
  531. for j=1:58
  532. n_scans = sum(days(j,:)~=0);
  533. d_organ(j,1:n_scans,:) = 100.*(suv_perc(j, flags(j,1)+[0:n_scans-1], :)./suv_perc(j, flags(j,1), :) - 1);
  534. % Take MAX over time points
  535. d_organ_MAX(j,:) = squeeze(max(d_organ(j,2:n_scans,:),[],2));
  536. end
  537. % Compute ROC stats for every SUV percentile 1-100
  538. for j=1:numel(percentile_grid)
  539. [~,~,~,temp_AUC,~] = perfcurve(irae_flag,d_organ_MAX(:,percentile_grid(j)),1);
  540. AUC_organ(j) = temp_AUC;
  541. end
  542. [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
  543. % Plot: AUC vs SUV percentile
  544. subplot(1,3,i)
  545. boxplot(d_organ_MAX(:,percentile_grid(ImaxAUC_organ)), irae_flag, 'Labels',{'NC','AE'});
  546. hold on; grid on;
  547. ylabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
  548. ylim([-50, 300]);
  549. text(1.5, 250, ['AUROC=' num2str(round(maxAUC_organ,2))],'HorizontalAlignment','center');
  550. text(1.5, 220, ['SUV_{OPT%}=' num2str(percentile_grid(ImaxAUC_organ)) '%'] ,'HorizontalAlignment','center');
  551. title(organ, 'FontSize',16,'FontName','Arial');
  552. end
  553. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\boxplots_dMAX_SUVOPT.png');
  554. %% Plot AUCvsSUV dMAXSUVOPT
  555. figure('pos',[100,100, 1200,400],'Color','w');
  556. percentile_grid = [5:5:100];
  557. for i=1:3
  558. switch i
  559. case 1
  560. suv_perc = bowel_SUVperc_COMBINED;
  561. organ = 'Bowel';
  562. irae_flag = flags(:,2);
  563. irae_days = flags(:,3);
  564. case 2
  565. suv_perc = lung_SUVperc_COMBINED;
  566. organ = 'Lung';
  567. irae_flag = flags(:,4);
  568. irae_days = flags(:,5);
  569. case 3
  570. suv_perc = thyroid_SUVperc_COMBINED;
  571. organ = 'Thyroid';
  572. irae_flag = flags(:,6);
  573. irae_days = flags(:,7);
  574. end
  575. for j=1:58
  576. n_scans = sum(days(j,:)~=0);
  577. d_organ(j,1:n_scans,:) = 100.*(suv_perc(j, flags(j,1)+[0:n_scans-1], :)./suv_perc(j, flags(j,1), :) - 1);
  578. % Take MAX over time points
  579. d_organ_MAX(j,:) = squeeze(max(d_organ(j,2:n_scans,:),[],2));
  580. end
  581. % Compute ROC stats for every SUV percentile 1-100
  582. for j=1:numel(percentile_grid)
  583. [~,~,~,temp_AUC,~] = perfcurve(irae_flag,d_organ_MAX(:,percentile_grid(j)),1);
  584. AUC_organ(j) = temp_AUC;
  585. end
  586. [maxAUC_organ, ImaxAUC_organ] = max(AUC_organ);
  587. % Plot: AUC vs SUV percentile
  588. subplot(1,3,i)
  589. plot(percentile_grid, AUC_organ, 'LineWidth',1);
  590. hold on; grid on;
  591. plot([0,100], [0.5, 0.5],'k-');
  592. xlabel('SUV percentile','FontSize',14);
  593. ylabel('AUC','FontSize',14);
  594. ylim([0.4, 1]);
  595. text(2,0.98, ['Optimal %ile: ' num2str(percentile_grid(ImaxAUC_organ))], 'FontSize',12,'HorizontalAlignment','left')
  596. title(organ, 'FontSize',16,'FontName','Arial');
  597. end
  598. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\AUCvsSUV_dMAXSUVOPT.png');
  599. %% LUNG - USING MAX (N=65 NC vs N=5 AE)
  600. xlims = [-100, 1200]; %for SUV longitudinal plots - in days
  601. % Compute relative lung change for all patients, all percentiles
  602. for i=1:58
  603. n_scans = sum(days(i,:)~=0);
  604. 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);
  605. % Take MAX over time points
  606. d_lung_MAX(i,:) = squeeze(max(d_lung(i,2:n_scans,:),[],2));
  607. end
  608. % Compute ROC stats for every SUV percentile 1-100
  609. for i=1:100
  610. [~,~,~,temp_AUC,~] = perfcurve(flags(:,4),d_lung_MAX(:,i),1);
  611. AUC_lung(i) = temp_AUC;
  612. end
  613. % Determine optimal percentile SUVxx that maximizes AUC
  614. [maxAUC_lung, ImaxAUC_lung] = max(AUC_lung);
  615. %redo AUC to get X, Y for optimal SUVxx
  616. [OPT_X_lung,OPT_Y_lung,OPT_T_lung,OPT_AUC_lung] = perfcurve(flags(:,4),d_lung_MAX(:,ImaxAUC_lung),1);
  617. % determine threshold that maximizes sum of sens and spec
  618. t = 1-OPT_X_lung+OPT_Y_lung;
  619. [~,ii] = max(t);
  620. OPT_OPT_T_lung = OPT_T_lung(ii);
  621. OPT_ROCPT_lung = [1-OPT_X_lung(ii), OPT_Y_lung(ii)];
  622. % Compute mean and sd for NC patients for plotting normal range
  623. d_lung_NC = d_lung(flags(:,4)==0,:,:);
  624. mu_lung_NC = squeeze(mean(d_lung_NC(:,2,:), 1));
  625. sigma_lung_NC = squeeze(std(d_lung_NC(:,2,:), 1));
  626. % Plot: AUC vs SUV percentile
  627. figure('pos',[200, 800, 400, 400], 'Color','w');
  628. plot([1:100], AUC_lung, 'LineWidth',2);
  629. hold on; grid on;
  630. plot([0,100], [0.5, 0.5],'k-');
  631. xlabel('SUV percentile','FontSize',14);
  632. ylabel('AUC','FontSize',14);
  633. ylim([0.4, 1]);
  634. text(10,0.9, ['Optimal %ile: ' num2str(ImaxAUC_lung)], 'FontSize',12)
  635. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_AUCvsSUVperc.png');
  636. % Plot: Paired boxplots for SUVxx that produce highest AUC
  637. figure('pos',[700, 800, 300, 400], 'Color','w');
  638. boxplot(d_lung_MAX(:,ImaxAUC_lung), flags(:,4), 'Labels',{'NC (n=65)','AE (n=5)'});
  639. ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
  640. grid on;
  641. lines = findobj(gcf, 'type', 'line');
  642. set(lines,'LineWidth',1.5);
  643. hold on;
  644. plot([0,3], [OPT_OPT_T_lung, OPT_OPT_T_lung], 'k-');
  645. p_lung = ranksum(d_lung_MAX(find(~flags(:,4)), ImaxAUC_lung) ,d_lung_MAX(find(flags(:,4)), ImaxAUC_lung));
  646. text(1.5, 180, ['p = 3e-4'],'HorizontalAlignment','center');
  647. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_boxplots.png');
  648. % Plot: ROC curve for SUVxx that produced highest AUC
  649. figure('pos',[1100, 800, 400, 400], 'Color','w');
  650. plot(1-OPT_X_lung, OPT_Y_lung,'LineWidth',2);
  651. hold on; grid on;
  652. scatter(OPT_ROCPT_lung(1), OPT_ROCPT_lung(2), 'ro');
  653. set(gca, 'XDir','reverse');
  654. xlabel('Specificity','FontSize',14);
  655. ylabel('Sensitivity','FontSize',14);
  656. text(0.05, 0.25, ['AUC = ' num2str(round(OPT_AUC_lung,3))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  657. text(0.05, 0.2, ['Sens = ' num2str(round(OPT_ROCPT_lung(2),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  658. text(0.05, 0.15, ['Spec = ' num2str(round(OPT_ROCPT_lung(1),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  659. text(0.05, 0.08, ['T_{opt} = +' num2str(round(OPT_OPT_T_lung,1)) '%'],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  660. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_ROC.png');
  661. % Plot: Longitudinal SUVxx with normal range
  662. figure('pos',[200, 200, 800, 400], 'Color','w');
  663. xlims = [-100, 1000];
  664. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  665. [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)],...
  666. [0.95 0.95 0.95]);
  667. hold on; grid on;
  668. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  669. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  670. 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);
  671. 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);
  672. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  673. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  674. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  675. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+2.*sigma_lung_NC(ImaxAUC_lung), '+2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  676. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-2.*sigma_lung_NC(ImaxAUC_lung), '-2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  677. for i=1:58
  678. if flags(i,4) == 1;
  679. n_scans = sum(days(i,:)~=0);
  680. if i<=30
  681. plot(days(i, 1:n_scans), ...
  682. 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
  683. ':o',...
  684. 'LineWidth',2,...
  685. 'Color','k');
  686. else
  687. plot(days(i, 1:n_scans), ...
  688. 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
  689. '-.o',...
  690. 'LineWidth',2,...
  691. 'Color','r');
  692. end
  693. hold on; grid on;
  694. end
  695. end
  696. xlim([xlims(1) xlims(2)]);
  697. ylim([-50, 220]);
  698. box on;
  699. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  700. xlabel('Time [days]','FontSize',14);
  701. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_SUVLong_CI.png');
  702. % Plot: Longitudinal SUVxx with optimal threshold
  703. figure('pos',[1200, 200, 800, 400], 'Color','w');
  704. xlims = [-100, 1000];
  705. hold on; grid on;
  706. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  707. plot([xlims(1), xlims(2)], [OPT_OPT_T_lung, OPT_OPT_T_lung], '-','Color','k', 'LineWidth',2);
  708. for i=1:58
  709. if flags(i,4) == 1;
  710. n_scans = sum(days(i,:)~=0);
  711. if i<=30
  712. plot(days(i, 1:n_scans), ...
  713. 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
  714. ':o',...
  715. 'LineWidth',2,...
  716. 'Color','k');
  717. else
  718. plot(days(i, 1:n_scans), ...
  719. 100.*(lung_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_lung)./lung_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_lung) - 1), ...
  720. '-.o',...
  721. 'LineWidth',2,...
  722. 'Color','r');
  723. end
  724. hold on; grid on;
  725. end
  726. end
  727. xlim([xlims(1) xlims(2)]);
  728. ylim([-50, 220]);
  729. box on;
  730. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  731. xlabel('Time [days]','FontSize',14);
  732. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_SUVLong_TOPT.png');
  733. % PLOT - logistic regression for % prob AE
  734. [log_reg_lung, gof_lung, output_lung] = fit(d_lung_MAX(:,ImaxAUC_lung), flags(:,4),'1./(1+exp(-k.*(x-x0)))','start',[1 50]);
  735. log_reg_lung
  736. figure('pos',[100,100, 500, 200], 'Color','w');
  737. scatter(d_lung_MAX(:,ImaxAUC_lung), flags(:,4));
  738. hold on; box on; grid on;
  739. plot(log_reg_lung, d_lung_MAX(:,ImaxAUC_lung), flags(:,4));
  740. xticks([-50:25:225]);
  741. xlim([-50, 225]);
  742. yticks([0:0.2:1]);
  743. xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
  744. ylabel('AE (y/n)','FontSize',14);
  745. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_Logreg.png');
  746. %% PLOT - individual SUVopt vs time with tx and dx start/stops
  747. % pat 608/13
  748. i=18;
  749. n_scans = sum(days(i,:)~=0);
  750. figure('pos',[100,100, 500, 400],'Color','w');
  751. xlims = [-50, 240];
  752. ylims = [-40, 220];
  753. xlim(xlims);
  754. ylim(ylims);
  755. % patch for NC +-sigma
  756. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  757. [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)],...
