biostudies-literatureGuo TGuangzhou Science and Technology Plan ProjectNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China1226https://www.ebi.ac.uk/biostudies/studies/S-EPMC11453003biostudies-literatureUnknown24(1)<h4>Background</h4>Colon cancer, a frequently encountered malignancy, exhibits a comparatively poor survival prognosis. Perineural invasion (PNI), highly correlated with tumor progression and metastasis, is a substantial effective predictor of stage II-III colon cancer. Nonetheless, the lack of effective and facile predictive methodologies for detecting PNI prior operation in colon cancer remains a persistent challenge.<h4>Method</h4>Pre-operative computer tomography (CT) images and clinical data of patients diagnosed with stage II-III colon cancer between January 2015 and December 2023 were obtained from two sub-districts of Sun Yat-sen Memorial Hospital (SYSUMH). The LASSO/RF/PCA filters were used to screen radiomics features and LR/SVM models were utilized to construct radiomics model. BMC cancerA radiomics model for predicting perineural invasion in stage II-III colon cancer based on computer tomography.PMC11453003822030362024A1515012799SL2024A04J01991Li YLi JLian GGao MHuang YCheng BGuo THuang KChen SfalseA radiomics model for predicting perineural invasion in stage II-III colon cancer based on computer tomography.<h4>Background</h4>Colon cancer, a frequently encountered malignancy, exhibits a comparatively poor survival prognosis. Perineural invasion (PNI), highly correlated with tumor progression and metastasis, is a substantial effective predictor of stage II-III colon cancer. Nonetheless, the lack of effective and facile predictive methodologies for detecting PNI prior operation in colon cancer remains a persistent challenge.<h4>Method</h4>Pre-operative computer tomography (CT) images and clinical data of patients diagnosed with stage II-III colon cancer between January 2015 and December 2023 were obtained from two sub-districts of Sun Yat-sen Memorial Hospital (SYSUMH). The LASSO/RF/PCA filters were used to screen radiomics features and LR/SVM models were utilized to construct radiomics model. 2024-01-01T00:00:00Z2024 Oct2025-04-04T02:36:25.716Z2025-04-04T02:36:25.716ZS-EPMC114530033936732110.1186/s12885-024-12951-x