The prognostic value of 18F-FDG PET texture analysis and metabolic parameters in colorectal cancer

Aim: This study aims to investigate the prognostic value of texture features and metabolic parameters derived from 18F-FDG PET images in patients diagnosed with colorectal cancer (CRC). Materials and Methods: 18F-FDG PET/CT and PET/MR images of CRC patients who underwent primary staging between January 2017 and December 2023 were retrospectively analyzed. Using LIFEx software, metabolic parameters (maximum standardized uptake value [SUVmax], metabolic tumor volume [MTV], and total lesion glycolysis [TLG]) and texture features were identified through segmentation of the primary tumor. The relationships between metabolic parameters and texture features were analyzed using Spearman's correlation test. The association of these parameters and clinical features with overall survival were evaluated using Kaplan-Meier survival curves and multivariate Cox regression analysis. Results: The study included 109 patients diagnosed with CRC, with a mean age of 62.01±12.8 years (48 females [44%] and 61 males [56%]). The mean overall survival time was 51.16±3.47 months. Statistically significant correlations were observed between metabolic parameters and certain texture features (p<0.01). According to univariate analysis and Kaplan-Meier overall survival curves, tumor size, TNM stage, the presence of distant metastasis, MTV, TLG, and six texture features (surface, GLCM_Correlation, GLRLM_GLNU, GLSZM_GLNU, GLSZM_ZSE and NGTDM_Strength) were associated with overall survival. In the multivariate Cox regression analysis, the presence of distant metastasis was identified as the only independent prognostic factor associated with shorter overall survival (p<0.05). Conclusion: This study demonstrated that volume-based metabolic parameters and certain texture features derived from 18F-FDG PET imaging have significant potential in predicting prognosis in CRC. Keywords: 18F-FDG PET, Colorectal Cancer, Metabolic Parameters, Texture Features