  758. [0.95 0.95 0.95]);
  759. % text for mu, sigma
  760. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  761. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  762. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  763. hold on; box on; grid on;
  764. % y axis and mu
  765. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  766. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  767. % SUVopt
  768. 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),...
  769. 'LineWidth',2,...
  770. 'Marker','o');
  771. % ICI tx patch BLUE
  772. tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  773. tx.FaceAlpha = 0.1;
  774. tx.EdgeAlpha = 0;
  775. %irAE diagnosis
  776. plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  777. % Imm Supp tx patch GREEN
  778. tx = patch([136 198 198 136], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  779. tx.FaceAlpha = 0.1;
  780. tx.EdgeAlpha = 0;
  781. % Death
  782. plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
  783. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  784. xlabel('Time [days]','FontSize',14);
  785. title('pneumonitisG2 608\_13');
  786. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_608_13.png');
  787. % pat 4982/15
  788. i=11;
  789. n_scans = sum(days(i,:)~=0);
  790. figure('pos',[100,100, 500, 400],'Color','w');
  791. xlims = [-50, 1200];
  792. ylims = [-40, 220];
  793. xlim(xlims);
  794. ylim(ylims);
  795. % patch for NC +-sigma
  796. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  797. [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)],...
  798. [0.95 0.95 0.95]);
  799. % text for mu, sigma
  800. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  801. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  802. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  803. hold on; box on; grid on;
  804. % y axis and mu
  805. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  806. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  807. % SUVopt
  808. 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),...
  809. 'LineWidth',2,...
  810. 'Marker','o');
  811. % ICI tx patch BLUE
  812. tx = patch([0 299 299 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  813. tx.FaceAlpha = 0.1;
  814. tx.EdgeAlpha = 0;
  815. tx = patch([376 xlims(2) xlims(2) 376], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  816. tx.FaceAlpha = 0.1;
  817. tx.EdgeAlpha = 0;
  818. %irAE diagnosis
  819. plot([245 245], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  820. % Imm Supp tx patch GREEN
  821. tx = patch([309 xlims(2) xlims(2) 309], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  822. tx.FaceAlpha = 0.1;
  823. tx.EdgeAlpha = 0;
  824. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  825. xlabel('Time [days]','FontSize',14);
  826. title('pneumonitisG2 4982\_15');
  827. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_4982_15.png');
  828. % pat 112_14
  829. i=1;
  830. n_scans = sum(days(i,:)~=0);
  831. figure('pos',[100,100, 500, 400],'Color','w');
  832. xlims = [-50, 280];
  833. ylims = [-40, 220];
  834. xlim(xlims);
  835. ylim(ylims);
  836. % patch for NC +-sigma
  837. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  838. [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)],...
  839. [0.95 0.95 0.95]);
  840. % text for mu, sigma
  841. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  842. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  843. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  844. hold on; box on; grid on;
  845. % y axis and mu
  846. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  847. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  848. % SUVopt
  849. 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),...
  850. 'LineWidth',2,...
  851. 'Marker','o');
  852. % ICI tx patch BLUE
  853. tx = patch([0 201 201 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  854. tx.FaceAlpha = 0.1;
  855. tx.EdgeAlpha = 0;
  856. % irAE diagnosis
  857. plot([232 232], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  858. % Imm Supp tx patch GREEN
  859. tx = patch([201 xlims(2) xlims(2) 201], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  860. tx.FaceAlpha = 0.1;
  861. tx.EdgeAlpha = 0;
  862. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  863. xlabel('Time [days]','FontSize',14);
  864. title('pneumonitisG4 112\_14');
  865. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_112_14.png');
  866. % pat 2278_07
  867. i=5;
  868. n_scans = sum(days(i,:)~=0);
  869. figure('pos',[100,100, 500, 400],'Color','w');
  870. xlims = [-50, 1500];
  871. ylims = [-40, 220];
  872. xlim(xlims);
  873. ylim(ylims);
  874. % patch for NC +-sigma
  875. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  876. [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)],...
  877. [0.95 0.95 0.95]);
  878. % text for mu, sigma
  879. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  880. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  881. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  882. hold on; box on; grid on;
  883. % y axis and mu
  884. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  885. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  886. % SUVopt
  887. 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),...
  888. 'LineWidth',2,...
  889. 'Marker','o');
  890. % ICI tx patch BLUE
  891. tx = patch([0 218 218 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  892. tx.FaceAlpha = 0.1;
  893. tx.EdgeAlpha = 0;
  894. % irAE diagnosis
  895. plot([191 191], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  896. % Imm Supp tx patch GREEN
  897. tx = patch([225 830 830 225], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  898. tx.FaceAlpha = 0.1;
  899. tx.EdgeAlpha = 0;
  900. % ICI tx patch BLUE
  901. tx = patch([560 590 590 560], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  902. tx.FaceAlpha = 0.1;
  903. tx.EdgeAlpha = 0;
  904. % irAE diagnosis
  905. plot([590 590], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  906. % ICI tx patch BLUE
  907. tx = patch([1447 xlims(2) xlims(2) 1447], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  908. tx.FaceAlpha = 0.1;
  909. tx.EdgeAlpha = 0;
  910. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  911. xlabel('Time [days]','FontSize',14);
  912. title('pneumonitisG2 2279\_07');
  913. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_2278_07.png');
  914. % pat AE6
  915. i=36;
  916. n_scans = sum(days(i,:)~=0);
  917. figure('pos',[100,100, 500, 400],'Color','w');
  918. xlims = [-20, 450];
  919. ylims = [-40, 220];
  920. xlim(xlims);
  921. ylim(ylims);
  922. % patch for NC +-sigma
  923. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  924. [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)],...
  925. [0.95 0.95 0.95]);
  926. % text for mu, sigma
  927. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  928. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  929. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  930. hold on; box on; grid on;
  931. % y axis and mu
  932. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  933. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  934. % SUVopt
  935. 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),...
  936. 'LineWidth',2,...
  937. 'Marker','o');
  938. % ICI tx patch BLUE
  939. tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  940. tx.FaceAlpha = 0.1;
  941. tx.EdgeAlpha = 0;
  942. tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  943. tx.FaceAlpha = 0.1;
  944. tx.EdgeAlpha = 0;
  945. % irAE diagnosis
  946. plot([273 273], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  947. % Imm Supp tx patch GREEN
  948. tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  949. tx.FaceAlpha = 0.1;
  950. tx.EdgeAlpha = 0;
  951. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  952. tx.FaceAlpha = 0.1;
  953. tx.EdgeAlpha = 0;
  954. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  955. xlabel('Time [days]','FontSize',14);
  956. title('pneumonitis ae6');
  957. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_ae6.png');
  958. %% PLOT - individual SUVopt vs time with tx and dx start/stops
  959. % pat 608/13
  960. i=18;
  961. n_scans = sum(days(i,:)~=0);
  962. figure('pos',[100,100, 500, 400],'Color','w');
  963. xlims = [-80, 1600];
  964. ylims = [-40, 220];
  965. xlim(xlims);
  966. ylim(ylims);
  967. % patch for NC +-sigma
  968. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  969. [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)],...
  970. [0.95 0.95 0.95]);
  971. % text for mu, sigma
  972. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  973. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  974. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  975. hold on; box on; grid on;
  976. % y axis and mu
  977. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  978. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  979. % SUVopt
  980. 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),...
  981. 'LineWidth',2,...
  982. 'Marker','o');
  983. % ICI tx patch BLUE
  984. tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  985. tx.FaceAlpha = 0.1;
  986. tx.EdgeAlpha = 0;
  987. %irAE diagnosis
  988. plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  989. % Imm Supp tx patch GREEN
  990. tx = patch([136 198 198 136], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  991. tx.FaceAlpha = 0.1;
  992. tx.EdgeAlpha = 0;
  993. % Death
  994. plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
  995. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  996. xlabel('Time [days]','FontSize',14);
  997. title('pneumonitisG2 608\_13');
  998. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_608_13_fixedtime.png');
  999. % pat 4982/15
  1000. i=11;
  1001. n_scans = sum(days(i,:)~=0);
  1002. figure('pos',[100,100, 500, 400],'Color','w');
  1003. xlims = [-80, 1600];
  1004. ylims = [-40, 220];
  1005. xlim(xlims);
  1006. ylim(ylims);
  1007. % patch for NC +-sigma
  1008. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1009. [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)],...
  1010. [0.95 0.95 0.95]);
  1011. % text for mu, sigma
  1012. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1013. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1014. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1015. hold on; box on; grid on;
  1016. % y axis and mu
  1017. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1018. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  1019. % SUVopt
  1020. 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),...
  1021. 'LineWidth',2,...
  1022. 'Marker','o');
  1023. % ICI tx patch BLUE
  1024. tx = patch([0 299 299 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1025. tx.FaceAlpha = 0.1;
  1026. tx.EdgeAlpha = 0;
  1027. tx = patch([376 xlims(2) xlims(2) 376], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1028. tx.FaceAlpha = 0.1;
  1029. tx.EdgeAlpha = 0;
  1030. %irAE diagnosis
  1031. plot([245 245], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1032. % Imm Supp tx patch GREEN
  1033. tx = patch([309 xlims(2) xlims(2) 309], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1034. tx.FaceAlpha = 0.1;
  1035. tx.EdgeAlpha = 0;
  1036. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1037. xlabel('Time [days]','FontSize',14);
  1038. title('pneumonitisG2 4982\_15');
  1039. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_4982_15_fixedtime.png');
  1040. % pat 112_14
  1041. i=1;
  1042. n_scans = sum(days(i,:)~=0);
  1043. figure('pos',[100,100, 500, 400],'Color','w');
  1044. xlims = [-80, 1600];
  1045. ylims = [-40, 220];
  1046. xlim(xlims);
  1047. ylim(ylims);
  1048. % patch for NC +-sigma
  1049. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1050. [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)],...
  1051. [0.95 0.95 0.95]);
  1052. % text for mu, sigma
  1053. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1054. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1055. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1056. hold on; box on; grid on;
  1057. % y axis and mu
  1058. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1059. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  1060. % SUVopt
  1061. 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),...
  1062. 'LineWidth',2,...
  1063. 'Marker','o');
  1064. % ICI tx patch BLUE
  1065. tx = patch([0 201 201 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1066. tx.FaceAlpha = 0.1;
  1067. tx.EdgeAlpha = 0;
  1068. % irAE diagnosis
  1069. plot([232 232], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1070. % Imm Supp tx patch GREEN
  1071. tx = patch([201 xlims(2) xlims(2) 201], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1072. tx.FaceAlpha = 0.1;
  1073. tx.EdgeAlpha = 0;
  1074. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1075. xlabel('Time [days]','FontSize',14);
  1076. title('pneumonitisG4 112\_14');
  1077. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_112_14_fixedtime.png');
  1078. % pat 2278_07
  1079. i=5;
  1080. n_scans = sum(days(i,:)~=0);
  1081. figure('pos',[100,100, 500, 400],'Color','w');
  1082. xlims = [-80, 1600];
  1083. ylims = [-40, 220];
  1084. xlim(xlims);
  1085. ylim(ylims);
  1086. % patch for NC +-sigma
  1087. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1088. [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)],...
  1089. [0.95 0.95 0.95]);
  1090. % text for mu, sigma
  1091. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1092. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1093. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1094. hold on; box on; grid on;
  1095. % y axis and mu
  1096. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1097. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  1098. % SUVopt
  1099. 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),...
  1100. 'LineWidth',2,...
