Skip to main content
. 2023 Jun 21;4(7):101092. doi: 10.1016/j.xcrm.2023.101092

Figure 6.

Figure 6

Radiomics signature predicts tertiary lymphoid structure

(A) Workflow of radiomics analysis. Tumors in standard-of-care CT images are segmented by an experienced radiologist. The segmented images are normalized and used as input for TexLab 2.0. Radiomics profiles are then used to build the predictive model.

(B) The coefficients of radiomics features (y axis) and number of features included in each model (upper x axis) are plotted against shrinkage parameter (lambda).

(C) Mean-squared error of each model after 10-fold cross-validation is plotted against lambda in log ratio.

(D) Correlation between radiomic TLS score and B cells in the TCGA cohort. Pearson’s correlation coefficient and p value are given.

(E) Kaplan-Meier plot of radiomic TLS score associated with progression-free survival in the HH cohort. The p-value is given by log rank test.

(F) Summary of patient response to immunotherapy in the HH NSCLC cohort.

(G) Kaplan-Meier plot of radiomic TLS score associated with progression-free survival in response to immunotherapy in the HH NSCLC cohort. The p-value is given by log rank test.