Predictive value of CT-based imaging model for BRAF gene mutation in patients with colorectal cancer: a retrospective...

In colorectal cancer, the BRAF gene mutations are associated with adverse clinical outcomes and therapeutic resistance. Radiomics, a quantitative imaging analysis approach, enables high-throughput extraction of tumor features from computed tomography (CT) scans to develop predictive models. This study aimed to explore the predictive value of CT imaging model for BRAF gene mutation in patients with colorectal cancer and provide a reference for clinical practice.

Patients with colorectal cancer treated in National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital from May 2022 to December 2023 were divided into mutation group and non-mutation group according to the occurrence of BRAF gene mutation. Univariate analysis of the influencing factors of BRAF gene mutation and multivariate logistics regression analysis of the influencing factors of BRAF gene mutation were used to construct a CT-based radiomics nomogram. Receiver operating characteristic (ROC) curve analysis of the predictive value of CT-based imaging model for BRAF gene mutation in patients with colorectal cancer was conducted.

In total, 100 patients were selected. Univariate analysis and multivariate logistics regression analysis showed that lymph node metastasis, tumor differentiation, tumor invasion depth and tumor size were independent influencing factors of BRAF gene mutation. Based on the influencing factors, the CT-based radiomics nomogram was constructed. The ROC analysis results showed that the area under the curve (AUC) of training and verification set of the CT-based radiomics model for predicting BRAF gene mutations in patients with colorectal cancer was 0.826 and 0.670.

In this study, the CT-based radiomics nomogram was constructed and its value was analyzed. The imaging model of CT is of high value in predicting BRAF gene mutation in patients with colorectal cancer.