  1101. 'Marker','o');
  1102. % ICI tx patch BLUE
  1103. tx = patch([0 218 218 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1104. tx.FaceAlpha = 0.1;
  1105. tx.EdgeAlpha = 0;
  1106. % irAE diagnosis
  1107. plot([191 191], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1108. % Imm Supp tx patch GREEN
  1109. tx = patch([225 830 830 225], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1110. tx.FaceAlpha = 0.1;
  1111. tx.EdgeAlpha = 0;
  1112. % ICI tx patch BLUE
  1113. tx = patch([560 590 590 560], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1114. tx.FaceAlpha = 0.1;
  1115. tx.EdgeAlpha = 0;
  1116. % irAE diagnosis
  1117. plot([590 590], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1118. % ICI tx patch BLUE
  1119. tx = patch([1447 xlims(2) xlims(2) 1447], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1120. tx.FaceAlpha = 0.1;
  1121. tx.EdgeAlpha = 0;
  1122. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1123. xlabel('Time [days]','FontSize',14);
  1124. title('pneumonitisG2 2279\_07');
  1125. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_2278_07_fixedtime.png');
  1126. % pat AE6
  1127. i=36;
  1128. n_scans = sum(days(i,:)~=0);
  1129. figure('pos',[100,100, 500, 400],'Color','w');
  1130. xlims = [-80, 1600];
  1131. ylims = [-40, 220];
  1132. xlim(xlims);
  1133. ylim(ylims);
  1134. % patch for NC +-sigma
  1135. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1136. [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)],...
  1137. [0.95 0.95 0.95]);
  1138. % text for mu, sigma
  1139. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1140. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)+sigma_lung_NC(ImaxAUC_lung), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1141. text(0.98.*xlims(2), mu_lung_NC(ImaxAUC_lung)-sigma_lung_NC(ImaxAUC_lung), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1142. hold on; box on; grid on;
  1143. % y axis and mu
  1144. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1145. plot([xlims(1), xlims(2)], [mu_lung_NC(ImaxAUC_lung), mu_lung_NC(ImaxAUC_lung)], 'k-', 'LineWidth',2);
  1146. % SUVopt
  1147. 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),...
  1148. 'LineWidth',2,...
  1149. 'Marker','o');
  1150. % ICI tx patch BLUE
  1151. tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1152. tx.FaceAlpha = 0.1;
  1153. tx.EdgeAlpha = 0;
  1154. tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1155. tx.FaceAlpha = 0.1;
  1156. tx.EdgeAlpha = 0;
  1157. % irAE diagnosis
  1158. plot([273 273], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1159. % Imm Supp tx patch GREEN
  1160. tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1161. tx.FaceAlpha = 0.1;
  1162. tx.EdgeAlpha = 0;
  1163. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1164. tx.FaceAlpha = 0.1;
  1165. tx.EdgeAlpha = 0;
  1166. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1167. xlabel('Time [days]','FontSize',14);
  1168. title('pneumonitis ae6');
  1169. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\pneumonitis_ae6_fixedtime.png');
  1170. %% BOWEL - USING MAX (N=64 NC vs N=6 AE)
  1171. xlims = [-100, 1200]; %for SUV longitudinal plots - in days
  1172. % Compute relative bowel change for all patients, all percentiles
  1173. for i=1:58
  1174. n_scans = sum(days(i,:)~=0);
  1175. 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);
  1176. % Take MAX over time points
  1177. d_bowel_MAX(i,:) = squeeze(max(d_bowel(i,2:n_scans,:),[],2));
  1178. end
  1179. % Compute ROC stats for every SUV percentile 1-100
  1180. for i=1:100
  1181. [~,~,~,temp_AUC,~] = perfcurve(flags(:,2),d_bowel_MAX(:,i),1);
  1182. AUC_bowel(i) = temp_AUC;
  1183. end
  1184. % Determine optimal percentile SUVxx that maximizes AUC
  1185. [maxAUC_bowel, ImaxAUC_bowel] = max(AUC_bowel);
  1186. %redo AUC to get X, Y for optimal SUVxx
  1187. [OPT_X_bowel,OPT_Y_bowel,OPT_T_bowel,OPT_AUC_bowel] = perfcurve(flags(:,2),d_bowel_MAX(:,ImaxAUC_bowel),1);
  1188. %pick optimal operating pt by sum of sensitivity and specificity
  1189. t = 1-OPT_X_bowel+OPT_Y_bowel;
  1190. [~,ii] = max(t);
  1191. OPT_OPT_T_bowel = OPT_T_bowel(ii);
  1192. OPT_ROCPT_bowel = [1-OPT_X_bowel(ii), OPT_Y_bowel(ii)];
  1193. % Compute mean and sd for NC patients for plotting normal range
  1194. d_bowel_NC = d_bowel(flags(:,2)==0,:,:);
  1195. mu_bowel_NC = squeeze(mean(d_bowel_NC(:,2,:), 1));
  1196. sigma_bowel_NC = squeeze(std(d_bowel_NC(:,2,:), 1));
  1197. % Plot: AUC vs SUV percentile
  1198. figure('pos',[200, 800, 400, 400], 'Color','w');
  1199. plot([1:100], AUC_bowel, 'LineWidth',2);
  1200. hold on; grid on;
  1201. plot([0,100], [0.5, 0.5],'k-');
  1202. xlabel('SUV percentile','FontSize',14);
  1203. ylabel('AUC','FontSize',14);
  1204. ylim([0.4, 1]);
  1205. text(10,0.9, ['Optimal %ile: ' num2str(ImaxAUC_bowel)], 'FontSize',12)
  1206. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_AUCvsSUVperc.png');
  1207. % Plot: Paired boxplots for SUVxx that produce highest AUC
  1208. figure('pos',[700, 800, 300, 400], 'Color','w');
  1209. boxplot(d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2), 'Labels',{'NC (n=64)','AE (n=6)'});
  1210. ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
  1211. grid on;
  1212. lines = findobj(gcf, 'type', 'line');
  1213. set(lines,'LineWidth',1.5);
  1214. hold on;
  1215. plot([0,3], [OPT_OPT_T_bowel, OPT_OPT_T_bowel], 'k-');
  1216. p_bowel = ranksum(d_bowel_MAX(find(~flags(:,2)), ImaxAUC_bowel) ,d_bowel_MAX(find(flags(:,2)), ImaxAUC_bowel));
  1217. text(1.5, 180, ['p = 1e-3'],'HorizontalAlignment','center');
  1218. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_boxplots.png');
  1219. % Plot: ROC curve for SUVxx that produced highest AUC
  1220. figure('pos',[1100, 800, 400, 400], 'Color','w');
  1221. plot(1-OPT_X_bowel, OPT_Y_bowel,'LineWidth',2);
  1222. hold on; grid on;
  1223. scatter(OPT_ROCPT_bowel(1), OPT_ROCPT_bowel(2), 'ro');
  1224. set(gca, 'XDir','reverse');
  1225. xlabel('Specificity','FontSize',14);
  1226. ylabel('Sensitivity','FontSize',14);
  1227. text(0.05, 0.25, ['AUC = ' num2str(round(OPT_AUC_bowel,3))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1228. text(0.05, 0.2, ['Sens = ' num2str(round(OPT_ROCPT_bowel(2),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1229. text(0.05, 0.15, ['Spec = ' num2str(round(OPT_ROCPT_bowel(1),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1230. text(0.05, 0.08, ['T_{opt} = +' num2str(round(OPT_OPT_T_bowel,1)) '%'],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1231. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_ROC.png');
  1232. % Plot: Longitudinal SUVxx with normal range
  1233. figure('pos',[200, 200, 800, 400], 'Color','w');
  1234. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1235. [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)],...
  1236. [0.95 0.95 0.95]);
  1237. hold on; grid on;
  1238. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1239. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1240. 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);
  1241. 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);
  1242. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1243. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1244. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1245. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+2.*sigma_bowel_NC(ImaxAUC_bowel), '+2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1246. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-2.*sigma_bowel_NC(ImaxAUC_bowel), '-2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1247. for i=1:58
  1248. if flags(i,2) == 1;
  1249. n_scans = sum(days(i,:)~=0);
  1250. if i<=30
  1251. plot(days(i, 1:n_scans), ...
  1252. 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
  1253. ':o',...
  1254. 'LineWidth',2,...
  1255. 'Color','k');
  1256. else
  1257. plot(days(i, 1:n_scans), ...
  1258. 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
  1259. '-.o',...
  1260. 'LineWidth',2,...
  1261. 'Color','r');
  1262. end
  1263. hold on; grid on;
  1264. end
  1265. end
  1266. xlim([xlims(1) xlims(2)]);
  1267. ylim([-60, 140]);
  1268. box on;
  1269. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1270. xlabel('Time [days]','FontSize',14);
  1271. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_SUVLong_CI.png');
  1272. % Plot: Longitudinal SUVxx with optimal threshold
  1273. figure('pos',[1200, 200, 800, 400], 'Color','w');
  1274. xlims = [-100, 1000];
  1275. hold on; grid on;
  1276. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1277. plot([xlims(1), xlims(2)], [OPT_OPT_T_bowel, OPT_OPT_T_bowel], '-','Color','k', 'LineWidth',2);
  1278. for i=1:58
  1279. if flags(i,2) == 1;
  1280. n_scans = sum(days(i,:)~=0);
  1281. if i<=30
  1282. plot(days(i, 1:n_scans), ...
  1283. 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
  1284. ':o',...
  1285. 'LineWidth',2,...
  1286. 'Color','k');
  1287. else
  1288. plot(days(i, 1:n_scans), ...
  1289. 100.*(bowel_SUVperc_COMBINED(i, flags(i,1)+[0:n_scans-1], ImaxAUC_bowel)./bowel_SUVperc_COMBINED(i, flags(i,1), ImaxAUC_bowel) - 1), ...
  1290. '-.o',...
  1291. 'LineWidth',2,...
  1292. 'Color','r');
  1293. end
  1294. hold on; grid on;
  1295. end
  1296. end
  1297. xlim([xlims(1) xlims(2)]);
  1298. ylim([-60, 140]);
  1299. box on;
  1300. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1301. xlabel('Time [days]','FontSize',14);
  1302. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_SUVLong_TOPT.png');
  1303. % PLOT - logistic regression for % prob AE
  1304. [log_reg_bowel, gof_bowel, output_bowel] = fit(d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2),'1./(1+exp(-k.*(x-x0)))','start',[1 50]);
  1305. log_reg_bowel
  1306. figure('pos',[100,100, 500, 200], 'Color','w');
  1307. scatter(d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2));
  1308. hold on; box on; grid on;
  1309. plot(log_reg_bowel, d_bowel_MAX(:,ImaxAUC_bowel), flags(:,2));
  1310. xticks([-50:50:400]);
  1311. yticks([0:0.2:1]);
  1312. xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
  1313. ylabel('AE (y/n)','FontSize',14);
  1314. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_Logreg.png');
  1315. % PLOT - logistic regression for % prob AE
  1316. ind = [1,3:10,12:58];
  1317. [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]);
  1318. figure('pos',[100,100, 500, 200], 'Color','w');
  1319. scatter(d_bowel_MAX(ind,ImaxAUC_bowel), flags(ind,2));
  1320. hold on; box on; grid on;
  1321. plot(log_reg_bowel2, d_bowel_MAX(ind,ImaxAUC_bowel), flags(ind,2));
  1322. xticks([-50:50:400]);
  1323. yticks([0:0.2:1]);
  1324. xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
  1325. ylabel('AE (y/n)','FontSize',14);
  1326. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_Logreg_no_outliers.png');
  1327. %% Individual patients with colitis AE
  1328. % pat 5490_15
  1329. i=15;
  1330. n_scans = sum(days(i,:)~=0);
  1331. figure('pos',[100,100, 500, 400],'Color','w');
  1332. xlims = [-80, 150];
  1333. ylims = [-40, 220];
  1334. xlim(xlims);
  1335. ylim(ylims);
  1336. % patch for NC +-sigma
  1337. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1338. [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)],...
  1339. [0.95 0.95 0.95]);
  1340. % text for mu, sigma
  1341. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1342. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1343. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1344. hold on; box on; grid on;
  1345. % y axis and mu
  1346. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1347. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1348. % SUVopt
  1349. 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),...
