qra/Instruction_Manual.txt

MATLAB:

irAE_plotting  - is the main file for plotting and analysis of SUV data

flags_combined.mat - matlab matrics that has :
        days - a matrix with lines (patients) and columns (consecutive patient image), values are days from treatment start to image 
        flags - first column (baseline_index); then in pairs: bowel, thyroid, lungs
                1st column in pair - 0-->no irAE, 1--> clinical diagnosis of irAE was made;
                2nd column in pair - days from treatment start that clinical diagnosis was made (0 if no diagnosis was made)
                
normal_range.mat - is a matriy that contains values of 95%CI; lines - organs (bowel, lungs, thyroid); 1st column is min value of 95%CI, 2nd column max value of 95%CI

suv_percentilesSLOthenUWM -  has three separate 3D tables - one for each organ; lines (patients), columns (consecutive patient image), 3rd dimension is the SUV% that was extracted. So (1,1,20) is value for 1st patient, 1st image, 20th percentile. The values are the SUV% extracted from organ segmentations made with DeepMedic

PYTHON:

GEN_CSV_anon - script that ganerates csv (needed input for SUV extraction); 

cases_retroMManon.csv - csv file (excel) that has inputs for SUV extraction; each line is one input (for patient and visit one input) - it has path to PET and path to Segmentation

extract_SUV_from_mask - script that has csv file as input (path to PET and segmentaation) and extracts SUV percentiles that are then saved in excel file (could be done also without csv with just path)