Value of pre-treatment (18)F-FDG PET/CT radiomics in predicting the prognosis of stage III-IV colorectal cancer

BACKGROUND AND PURPOSE: To investigate the value of radiomics features extracted from pre-treatment (18)F-FDG PET/CT in predicting the outcomes of stage III-IV colorectal cancer (CRC), which may assist in clinical management strategies and precise treatment of stage III-IV CRC. MATERIALS AND METHODS: 124 patients with pathologically confirmed stage III-IV CRC who underwent pre-treatment (18)F-FDG PET/CT scans were enrolled in this study. The least absolute shrinkage and selection operator Cox regression (LASSO-Cox) was used to select radiomics features, and the radiomics scores (Rad-scores) were calculated to build radiomics models. The performance of radiomics models was represented by the concordance index (C-index) and compared with clinical models and complex model. The bootstrap resampling method was used to create validation sets. Additionally, nomograms were developed based on complex models. RESULTS: The C-indices of the radiomics model for predicting PFS and OS were 0.712 (95%CI: 0.680–0.744) and 0.758 (0.728–0.789), respectively. In the clinical model, these values were 0.690 (0.664–0.0.717) and 0.738 (0.709–0.767), respectively. However, in the complex model were 0.734 (0.705–0.762) and 0.780 (0.754–0.807), respectively. The Kaplan–Meier curves demonstrated that the radiomics model could effectively separate patients with stage III-IV stage CRC into high- and low-risk groups (p < 0.001). Multivariate Cox regression analysis confirmed the independent prognostic value of Rad-scores. CONCLUSION: Pre-treatment (18)F-FDG PET/CT radiomics features can stratify the risk of patients with stage III-IV CRC and accurately predict their outcomes. These findings could be clinically valuable for precision treatment and management decisions in stage III-IV CRC.