  1350. 'LineWidth',2,...
  1351. 'Marker','o');
  1352. % ICI tx patch BLUE
  1353. tx = patch([0 65 65 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1354. tx.FaceAlpha = 0.1;
  1355. tx.EdgeAlpha = 0;
  1356. % irAE diagnosis
  1357. plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1358. % Imm Supp tx patch GREEN
  1359. tx = patch([65 110 100 65], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1360. tx.FaceAlpha = 0.1;
  1361. tx.EdgeAlpha = 0;
  1362. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1363. xlabel('Time [days]','FontSize',14);
  1364. title('colitisG2 5490\_15');
  1365. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5490_15.png');
  1366. %% pat 5003_16
  1367. i=12;
  1368. n_scans = sum(days(i,:)~=0);
  1369. figure('pos',[100,100, 500, 400],'Color','w');
  1370. xlims = [-80, 320];
  1371. ylims = [-40, 220];
  1372. xlim(xlims);
  1373. ylim(ylims);
  1374. % patch for NC +-sigma
  1375. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1376. [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)],...
  1377. [0.95 0.95 0.95]);
  1378. % text for mu, sigma
  1379. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1380. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1381. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1382. hold on; box on; grid on;
  1383. % y axis and mu
  1384. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1385. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1386. % SUVopt
  1387. 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),...
  1388. 'LineWidth',2,...
  1389. 'Marker','o');
  1390. % ICI tx patch BLUE
  1391. tx = patch([0 196 196 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1392. tx.FaceAlpha = 0.1;
  1393. tx.EdgeAlpha = 0;
  1394. % irAE diagnosis
  1395. plot([173 173], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1396. % Imm Supp tx patch GREEN
  1397. tx = patch([196 238 238 196], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1398. tx.FaceAlpha = 0.1;
  1399. tx.EdgeAlpha = 0;
  1400. % ICI tx patch BLUE
  1401. tx = patch([238 308 308 238], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1402. tx.FaceAlpha = 0.1;
  1403. tx.EdgeAlpha = 0;
  1404. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1405. xlabel('Time [days]','FontSize',14);
  1406. title('colitisG2 5003\_16');
  1407. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5003_16.png');
  1408. %% pat ae6
  1409. i=36;
  1410. n_scans = sum(days(i,:)~=0);
  1411. figure('pos',[100,100, 500, 400],'Color','w');
  1412. xlims = [-80, 450];
  1413. ylims = [-40, 220];
  1414. xlim(xlims);
  1415. ylim(ylims);
  1416. % patch for NC +-sigma
  1417. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1418. [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)],...
  1419. [0.95 0.95 0.95]);
  1420. % text for mu, sigma
  1421. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1422. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1423. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1424. hold on; box on; grid on;
  1425. % y axis and mu
  1426. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1427. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1428. % SUVopt
  1429. 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),...
  1430. 'LineWidth',2,...
  1431. 'Marker','o');
  1432. % ICI tx patch BLUE
  1433. tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1434. tx.FaceAlpha = 0.1;
  1435. tx.EdgeAlpha = 0;
  1436. tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1437. tx.FaceAlpha = 0.1;
  1438. tx.EdgeAlpha = 0;
  1439. % irAE diagnosis
  1440. plot([195 195], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1441. % Imm Supp tx patch GREEN
  1442. tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1443. tx.FaceAlpha = 0.1;
  1444. tx.EdgeAlpha = 0;
  1445. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1446. tx.FaceAlpha = 0.1;
  1447. tx.EdgeAlpha = 0;
  1448. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1449. xlabel('Time [days]','FontSize',14);
  1450. title('colitisG3 ae6');
  1451. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae6.png');
  1452. %% pat ae10
  1453. i=39;
  1454. n_scans = sum(days(i,:)~=0);
  1455. figure('pos',[100,100, 500, 400],'Color','w');
  1456. xlims = [-80, 1000];
  1457. ylims = [-40, 220];
  1458. xlim(xlims);
  1459. ylim(ylims);
  1460. % patch for NC +-sigma
  1461. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1462. [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)],...
  1463. [0.95 0.95 0.95]);
  1464. % text for mu, sigma
  1465. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1466. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1467. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1468. hold on; box on; grid on;
  1469. % y axis and mu
  1470. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1471. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1472. % SUVopt
  1473. 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),...
  1474. 'LineWidth',2,...
  1475. 'Marker','o');
  1476. % ICI tx patch BLUE
  1477. tx = patch([0 760 760 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1478. tx.FaceAlpha = 0.1;
  1479. tx.EdgeAlpha = 0;
  1480. % irAE diagnosis
  1481. plot([32 32], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1482. plot([774 774], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1483. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1484. xlabel('Time [days]','FontSize',14);
  1485. title('colitisG2 ae10');
  1486. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae10.png');
  1487. %% AE 11
  1488. i=40;
  1489. n_scans = sum(days(i,:)~=0);
  1490. figure('pos',[100,100, 500, 400],'Color','w');
  1491. xlims = [-80, 350];
  1492. ylims = [-40, 220];
  1493. xlim(xlims);
  1494. ylim(ylims);
  1495. % patch for NC +-sigma
  1496. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1497. [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)],...
  1498. [0.95 0.95 0.95]);
  1499. % text for mu, sigma
  1500. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1501. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1502. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1503. hold on; box on; grid on;
  1504. % y axis and mu
  1505. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1506. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1507. % SUVopt
  1508. 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),...
  1509. 'LineWidth',2,...
  1510. 'Marker','o');
  1511. % ICI tx patch BLUE
  1512. tx = patch([0 296 296 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1513. tx.FaceAlpha = 0.1;
  1514. tx.EdgeAlpha = 0;
  1515. % irAE diagnosis
  1516. plot([302 302], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1517. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1518. xlabel('Time [days]','FontSize',14);
  1519. title('colitisG3 ae11');
  1520. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae11.png');
  1521. %% AE 17
  1522. i=46;
  1523. n_scans = sum(days(i,:)~=0);
  1524. figure('pos',[100,100, 500, 400],'Color','w');
  1525. xlims = [-100, 550];
  1526. ylims = [-40, 220];
  1527. xlim(xlims);
  1528. ylim(ylims);
  1529. % patch for NC +-sigma
  1530. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1531. [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)],...
  1532. [0.95 0.95 0.95]);
  1533. % text for mu, sigma
  1534. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1535. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1536. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1537. hold on; box on; grid on;
  1538. % y axis and mu
  1539. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1540. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1541. % SUVopt
  1542. 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),...
  1543. 'LineWidth',2,...
  1544. 'Marker','o');
  1545. % ICI tx patch BLUE
  1546. tx = patch([0 155 155 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1547. tx.FaceAlpha = 0.1;
  1548. tx.EdgeAlpha = 0;
  1549. % irAE diagnosis
  1550. plot([231 231], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1551. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1552. xlabel('Time [days]','FontSize',14);
  1553. title('colitisG2 ae17');
  1554. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae17.png');
  1555. %% Individual patients, same xlims
  1556. % pat 5490_15
  1557. i=15;
  1558. n_scans = sum(days(i,:)~=0);
  1559. figure('pos',[100,100, 500, 400],'Color','w');
  1560. xlims = [-100, 1000];
  1561. ylims = [-40, 220];
  1562. xlim(xlims);
  1563. ylim(ylims);
  1564. % patch for NC +-sigma
  1565. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1566. [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)],...
  1567. [0.95 0.95 0.95]);
  1568. % text for mu, sigma
  1569. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1570. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1571. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1572. hold on; box on; grid on;
  1573. % y axis and mu
  1574. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1575. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1576. % SUVopt
  1577. 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),...
  1578. 'LineWidth',2,...
  1579. 'Marker','o');
  1580. % ICI tx patch BLUE
  1581. tx = patch([0 65 65 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1582. tx.FaceAlpha = 0.1;
  1583. tx.EdgeAlpha = 0;
  1584. % irAE diagnosis
  1585. plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1586. % Imm Supp tx patch GREEN
  1587. tx = patch([65 110 100 65], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1588. tx.FaceAlpha = 0.1;
  1589. tx.EdgeAlpha = 0;
  1590. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1591. xlabel('Time [days]','FontSize',14);
  1592. title('colitisG2 5490\_15');
  1593. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5490_15_fixedtime.png');
  1594. % pat 5003_16
  1595. i=12;
  1596. n_scans = sum(days(i,:)~=0);
  1597. figure('pos',[100,100, 500, 400],'Color','w');
  1598. xlims = [-100, 1000];
  1599. ylims = [-40, 220];
  1600. xlim(xlims);
  1601. ylim(ylims);
  1602. % patch for NC +-sigma
  1603. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1604. [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)],...
  1605. [0.95 0.95 0.95]);
  1606. % text for mu, sigma
  1607. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1608. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1609. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1610. hold on; box on; grid on;
  1611. % y axis and mu
  1612. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1613. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1614. % SUVopt
  1615. 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),...
  1616. 'LineWidth',2,...
  1617. 'Marker','o');
  1618. % ICI tx patch BLUE
  1619. tx = patch([0 196 196 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1620. tx.FaceAlpha = 0.1;
  1621. tx.EdgeAlpha = 0;
  1622. % irAE diagnosis
  1623. plot([173 173], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1624. % Imm Supp tx patch GREEN
  1625. tx = patch([196 238 238 196], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1626. tx.FaceAlpha = 0.1;
  1627. tx.EdgeAlpha = 0;
  1628. % ICI tx patch BLUE
  1629. tx = patch([238 308 308 238], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1630. tx.FaceAlpha = 0.1;
  1631. tx.EdgeAlpha = 0;
  1632. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1633. xlabel('Time [days]','FontSize',14);
  1634. title('colitisG2 5003\_16');
  1635. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_5003_16_fixedtime.png');
  1636. % pat ae6
  1637. i=36;
  1638. n_scans = sum(days(i,:)~=0);
  1639. figure('pos',[100,100, 500, 400],'Color','w');
  1640. xlims = [-100, 1000];
  1641. ylims = [-40, 220];
  1642. xlim(xlims);
  1643. ylim(ylims);
  1644. % patch for NC +-sigma
  1645. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1646. [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)],...
  1647. [0.95 0.95 0.95]);
  1648. % text for mu, sigma
  1649. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1650. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1651. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1652. hold on; box on; grid on;
  1653. % y axis and mu
  1654. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1655. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1656. % SUVopt
  1657. 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),...
  1658. 'LineWidth',2,...
  1659. 'Marker','o');
  1660. % ICI tx patch BLUE
  1661. tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1662. tx.FaceAlpha = 0.1;
  1663. tx.EdgeAlpha = 0;
  1664. tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1665. tx.FaceAlpha = 0.1;
  1666. tx.EdgeAlpha = 0;
  1667. % irAE diagnosis
  1668. plot([195 195], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1669. % Imm Supp tx patch GREEN
  1670. tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1671. tx.FaceAlpha = 0.1;
  1672. tx.EdgeAlpha = 0;
  1673. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1674. tx.FaceAlpha = 0.1;
  1675. tx.EdgeAlpha = 0;
  1676. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1677. xlabel('Time [days]','FontSize',14);
  1678. title('colitisG3 ae6');
  1679. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae6_fixedtime.png');
  1680. % pat ae10
  1681. i=39;
  1682. n_scans = sum(days(i,:)~=0);
  1683. figure('pos',[100,100, 500, 400],'Color','w');
  1684. xlims = [-100, 1000];
  1685. ylims = [-40, 220];
  1686. xlim(xlims);
  1687. ylim(ylims);
  1688. % patch for NC +-sigma
  1689. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1690. [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)],...
  1691. [0.95 0.95 0.95]);
  1692. % text for mu, sigma
  1693. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1694. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1695. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1696. hold on; box on; grid on;
  1697. % y axis and mu
  1698. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1699. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1700. % SUVopt
  1701. 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),...
  1702. 'LineWidth',2,...
