Integrating radiomics, pathomics, and biopsy-adapted immunoscore for predicting distant metastasis in locally...

This study aimed to develop and validate a nomogram that utilized macro- and microscopic tumor characteristics at baseline, including radiomics, pathomics, and biopsy-adapted immunoscore (IS_B), to accurately predict distant metastasis (DM) in patients with locally advanced rectal cancer (LARC) who underwent neoadjuvant chemoradiotherapy (nCRT).

In total, 201 patients with LARC (91 months of median follow-up) were enrolled. Radiomics features were extracted from apparent diffusion coefficient maps and T2-weighted images. Pathomics features including global pattern (features of the entire image) and local pattern (features of the tumor nuclei) were extracted from whole-slide images of hematoxylin-eosin-stained biopsy specimens. IS_B was calculated from the densities of CD3+ and CD8+ T cells in the tumor region using immunohistochemistry on biopsy specimens. The construction of a predictive model was carried out using the least absolute shrinkage and selection operator-Cox analysis, with performance metrics including the area under the curve (AUC) and concordance index (C-index) utilized for evaluation.

Compared with patients with moderate and high IS_B, patients with low IS_B exhibited significantly higher risk scores for radiomics and pathomics signatures. The nomogram showed respective C-indexes of 0.902 and 0.848 for 5-year DM-free survival in the training and test sets, along with corresponding AUC values of 0.950 and 0.872. Patients could be efficiently categorized into low- and high-risk groups for developing DM using the nomogram.

The nomogram integrating macroscopic radiological information and microscopic pathological information is effective for risk stratification at baseline in LARC treated with nCRT.