# Radiomic features of CECT and SUVmax of dual-tracer PET/CT reveal PD-L1 spatial heterogeneity in PDAC

## TL;DR

This study uses imaging techniques to predict PD-L1 expression in pancreatic cancer, offering a non-invasive alternative to biopsies.

## Contribution

The study introduces multi-parametric imaging biomarkers to capture PD-L1 spatial heterogeneity in pancreatic cancer.

## Key findings

- Multimodal intensity histograms from CECT correlate with PD-L1 expression in PDAC tissues.
- FDG PET/CT SUVmax shows moderate correlation with PD-L1 expression (R2 = 0.36).
- Radiomic features from CECT can enhance immunohistochemistry for patient stratification.

## Abstract

Pancreatic ductal adenocarcinoma (PDAC) is characterized by limited responsiveness to immunotherapy due to spatial heterogeneity of PD-L1 expression. Invasive biopsy-based assessments may fail to capture this heterogeneity. This study aims to evaluate non-invasive imaging biomarkers to predict the expression of PD-L1 in 52 PDAC patients using CECT and F-18 FDG PET/CT and Ga-68 FAPI-04 PET/CT imaging. Intensity histogram and Gray Level Co-occurrence Matrix (GLCM) features were extracted from CECT using IBEX software. PD-L1 expression was validated by immunohistochemistry, RT-PCR, and Western blotting. Correlation between PD-L1 expression, SUVmax of F-18 FDG, and FAPI-04 PET/CT and radiomic CECT features were assessed. PDAC tissues demonstrated multimodal intensity histograms with lower histogram peak height correlated with high PD-L1 expression. A moderate positive correlation was observed between PD-L1 expression and FDG uptake (R2 = 0.36) and a weaker correlation with FAPI uptake (R2 = 0.19). This Multi-parametric imaging can enhance immunohistochemistry, aiding in patient stratification for immunotherapy and overcoming the limitations of single-site biopsies.

The online version contains supplementary material available at 10.1186/s40644-025-00960-3.