  1703. 'Marker','o');
  1704. % ICI tx patch BLUE
  1705. tx = patch([0 760 760 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1706. tx.FaceAlpha = 0.1;
  1707. tx.EdgeAlpha = 0;
  1708. % irAE diagnosis
  1709. plot([32 32], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1710. plot([774 774], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1711. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1712. xlabel('Time [days]','FontSize',14);
  1713. title('colitisG2 ae10');
  1714. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae10_fixedtime.png');
  1715. % AE 11
  1716. i=40;
  1717. n_scans = sum(days(i,:)~=0);
  1718. figure('pos',[100,100, 500, 400],'Color','w');
  1719. xlims = [-100, 1000];
  1720. ylims = [-40, 220];
  1721. xlim(xlims);
  1722. ylim(ylims);
  1723. % patch for NC +-sigma
  1724. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1725. [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)],...
  1726. [0.95 0.95 0.95]);
  1727. % text for mu, sigma
  1728. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1729. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1730. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1731. hold on; box on; grid on;
  1732. % y axis and mu
  1733. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1734. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1735. % SUVopt
  1736. 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),...
  1737. 'LineWidth',2,...
  1738. 'Marker','o');
  1739. % ICI tx patch BLUE
  1740. tx = patch([0 296 296 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1741. tx.FaceAlpha = 0.1;
  1742. tx.EdgeAlpha = 0;
  1743. % irAE diagnosis
  1744. plot([302 302], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1745. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1746. xlabel('Time [days]','FontSize',14);
  1747. title('colitisG3 ae11');
  1748. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae11_fixedtime.png');
  1749. % AE 17
  1750. i=46;
  1751. n_scans = sum(days(i,:)~=0);
  1752. figure('pos',[100,100, 500, 400],'Color','w');
  1753. xlims = [-100, 1000];
  1754. ylims = [-40, 220];
  1755. xlim(xlims);
  1756. ylim(ylims);
  1757. % patch for NC +-sigma
  1758. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1759. [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)],...
  1760. [0.95 0.95 0.95]);
  1761. % text for mu, sigma
  1762. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1763. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)+sigma_bowel_NC(ImaxAUC_bowel), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1764. text(0.98.*xlims(2), mu_bowel_NC(ImaxAUC_bowel)-sigma_bowel_NC(ImaxAUC_bowel), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1765. hold on; box on; grid on;
  1766. % y axis and mu
  1767. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1768. plot([xlims(1), xlims(2)], [mu_bowel_NC(ImaxAUC_bowel), mu_bowel_NC(ImaxAUC_bowel)], 'k-', 'LineWidth',2);
  1769. % SUVopt
  1770. 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),...
  1771. 'LineWidth',2,...
  1772. 'Marker','o');
  1773. % ICI tx patch BLUE
  1774. tx = patch([0 155 155 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1775. tx.FaceAlpha = 0.1;
  1776. tx.EdgeAlpha = 0;
  1777. % irAE diagnosis
  1778. plot([231 231], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1779. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1780. xlabel('Time [days]','FontSize',14);
  1781. title('colitisG2 ae17');
  1782. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\colitis_ae17_fixedtime.png');
  1783. %% thyroid - USING MAX (N=59 NC vs N=11 AE)
  1784. xlims = [-350, 1200]; %for SUV longitudinal plots - in days
  1785. thyroid_ind = [1:16,18:22, 24:31, 33:37, 39:49, 52:63, 65:70];
  1786. thyroid_ind = [1:58];
  1787. thyroid_SUVperc_COMBINED = thyroid_SUVperc_COMBINED(thyroid_ind, :, :);
  1788. flags_thyroid = flags(thyroid_ind,:);
  1789. patients_thyroid = patients(thyroid_ind);
  1790. days_thyroid = days(thyroid_ind,:);
  1791. % Compute relative thyroid change for all patients, all percentiles
  1792. for i=1:numel(thyroid_ind)
  1793. n_scans = sum(days_thyroid(i,:)~=0);
  1794. 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);
  1795. % Take MAX over time points
  1796. d_thyroid_MAX(i,:) = squeeze(max(d_thyroid(i,2:n_scans,:),[],2));
  1797. end
  1798. % Compute ROC stats for every SUV percentile 1-100
  1799. for i=1:100
  1800. [~,~,~,temp_AUC,~] = perfcurve(flags_thyroid(:,6),d_thyroid_MAX(:,i),1);
  1801. AUC_thyroid(i) = temp_AUC;
  1802. end
  1803. % Determine optimal percentile SUVxx that maximizes AUC
  1804. [maxAUC_thyroid, ImaxAUC_thyroid] = max(AUC_thyroid);
  1805. %redo AUC to get X, Y for optimal SUVxx
  1806. [OPT_X_thyroid,OPT_Y_thyroid,OPT_T_thyroid,OPT_AUC_thyroid] = perfcurve(flags_thyroid(:,6),d_thyroid_MAX(:,ImaxAUC_thyroid),1);
  1807. t = 1-OPT_X_thyroid+OPT_Y_thyroid;
  1808. [~,ii] = max(t);
  1809. OPT_OPT_T_thyroid = OPT_T_thyroid(ii);
  1810. OPT_ROCPT_thyroid = [1-OPT_X_thyroid(ii), OPT_Y_thyroid(ii)];
  1811. % Compute mean and sd for NC patients for plotting normal range
  1812. d_thyroid_NC = d_thyroid(flags_thyroid(:,6)==0,:,:);
  1813. mu_thyroid_NC = squeeze(mean(d_thyroid_NC(:,2,:), 1));
  1814. sigma_thyroid_NC = squeeze(std(d_thyroid_NC(:,2,:), 1));
  1815. % Plot: AUC vs SUV percentile
  1816. figure('pos',[200, 800, 400, 400], 'Color','w');
  1817. plot([1:100], AUC_thyroid, 'LineWidth',2);
  1818. hold on; grid on;
  1819. plot([0,100], [0.5, 0.5],'k-');
  1820. xlabel('SUV percentile','FontSize',14);
  1821. ylabel('AUC','FontSize',14);
  1822. ylim([0.4, 1]);
  1823. text(10,0.9, ['Optimal %ile: ' num2str(ImaxAUC_thyroid)], 'FontSize',12)
  1824. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_AUCvsSUVperc.png');
  1825. % Plot: Paired boxplots for SUVxx that produce highest AUC
  1826. figure('pos',[700, 800, 300, 400], 'Color','w');
  1827. 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)) ')']});
  1828. ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
  1829. grid on;
  1830. lines = findobj(gcf, 'type', 'line');
  1831. set(lines,'LineWidth',1.5);
  1832. hold on;
  1833. plot([0,3], [OPT_OPT_T_thyroid, OPT_OPT_T_thyroid], 'k-');
  1834. ylim([-60, 250]);
  1835. p_thyroid = ranksum(d_thyroid_MAX(find(~flags_thyroid(:,6)), ImaxAUC_thyroid) ,d_thyroid_MAX(find(flags_thyroid(:,6)), ImaxAUC_thyroid));
  1836. text(1.5, 180, ['p = 6e-6'],'HorizontalAlignment','center');
  1837. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_boxplots.png');
  1838. % Plot: ROC curve for SUVxx that produced highest AUC
  1839. figure('pos',[1100, 800, 400, 400], 'Color','w');
  1840. plot(1-OPT_X_thyroid, OPT_Y_thyroid,'LineWidth',2);
  1841. hold on; grid on;
  1842. scatter(OPT_ROCPT_thyroid(1), OPT_ROCPT_thyroid(2), 'ro');
  1843. set(gca, 'XDir','reverse');
  1844. xlabel('Specificity','FontSize',14);
  1845. ylabel('Sensitivity','FontSize',14);
  1846. text(0.05, 0.25, ['AUC = ' num2str(round(OPT_AUC_thyroid,3))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1847. text(0.05, 0.2, ['Sens = ' num2str(round(OPT_ROCPT_thyroid(2),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1848. text(0.05, 0.15, ['Spec = ' num2str(round(OPT_ROCPT_thyroid(1),2))],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1849. text(0.05, 0.08, ['T_{opt} = +' num2str(round(OPT_OPT_T_thyroid,1)) '%'],'FontSize',12,'VerticalAlignment','bottom','HorizontalAlignment', 'right');
  1850. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_ROC.png');
  1851. % Plot: Longitudinal SUVxx with normal range
  1852. figure('pos',[200, 200, 800, 400], 'Color','w');
  1853. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1854. [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)],...
  1855. [0.95 0.95 0.95]);
  1856. hold on; grid on;
  1857. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1858. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  1859. 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);
  1860. 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);
  1861. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1862. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1863. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1864. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+2.*sigma_thyroid_NC(ImaxAUC_thyroid), '+2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1865. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-2.*sigma_thyroid_NC(ImaxAUC_thyroid), '-2\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1866. for i=1:numel(thyroid_ind)
  1867. if flags_thyroid(i,6) == 1;
  1868. n_scans = sum(days_thyroid(i,:)~=0);
  1869. if i<=28
  1870. plot(days_thyroid(i, 1:n_scans), ...
  1871. 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), ...
  1872. ':o',...
  1873. 'LineWidth',2,...
  1874. 'Color','k');
  1875. else
  1876. plot(days_thyroid(i, 1:n_scans), ...
  1877. 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), ...
  1878. '-.o',...
  1879. 'LineWidth',2,...
  1880. 'Color','r');
  1881. end
  1882. hold on; grid on;
  1883. end
  1884. end
  1885. xlim([xlims(1) xlims(2)]);
  1886. ylim([-60, 250]);
  1887. box on;
  1888. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1889. xlabel('Time [days]','FontSize',14);
  1890. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_SUVLong_CI.png');
  1891. % Plot: Longitudinal SUVxx with optimal threshold
  1892. figure('pos',[1200, 200, 800, 400], 'Color','w');
  1893. hold on; grid on;
  1894. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1895. plot([xlims(1), xlims(2)], [OPT_OPT_T_thyroid, OPT_OPT_T_thyroid], '-','Color','k', 'LineWidth',2);
  1896. for i=1:numel(thyroid_ind)
  1897. if flags_thyroid(i,6) == 1;
  1898. n_scans = sum(days_thyroid(i,:)~=0);
  1899. if i<=28
  1900. plot(days_thyroid(i, 1:n_scans), ...
  1901. 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), ...
  1902. ':o',...
  1903. 'LineWidth',2,...
  1904. 'Color','k');
  1905. else
  1906. plot(days_thyroid(i, 1:n_scans), ...
  1907. 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), ...
  1908. '-.o',...
  1909. 'LineWidth',2,...
  1910. 'Color','r');
  1911. end
  1912. %scatter(flags_thyroid(i,7), d_thyroid_MAX(i, ImaxAUC_thyroid), 'bo','filled');
  1913. hold on; grid on;
  1914. end
  1915. end
  1916. xlim([xlims(1) xlims(2)]);
  1917. ylim([-60, 250]);
  1918. box on;
  1919. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1920. xlabel('Time [days]','FontSize',14);
  1921. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_SUVLong_TOPT.png');
  1922. % PLOT - logistic regression for % prob AE
  1923. [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]);
  1924. log_reg_thyroid
  1925. figure('pos',[100,100, 500, 200],'Color','w');
  1926. scatter(d_thyroid_MAX(:,ImaxAUC_thyroid), flags_thyroid(:,6));
  1927. hold on; box on; grid on;
  1928. plot(log_reg_thyroid, d_thyroid_MAX(:,ImaxAUC_thyroid), flags_thyroid(:,6));
  1929. xticks([-50:25:225]);
  1930. yticks([0:0.2:1]);
  1931. xlabel('MAX (\Delta SUV_{OPT%}) [%]','FontSize',14);
  1932. ylabel('AE (y/n)','FontSize',14);
  1933. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_Logreg.png');
  1934. %% Individual patients with thyroid AE
  1935. % use days_thyroid, patients_thyroid
  1936. %% pat 5345_11
  1937. i=13;
  1938. n_scans = sum(days_thyroid(i,:)~=0);
  1939. figure('pos',[100,100, 500, 400],'Color','w');
  1940. xlims = [-320, 1200];
  1941. ylims = [-50, 250];
  1942. xlim(xlims);
  1943. ylim(ylims);
  1944. % patch for NC +-sigma
  1945. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1946. [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)],...
