Esra ÇİFTÇİ
Annals of Clinical and Analytical Medicine - 2026;17(8):834-841
Aim: This study aimed to evaluate the prognostic value of tumor asphericity and radiomic features derived from 18F-FDG PET/CT in patients with colorectal cancer, and to assess their role in risk stratification for progression-free survival (PFS). Methods: A retrospective analysis of 102 patients with diagnosed colorectal cancer who underwent pre-treatment 18F-FDG PET/CT imaging. Clinical variables, conventional PET parameters (SUVmax, MTV, and TLG), and radiomic features, including tumor asphericity (ASP), GLCM (gray-level co-occurrence matrix) entropy, and GLSZM (gray-level size zone matrix) and GLRLM (gray-level run length matrix) parameters, were extracted. Progression-free survival (PFS) was the primary endpoint, and overall survival (OS) was the secondary endpoint. Univariate and multivariate Cox regression analyses, ROC curve analysis, and Kaplan-Meier curves were performed. Results: During a median follow-up of 26.5 months, 59 patients (57.8%) had disease progression and 50 (49%) died. Progression correlated with higher ASP ( P = .024), GLCM entropy ( P < .001), GLSZM-SZE ( P = .001), and lower GLSZM-LZE ( P = .030). Univariate Cox analysis showed that ASP, GLCM entropy, GLSZM-SZE, GLSZM-LZE, and TNM stage were associated with PFS and OS. Multivariate analysis identified ASP (HR = 5.6, P = .021), GLCM entropy (HR = 1.55, P = .006), and TNM stage (all P < .001) as independent predictors. Patients with ASP values above the ROC-derived cutoff of 0.36 and GLCM entropy values above 9.65 had significantly shorter PFS (9.2 vs. 37.4 months and 21.6 vs. 52.3 months, respectively). Conclusions: Tumor asphericity and GLCM-derived entropy from pretreatment 18F-FDG PET/CT provide independent and complementary prognostic information beyond conventional metabolic parameters in colorectal cancer. These biomarkers may improve risk stratification and help identify patients at increased risk of disease progression and mortality.
