Fig. 3: High-autocorrelation omental implants are associated with shorter OS.
a, Segmented omental lesion (red) on CE-CT. b, The log HR is depicted for each radiomic feature derived from omental implants (n = 600 features). Features above the line were statistically significant by Cox regression after multiple testing correction of interquartile range-filtered features. c, Adnexal radiomic features (n = 600 features) were not significant by Cox regression after correction of interquartile range-filtered features. d, The hazard ratio with 95% CI as estimated by Cox regression is shown for the feature in the final model, the autocorrelation derived from the gray level co-occurrence matrix for the wavelet-filtered image. e, The value of this feature against OS is plotted for patients in the training set (n = 251 patients). f, Training and test concordance indices for the model are shown; the height of each bar shows the c-Index and the lower and upper points of the respective error bars depict the 95% CI by 100-fold leave-one-out bootstrapping. g,h, Two risk groups based on the model’s predicted risk score are shown for the training and test sets. P values were derived using the log-rank test. glcm, gray level co-occurrence matrix; gldm, gray level dependence matrix; glrlm, gray level run length matrix; glszm, gray level size zone matrix; ngtdm, neighboring gray tone difference matrix.