  1947. [0.95 0.95 0.95]);
  1948. % text for mu, sigma
  1949. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1950. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1951. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1952. hold on; box on; grid on;
  1953. % y axis and mu
  1954. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1955. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  1956. % SUVopt
  1957. 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),...
  1958. 'LineWidth',2,...
  1959. 'Marker','o');
  1960. % ICI tx patch BLUE
  1961. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  1962. tx.FaceAlpha = 0.1;
  1963. tx.EdgeAlpha = 0;
  1964. % irAE diagnosis
  1965. plot([225 225], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  1966. % Imm Supp tx patch GREEN
  1967. tx = patch([108 xlims(2) xlims(2) 108], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  1968. tx.FaceAlpha = 0.1;
  1969. tx.EdgeAlpha = 0;
  1970. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  1971. xlabel('Time [days]','FontSize',14);
  1972. title('thyroidG2 5345\_11');
  1973. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_5345_11.png');
  1974. %% pat 7339_11
  1975. i=22;
  1976. n_scans = sum(days_thyroid(i,:)~=0);
  1977. figure('pos',[100,100, 500, 400],'Color','w');
  1978. xlims = [-60, 300];
  1979. ylims = [-50, 250];
  1980. xlim(xlims);
  1981. ylim(ylims);
  1982. % patch for NC +-sigma
  1983. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  1984. [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)],...
  1985. [0.95 0.95 0.95]);
  1986. % text for mu, sigma
  1987. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1988. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1989. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  1990. hold on; box on; grid on;
  1991. % y axis and mu
  1992. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  1993. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  1994. % SUVopt
  1995. 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),...
  1996. 'LineWidth',2,...
  1997. 'Marker','o');
  1998. % ICI tx patch BLUE
  1999. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2000. tx.FaceAlpha = 0.1;
  2001. tx.EdgeAlpha = 0;
  2002. % irAE diagnosis
  2003. plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2004. % Imm Supp tx patch GREEN
  2005. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2006. tx.FaceAlpha = 0.1;
  2007. tx.EdgeAlpha = 0;
  2008. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2009. xlabel('Time [days]','FontSize',14);
  2010. title('thyroidG2 7339\_11');
  2011. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7339_11.png');
  2012. %% pat 6756_12
  2013. i=19;
  2014. n_scans = sum(days_thyroid(i,:)~=0);
  2015. figure('pos',[100,100, 500, 400],'Color','w');
  2016. xlims = [-60, 1500];
  2017. ylims = [-50, 250];
  2018. xlim(xlims);
  2019. ylim(ylims);
  2020. % patch for NC +-sigma
  2021. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2022. [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)],...
  2023. [0.95 0.95 0.95]);
  2024. % text for mu, sigma
  2025. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2026. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2027. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2028. hold on; box on; grid on;
  2029. % y axis and mu
  2030. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2031. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2032. % SUVopt
  2033. 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),...
  2034. 'LineWidth',2,...
  2035. 'Marker','o');
  2036. % ICI tx patch BLUE
  2037. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2038. tx.FaceAlpha = 0.1;
  2039. tx.EdgeAlpha = 0;
  2040. % irAE diagnosis
  2041. plot([630 630], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2042. % Imm Supp tx patch GREEN
  2043. tx = patch([675 xlims(2) xlims(2) 675], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2044. tx.FaceAlpha = 0.1;
  2045. tx.EdgeAlpha = 0;
  2046. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2047. xlabel('Time [days]','FontSize',14);
  2048. title('thyroidG2 6756\_12');
  2049. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_6756_12.png');
  2050. %% pat 608_13
  2051. i=17;
  2052. n_scans = sum(days_thyroid(i,:)~=0);
  2053. figure('pos',[100,100, 500, 400],'Color','w');
  2054. xlims = [-60, 240];
  2055. ylims = [-50, 250];
  2056. xlim(xlims);
  2057. ylim(ylims);
  2058. % patch for NC +-sigma
  2059. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2060. [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)],...
  2061. [0.95 0.95 0.95]);
  2062. % text for mu, sigma
  2063. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2064. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2065. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2066. hold on; box on; grid on;
  2067. % y axis and mu
  2068. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2069. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2070. % SUVopt
  2071. 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),...
  2072. 'LineWidth',2,...
  2073. 'Marker','o');
  2074. % ICI tx patch BLUE
  2075. tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2076. tx.FaceAlpha = 0.1;
  2077. tx.EdgeAlpha = 0;
  2078. % irAE diagnosis
  2079. plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2080. % Death
  2081. plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
  2082. % Imm Supp tx patch GREEN
  2083. tx = patch([140 198 198 140], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2084. tx.FaceAlpha = 0.1;
  2085. tx.EdgeAlpha = 0;
  2086. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2087. xlabel('Time [days]','FontSize',14);
  2088. title('thyroidG2 608\_13');
  2089. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_608_13.png');
  2090. %% pat 7359_09
  2091. i=23;
  2092. n_scans = sum(days_thyroid(i,:)~=0);
  2093. figure('pos',[100,100, 500, 400],'Color','w');
  2094. xlims = [-80, 1050];
  2095. ylims = [-50, 250];
  2096. xlim(xlims);
  2097. ylim(ylims);
  2098. % patch for NC +-sigma
  2099. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2100. [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)],...
  2101. [0.95 0.95 0.95]);
  2102. % text for mu, sigma
  2103. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2104. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2105. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2106. hold on; box on; grid on;
  2107. % y axis and mu
  2108. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2109. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2110. % SUVopt
  2111. 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),...
  2112. 'LineWidth',2,...
  2113. 'Marker','o');
  2114. % ICI tx patch BLUE
  2115. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2116. tx.FaceAlpha = 0.1;
  2117. tx.EdgeAlpha = 0;
  2118. % irAE diagnosis
  2119. plot([108 108], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2120. % Imm Supp tx patch GREEN
  2121. tx = patch([15 xlims(2) xlims(2) 15], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2122. tx.FaceAlpha = 0.1;
  2123. tx.EdgeAlpha = 0;
  2124. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2125. xlabel('Time [days]','FontSize',14);
  2126. title('thyroidG2 7359\_09');
  2127. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7359_09.png');
  2128. %% pat 1127_06
  2129. i=2;
  2130. n_scans = sum(days_thyroid(i,:)~=0);
  2131. figure('pos',[100,100, 500, 400],'Color','w');
  2132. xlims = [-140, 720];
  2133. ylims = [-50, 250];
  2134. xlim(xlims);
  2135. ylim(ylims);
  2136. % patch for NC +-sigma
  2137. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2138. [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)],...
  2139. [0.95 0.95 0.95]);
  2140. % text for mu, sigma
  2141. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2142. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2143. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2144. hold on; box on; grid on;
  2145. % y axis and mu
  2146. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2147. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2148. % SUVopt
  2149. 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),...
  2150. 'LineWidth',2,...
  2151. 'Marker','o');
  2152. % ICI tx patch BLUE
  2153. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2154. tx.FaceAlpha = 0.1;
  2155. tx.EdgeAlpha = 0;
  2156. % irAE diagnosis
  2157. plot([83 83], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2158. % Imm Supp tx patch GREEN
  2159. tx = patch([17 xlims(2) xlims(2) 17], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2160. tx.FaceAlpha = 0.1;
  2161. tx.EdgeAlpha = 0;
  2162. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2163. xlabel('Time [days]','FontSize',14);
  2164. title('thyroidG2 1127\_06');
  2165. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_1127_06.png');
  2166. %% pat ae6
  2167. i=33;
  2168. n_scans = sum(days_thyroid(i,:)~=0);
  2169. figure('pos',[100,100, 500, 400],'Color','w');
  2170. xlims = [-50, 550];
  2171. ylims = [-50, 250];
  2172. xlim(xlims);
  2173. ylim(ylims);
  2174. % patch for NC +-sigma
  2175. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2176. [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)],...
  2177. [0.95 0.95 0.95]);
  2178. % text for mu, sigma
  2179. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2180. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2181. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2182. hold on; box on; grid on;
  2183. % y axis and mu
  2184. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2185. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2186. % SUVopt
  2187. 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),...
  2188. 'LineWidth',2,...
  2189. 'Marker','o');
  2190. % ICI tx patch BLUE
  2191. tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2192. tx.FaceAlpha = 0.1;
  2193. tx.EdgeAlpha = 0;
  2194. tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2195. tx.FaceAlpha = 0.1;
  2196. tx.EdgeAlpha = 0;
  2197. % irAE diagnosis
  2198. plot([76 76], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2199. % Imm Supp tx patch GREEN
  2200. tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2201. tx.FaceAlpha = 0.1;
  2202. tx.EdgeAlpha = 0;
  2203. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2204. tx.FaceAlpha = 0.1;
  2205. tx.EdgeAlpha = 0;
  2206. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2207. xlabel('Time [days]','FontSize',14);
  2208. title('thyroidG2 ae6');
  2209. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae6.png');
  2210. %% pat ae15
  2211. i=40;
  2212. n_scans = sum(days_thyroid(i,:)~=0);
  2213. figure('pos',[100,100, 500, 400],'Color','w');
  2214. xlims = [-30, 400];
  2215. ylims = [-50, 250];
  2216. xlim(xlims);
  2217. ylim(ylims);
  2218. % patch for NC +-sigma
  2219. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2220. [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)],...
  2221. [0.95 0.95 0.95]);
  2222. % text for mu, sigma
  2223. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2224. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2225. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2226. hold on; box on; grid on;
  2227. % y axis and mu
  2228. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2229. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2230. % SUVopt
  2231. 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),...
  2232. 'LineWidth',2,...
  2233. 'Marker','o');
  2234. % ICI tx patch BLUE
  2235. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2236. tx.FaceAlpha = 0.1;
  2237. tx.EdgeAlpha = 0;
  2238. % irAE diagnosis
  2239. plot([27 27], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2240. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2241. xlabel('Time [days]','FontSize',14);
  2242. title('thyroidG2 ae15');
  2243. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae15.png');
  2244. %% pat ae20
  2245. i=45;
  2246. n_scans = sum(days_thyroid(i,:)~=0);
  2247. figure('pos',[100,100, 500, 400],'Color','w');
  2248. xlims = [-100, 700];
  2249. ylims = [-50, 250];
  2250. xlim(xlims);
  2251. ylim(ylims);
  2252. % patch for NC +-sigma
  2253. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2254. [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)],...
  2255. [0.95 0.95 0.95]);
  2256. % text for mu, sigma
  2257. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2258. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2259. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2260. hold on; box on; grid on;
  2261. % y axis and mu
  2262. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2263. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2264. % SUVopt
  2265. 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),...
  2266. 'LineWidth',2,...
  2267. 'Marker','o');
  2268. % ICI tx patch BLUE
  2269. tx = patch([0 357 357 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2270. tx.FaceAlpha = 0.1;
  2271. tx.EdgeAlpha = 0;
  2272. % irAE diagnosis
  2273. plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2274. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2275. xlabel('Time [days]','FontSize',14);
  2276. title('thyroidG2 ae20');
  2277. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae20.png');
  2278. %% pat ae40
  2279. i=58;
  2280. n_scans = sum(days_thyroid(i,:)~=0);
  2281. figure('pos',[100,100, 500, 400],'Color','w');
  2282. xlims = [-50, 300];
  2283. ylims = [-50, 250];
  2284. xlim(xlims);
  2285. ylim(ylims);
  2286. % patch for NC +-sigma
  2287. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2288. [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)],...
