Eur J Radiol. 2026 Jun 28;203:113038. doi: 10.1016/j.ejrad.2026.113038. Online ahead of print.
ABSTRACT
Here, we establish a co-clinical computed tomography (CT) radiomics pipeline for the identification of candidate imaging biomarkers in RAS-mutant metastatic colorectal cancer (mCRC). Orthotopic KRAS-mutant xenograft models (LOVO-Luc2 (N = 52) and SW480-Luc2 (N = 52)) were treated with standard-of-care regimens (FOLFOX, bevacizumab, or combination) and longitudinally imaged by CT (N = 104 tumour scans, N = 156 liver scans collected over 4 timepoints). Radiomic features derived from primary tumour and liver parenchyma were assessed as biomarkers of treatment sensitivity and early metastatic disease. Pre-treatment CT-radiomics identified baseline radiomic correlates of treatment sensitivity in the LOVO-Luc2 model (0.716), with first-order statistical features (Median, 10percentile) significantly associated with therapy outcome. Texture-based liver radiomic features enabled prediction of metastases earlier than visual CT assessment (AUROC = 0.871). The most predictive features, GLSZM Gray Level Non-Uniformity, GLRLM Run Length Non-Uniformity Normalized, and GLDM Small Dependence Emphasis, were significantly associated with metastatic burden and survival in a clinical CRC cohort (N = 41), indicating species conservation and translational relevance. Collectively, these data demonstrate that preclinical CT radiomics can identify quantitative imaging features associated with treatment sensitivity and early metastatic progression, supporting translational potential.
PMID:42385277 | DOI:10.1016/j.ejrad.2026.113038