  2289. [0.95 0.95 0.95]);
  2290. % text for mu, sigma
  2291. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2292. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2293. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2294. hold on; box on; grid on;
  2295. % y axis and mu
  2296. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2297. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2298. % SUVopt
  2299. 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),...
  2300. 'LineWidth',2,...
  2301. 'Marker','o');
  2302. % ICI tx patch BLUE
  2303. tx = patch([0 111 111 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2304. tx.FaceAlpha = 0.1;
  2305. tx.EdgeAlpha = 0;
  2306. % irAE diagnosis
  2307. %plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2308. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2309. xlabel('Time [days]','FontSize',14);
  2310. title('thyroidG2 ae40');
  2311. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae40.png');
  2312. %% pat ae41
  2313. i=58;
  2314. n_scans = sum(days_thyroid(i,:)~=0);
  2315. figure('pos',[100,100, 500, 400],'Color','w');
  2316. xlims = [-50, 550];
  2317. ylims = [-50, 250];
  2318. xlim(xlims);
  2319. ylim(ylims);
  2320. % patch for NC +-sigma
  2321. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2322. [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)],...
  2323. [0.95 0.95 0.95]);
  2324. % text for mu, sigma
  2325. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2326. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2327. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2328. hold on; box on; grid on;
  2329. % y axis and mu
  2330. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2331. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2332. % SUVopt
  2333. 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),...
  2334. 'LineWidth',2,...
  2335. 'Marker','o');
  2336. % ICI tx patch BLUE
  2337. tx = patch([0 217 217 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2338. tx.FaceAlpha = 0.1;
  2339. tx.EdgeAlpha = 0;
  2340. % irAE diagnosis
  2341. %plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2342. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2343. xlabel('Time [days]','FontSize',14);
  2344. title('thyroidG2 ae41');
  2345. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae41.png');
  2346. %% Individual patients with thyroid AE - _fixedtime
  2347. % use days_thyroid, patients_thyroid
  2348. %% pat 5345_11
  2349. i=13;
  2350. n_scans = sum(days_thyroid(i,:)~=0);
  2351. figure('pos',[100,100, 500, 400],'Color','w');
  2352. xlims = [-300, 1500];
  2353. ylims = [-50, 250];
  2354. xlim(xlims);
  2355. ylim(ylims);
  2356. % patch for NC +-sigma
  2357. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2358. [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)],...
  2359. [0.95 0.95 0.95]);
  2360. % text for mu, sigma
  2361. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2362. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2363. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2364. hold on; box on; grid on;
  2365. % y axis and mu
  2366. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2367. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2368. % SUVopt
  2369. 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),...
  2370. 'LineWidth',2,...
  2371. 'Marker','o');
  2372. % ICI tx patch BLUE
  2373. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2374. tx.FaceAlpha = 0.1;
  2375. tx.EdgeAlpha = 0;
  2376. % irAE diagnosis
  2377. plot([225 225], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2378. % Imm Supp tx patch GREEN
  2379. tx = patch([108 xlims(2) xlims(2) 108], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2380. tx.FaceAlpha = 0.1;
  2381. tx.EdgeAlpha = 0;
  2382. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2383. xlabel('Time [days]','FontSize',14);
  2384. title('thyroidG2 5345\_11');
  2385. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_5345_11_fixedtime.png');
  2386. %% pat 7339_11
  2387. i=22;
  2388. n_scans = sum(days_thyroid(i,:)~=0);
  2389. figure('pos',[100,100, 500, 400],'Color','w');
  2390. xlims = [-300, 1500];
  2391. ylims = [-50, 250];
  2392. xlim(xlims);
  2393. ylim(ylims);
  2394. % patch for NC +-sigma
  2395. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2396. [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)],...
  2397. [0.95 0.95 0.95]);
  2398. % text for mu, sigma
  2399. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2400. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2401. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2402. hold on; box on; grid on;
  2403. % y axis and mu
  2404. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2405. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2406. % SUVopt
  2407. 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),...
  2408. 'LineWidth',2,...
  2409. 'Marker','o');
  2410. % ICI tx patch BLUE
  2411. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2412. tx.FaceAlpha = 0.1;
  2413. tx.EdgeAlpha = 0;
  2414. % irAE diagnosis
  2415. plot([120 120], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2416. % Imm Supp tx patch GREEN
  2417. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2418. tx.FaceAlpha = 0.1;
  2419. tx.EdgeAlpha = 0;
  2420. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2421. xlabel('Time [days]','FontSize',14);
  2422. title('thyroidG2 7339\_11');
  2423. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7339_11_fixedtime.png');
  2424. %% pat 6756_12
  2425. i=19;
  2426. n_scans = sum(days_thyroid(i,:)~=0);
  2427. figure('pos',[100,100, 500, 400],'Color','w');
  2428. xlims = [-300, 1500];
  2429. ylims = [-50, 250];
  2430. xlim(xlims);
  2431. ylim(ylims);
  2432. % patch for NC +-sigma
  2433. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2434. [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)],...
  2435. [0.95 0.95 0.95]);
  2436. % text for mu, sigma
  2437. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2438. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2439. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2440. hold on; box on; grid on;
  2441. % y axis and mu
  2442. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2443. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2444. % SUVopt
  2445. 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),...
  2446. 'LineWidth',2,...
  2447. 'Marker','o');
  2448. % ICI tx patch BLUE
  2449. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2450. tx.FaceAlpha = 0.1;
  2451. tx.EdgeAlpha = 0;
  2452. % irAE diagnosis
  2453. plot([630 630], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2454. % Imm Supp tx patch GREEN
  2455. tx = patch([675 xlims(2) xlims(2) 675], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2456. tx.FaceAlpha = 0.1;
  2457. tx.EdgeAlpha = 0;
  2458. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2459. xlabel('Time [days]','FontSize',14);
  2460. title('thyroidG2 6756\_12');
  2461. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_6756_12_fixedtime.png');
  2462. %% pat 608_13
  2463. i=17;
  2464. n_scans = sum(days_thyroid(i,:)~=0);
  2465. figure('pos',[100,100, 500, 400],'Color','w');
  2466. xlims = [-300, 1500];
  2467. ylims = [-50, 250];
  2468. xlim(xlims);
  2469. ylim(ylims);
  2470. % patch for NC +-sigma
  2471. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2472. [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)],...
  2473. [0.95 0.95 0.95]);
  2474. % text for mu, sigma
  2475. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2476. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2477. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2478. hold on; box on; grid on;
  2479. % y axis and mu
  2480. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2481. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2482. % SUVopt
  2483. 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),...
  2484. 'LineWidth',2,...
  2485. 'Marker','o');
  2486. % ICI tx patch BLUE
  2487. tx = patch([0 122 122 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2488. tx.FaceAlpha = 0.1;
  2489. tx.EdgeAlpha = 0;
  2490. % irAE diagnosis
  2491. plot([115 115], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2492. % Death
  2493. plot([198 198], [ylims(1), ylims(2)], 'r-','LineWidth',2);
  2494. % Imm Supp tx patch GREEN
  2495. tx = patch([140 198 198 140], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2496. tx.FaceAlpha = 0.1;
  2497. tx.EdgeAlpha = 0;
  2498. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2499. xlabel('Time [days]','FontSize',14);
  2500. title('thyroidG2 608\_13');
  2501. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_608_13_fixedtime.png');
  2502. %% pat 7359_09
  2503. i=23;
  2504. n_scans = sum(days_thyroid(i,:)~=0);
  2505. figure('pos',[100,100, 500, 400],'Color','w');
  2506. xlims = [-300, 1500];
  2507. ylims = [-50, 250];
  2508. xlim(xlims);
  2509. ylim(ylims);
  2510. % patch for NC +-sigma
  2511. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2512. [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)],...
  2513. [0.95 0.95 0.95]);
  2514. % text for mu, sigma
  2515. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2516. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2517. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2518. hold on; box on; grid on;
  2519. % y axis and mu
  2520. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2521. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2522. % SUVopt
  2523. 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),...
  2524. 'LineWidth',2,...
  2525. 'Marker','o');
  2526. % ICI tx patch BLUE
  2527. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2528. tx.FaceAlpha = 0.1;
  2529. tx.EdgeAlpha = 0;
  2530. % irAE diagnosis
  2531. plot([108 108], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2532. % Imm Supp tx patch GREEN
  2533. tx = patch([15 xlims(2) xlims(2) 15], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2534. tx.FaceAlpha = 0.1;
  2535. tx.EdgeAlpha = 0;
  2536. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2537. xlabel('Time [days]','FontSize',14);
  2538. title('thyroidG2 7359\_09');
  2539. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_7359_09_fixedtime.png');
  2540. %% pat 1127_06
  2541. i=2;
  2542. n_scans = sum(days_thyroid(i,:)~=0);
  2543. figure('pos',[100,100, 500, 400],'Color','w');
  2544. xlims = [-300, 1500];
  2545. ylims = [-50, 250];
  2546. xlim(xlims);
  2547. ylim(ylims);
  2548. % patch for NC +-sigma
  2549. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2550. [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)],...
  2551. [0.95 0.95 0.95]);
  2552. % text for mu, sigma
  2553. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2554. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2555. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2556. hold on; box on; grid on;
  2557. % y axis and mu
  2558. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2559. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2560. % SUVopt
  2561. 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),...
  2562. 'LineWidth',2,...
  2563. 'Marker','o');
  2564. % ICI tx patch BLUE
  2565. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2566. tx.FaceAlpha = 0.1;
  2567. tx.EdgeAlpha = 0;
  2568. % irAE diagnosis
  2569. plot([83 83], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2570. % Imm Supp tx patch GREEN
  2571. tx = patch([17 xlims(2) xlims(2) 17], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2572. tx.FaceAlpha = 0.1;
  2573. tx.EdgeAlpha = 0;
  2574. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2575. xlabel('Time [days]','FontSize',14);
  2576. title('thyroidG2 1127\_06');
  2577. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_1127_06_fixedtime.png');
  2578. %% pat ae6
  2579. i=33;
  2580. n_scans = sum(days_thyroid(i,:)~=0);
  2581. figure('pos',[100,100, 500, 400],'Color','w');
  2582. xlims = [-300, 1500];
  2583. ylims = [-50, 250];
  2584. xlim(xlims);
  2585. ylim(ylims);
  2586. % patch for NC +-sigma
  2587. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2588. [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)],...
  2589. [0.95 0.95 0.95]);
  2590. % text for mu, sigma
  2591. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2592. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2593. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2594. hold on; box on; grid on;
  2595. % y axis and mu
  2596. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2597. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2598. % SUVopt
  2599. 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),...
  2600. 'LineWidth',2,...
  2601. 'Marker','o');
  2602. % ICI tx patch BLUE
  2603. tx = patch([0 14 14 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2604. tx.FaceAlpha = 0.1;
  2605. tx.EdgeAlpha = 0;
  2606. tx = patch([98 140 140 98], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2607. tx.FaceAlpha = 0.1;
  2608. tx.EdgeAlpha = 0;
  2609. % irAE diagnosis
  2610. plot([76 76], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2611. % Imm Supp tx patch GREEN
  2612. tx = patch([14 80 80 14], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2613. tx.FaceAlpha = 0.1;
  2614. tx.EdgeAlpha = 0;
  2615. tx = patch([154 xlims(2) xlims(2) 154], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0.9, 0]);
  2616. tx.FaceAlpha = 0.1;
  2617. tx.EdgeAlpha = 0;
  2618. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2619. xlabel('Time [days]','FontSize',14);
  2620. title('thyroidG2 ae6');
  2621. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae6_fixedtime.png');
  2622. %% pat ae15
  2623. i=40;
  2624. n_scans = sum(days_thyroid(i,:)~=0);
  2625. figure('pos',[100,100, 500, 400],'Color','w');
  2626. xlims = [-300, 1500];
  2627. ylims = [-50, 250];
  2628. xlim(xlims);
  2629. ylim(ylims);
  2630. % patch for NC +-sigma
  2631. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2632. [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)],...
  2633. [0.95 0.95 0.95]);
  2634. % text for mu, sigma
  2635. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2636. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2637. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2638. hold on; box on; grid on;
  2639. % y axis and mu
  2640. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2641. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2642. % SUVopt
  2643. 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),...
  2644. 'LineWidth',2,...
  2645. 'Marker','o');
  2646. % ICI tx patch BLUE
  2647. tx = patch([0 xlims(2) xlims(2) 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2648. tx.FaceAlpha = 0.1;
  2649. tx.EdgeAlpha = 0;
  2650. % irAE diagnosis
  2651. plot([27 27], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2652. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2653. xlabel('Time [days]','FontSize',14);
  2654. title('thyroidG2 ae15');
  2655. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae15_fixedtime.png');
  2656. %% pat ae20
  2657. i=45;
  2658. n_scans = sum(days_thyroid(i,:)~=0);
  2659. figure('pos',[100,100, 500, 400],'Color','w');
  2660. xlims = [-300, 1500];
  2661. ylims = [-50, 250];
  2662. xlim(xlims);
  2663. ylim(ylims);
  2664. % patch for NC +-sigma
  2665. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2666. [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)],...
  2667. [0.95 0.95 0.95]);
  2668. % text for mu, sigma
  2669. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2670. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2671. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2672. hold on; box on; grid on;
  2673. % y axis and mu
  2674. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2675. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2676. % SUVopt
  2677. 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),...
  2678. 'LineWidth',2,...
  2679. 'Marker','o');
  2680. % ICI tx patch BLUE
  2681. tx = patch([0 357 357 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2682. tx.FaceAlpha = 0.1;
  2683. tx.EdgeAlpha = 0;
  2684. % irAE diagnosis
  2685. plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2686. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2687. xlabel('Time [days]','FontSize',14);
  2688. title('thyroidG2 ae20');
  2689. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae20_fixedtime.png');
  2690. %% pat ae40
  2691. i=58;
  2692. n_scans = sum(days_thyroid(i,:)~=0);
  2693. figure('pos',[100,100, 500, 400],'Color','w');
  2694. xlims = [-300, 1500];
  2695. ylims = [-50, 250];
  2696. xlim(xlims);
  2697. ylim(ylims);
  2698. % patch for NC +-sigma
  2699. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2700. [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)],...
  2701. [0.95 0.95 0.95]);
  2702. % text for mu, sigma
  2703. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2704. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2705. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2706. hold on; box on; grid on;
  2707. % y axis and mu
  2708. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2709. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2710. % SUVopt
  2711. 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),...
  2712. 'LineWidth',2,...
  2713. 'Marker','o');
  2714. % ICI tx patch BLUE
  2715. tx = patch([0 111 111 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2716. tx.FaceAlpha = 0.1;
  2717. tx.EdgeAlpha = 0;
  2718. % irAE diagnosis
  2719. %plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2720. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2721. xlabel('Time [days]','FontSize',14);
  2722. title('thyroidG2 ae40');
  2723. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae40_fixedtime.png');
  2724. %% pat ae41
  2725. i=58;
  2726. n_scans = sum(days_thyroid(i,:)~=0);
  2727. figure('pos',[100,100, 500, 400],'Color','w');
  2728. xlims = [-300, 1500];
  2729. ylims = [-50, 250];
  2730. xlim(xlims);
  2731. ylim(ylims);
  2732. % patch for NC +-sigma
  2733. patch([xlims(1) xlims(2) xlims(2) xlims(1)], ...
  2734. [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)],...
  2735. [0.95 0.95 0.95]);
  2736. % text for mu, sigma
  2737. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid), '\mu','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2738. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)+sigma_thyroid_NC(ImaxAUC_thyroid), '+1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2739. text(0.98.*xlims(2), mu_thyroid_NC(ImaxAUC_thyroid)-sigma_thyroid_NC(ImaxAUC_thyroid), '-1\sigma','FontSize',12, 'VerticalAlignment','bottom', 'HorizontalAlignment', 'right');
  2740. hold on; box on; grid on;
  2741. % y axis and mu
  2742. plot([xlims(1), xlims(2)], [0, 0], 'k--', 'LineWidth',1);
  2743. plot([xlims(1), xlims(2)], [mu_thyroid_NC(ImaxAUC_thyroid), mu_thyroid_NC(ImaxAUC_thyroid)], 'k-', 'LineWidth',2);
  2744. % SUVopt
  2745. 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),...
  2746. 'LineWidth',2,...
  2747. 'Marker','o');
  2748. % ICI tx patch BLUE
  2749. tx = patch([0 217 217 0], [ylims(1) ylims(1) ylims(2) ylims(2)], [0, 0, 0.9]);
  2750. tx.FaceAlpha = 0.1;
  2751. tx.EdgeAlpha = 0;
  2752. % irAE diagnosis
  2753. %plot([28 28], [ylims(1), ylims(2)], 'r:','LineWidth',2);
  2754. ylabel('change SUV_{OPT%} [%]','FontSize',14);
  2755. xlabel('Time [days]','FontSize',14);
  2756. title('thyroidG2 ae41');
  2757. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroiditis_ae41_fixedtime.png');
  2758. %% Normal N=15 subcohort
  2759. 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'};
  2760. % PATIENT 5706_16 has to be excluded from normals for Lung and Thyroid
  2761. % PATIENT 7093_08 has to be excluded from normals for Thyroid
  2762. nc0_ind_thyroid = [];
  2763. for i=1:numel(patient_ids_norm);
  2764. for j=1:numel(patients_thyroid);
  2765. if strcmp(patient_ids_norm{i}, patients_thyroid{j});
  2766. nc0_ind_thyroid(i) = j;
  2767. end
  2768. end
  2769. end
  2770. nc0_ind_thyroid = nc0_ind_thyroid(nc0_ind_thyroid>0);
  2771. % Compute mean and sd for NC patients for plotting normal range
  2772. d_thyroid_NC0 = d_thyroid(nc0_ind_thyroid,:,:);
  2773. mu_thyroid_NC0 = squeeze(mean(d_thyroid_NC0(:,2,:), 1));
  2774. sigma_thyroid_NC0 = squeeze(std(d_thyroid_NC0(:,2,:), 1));
  2775. figure('pos',[700, 800, 300, 400], 'Color','w');
  2776. boxplot([d_thyroid_MAX(nc0_ind_thyroid,ImaxAUC_thyroid); ...
  2777. d_thyroid_MAX(flags_thyroid(:,6)==0,ImaxAUC_thyroid); ...
  2778. d_thyroid_MAX(flags_thyroid(:,6)==1,ImaxAUC_thyroid)], ...
  2779. [1.*ones(1, numel(d_thyroid_MAX(nc0_ind_thyroid,ImaxAUC_thyroid))), ...
  2780. 2.*ones(1, numel(d_thyroid_MAX(flags_thyroid(:,6)==0,ImaxAUC_thyroid))), ...
  2781. 3.*ones(1, numel(d_thyroid_MAX(flags_thyroid(:,6)==1,ImaxAUC_thyroid)))], ...
  2782. 'Labels',{['NC0 (n=' num2str(numel(nc0_ind_thyroid)) ')'],...
  2783. ['NC (n=' num2str(sum(flags_thyroid(:,6)==0)) ')'],...
  2784. ['AE (n=' num2str(sum(flags_thyroid(:,6)==1)) ')']});
  2785. ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
  2786. grid on;
  2787. lines = findobj(gcf, 'type', 'line');
  2788. set(lines,'LineWidth',1.5);
  2789. hold on;
  2790. plot([0,4], [OPT_OPT_T_thyroid, OPT_OPT_T_thyroid], 'k-');
  2791. ylim([-60, 250]);
  2792. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\thyroid_boxplots3.png');
  2793. % Lung
  2794. nc0_ind = [];
  2795. for i=1:numel(patient_ids_norm);
  2796. for j=1:numel(patients);
  2797. if strcmp(patient_ids_norm{i}, patients{j});
  2798. nc0_ind(i) = j;
  2799. end
  2800. end
  2801. end
  2802. nc0_ind = nc0_ind(nc0_ind>0);
  2803. % Compute mean and sd for NC patients for plotting normal range
  2804. d_lung_NC0 = d_lung(nc0_ind,:,:);
  2805. mu_lung_NC0 = squeeze(mean(d_lung_NC0(:,2,:), 1));
  2806. sigma_lung_NC0 = squeeze(std(d_lung_NC0(:,2,:), 1));
  2807. figure('pos',[700, 800, 300, 400], 'Color','w');
  2808. boxplot([d_lung_MAX(nc0_ind,ImaxAUC_lung); ...
  2809. d_lung_MAX(flags(:,4)==0,ImaxAUC_lung); ...
  2810. d_lung_MAX(flags(:,4)==1,ImaxAUC_lung)], ...
  2811. [1.*ones(1, numel(d_lung_MAX(nc0_ind,ImaxAUC_lung))), ...
  2812. 2.*ones(1, numel(d_lung_MAX(flags(:,4)==0,ImaxAUC_lung))), ...
  2813. 3.*ones(1, numel(d_lung_MAX(flags(:,4)==1,ImaxAUC_lung)))], ...
  2814. 'Labels',{['NC0 (n=' num2str(numel(nc0_ind)) ')'],...
  2815. ['NC (n=' num2str(sum(flags(:,4)==0)) ')'],...
  2816. ['AE (n=' num2str(sum(flags(:,4)==1)) ')']});
  2817. ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
  2818. grid on;
  2819. lines = findobj(gcf, 'type', 'line');
  2820. set(lines,'LineWidth',1.5);
  2821. hold on;
  2822. plot([0,4], [OPT_OPT_T_lung, OPT_OPT_T_lung], 'k-');
  2823. ylim([-60, 250]);
  2824. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\lung_boxplots3.png');
  2825. % Bowel
  2826. % Compute mean and sd for NC patients for plotting normal range
  2827. d_bowel_NC0 = d_bowel(nc0_ind,:,:);
  2828. mu_bowel_NC0 = squeeze(mean(d_bowel_NC0(:,2,:), 1));
  2829. sigma_bowel_NC0 = squeeze(std(d_bowel_NC0(:,2,:), 1));
  2830. figure('pos',[700, 800, 300, 400], 'Color','w');
  2831. boxplot([d_bowel_MAX(nc0_ind,ImaxAUC_bowel); ...
  2832. d_bowel_MAX(flags(:,2)==0,ImaxAUC_bowel); ...
  2833. d_bowel_MAX(flags(:,2)==1,ImaxAUC_bowel)], ...
  2834. [1.*ones(1, numel(d_bowel_MAX(nc0_ind,ImaxAUC_bowel))), ...
  2835. 2.*ones(1, numel(d_bowel_MAX(flags(:,2)==0,ImaxAUC_bowel))), ...
  2836. 3.*ones(1, numel(d_bowel_MAX(flags(:,2)==1,ImaxAUC_bowel)))], ...
  2837. 'Labels',{['NC0 (n=' num2str(numel(nc0_ind)) ')'],...
  2838. ['NC (n=' num2str(sum(flags(:,2)==0)) ')'],...
  2839. ['AE (n=' num2str(sum(flags(:,2)==1)) ')']});
  2840. ylabel('MAX(\Delta SUV_{OPT%})','FontSize',14);
  2841. grid on;
  2842. lines = findobj(gcf, 'type', 'line');
  2843. set(lines,'LineWidth',1.5);
  2844. hold on;
  2845. plot([0,4], [OPT_OPT_T_bowel, OPT_OPT_T_bowel], 'k-');
  2846. ylim([-60, 400]);
  2847. export_fig('C:\Users\strah\OneDrive\Namizje\Melanoma\Daniel\bowel_boxplots3.png');