{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Guo T"],"funding":["Guangzhou Science and Technology Plan Project","Natural Science Foundation of Guangdong Province","National Natural Science Foundation of China"],"pagination":["1226"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11453003"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["24(1)"],"pubmed_abstract":["<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. "],"journal":["BMC cancer"],"pubmed_title":["A radiomics model for predicting perineural invasion in stage II-III colon cancer based on computer tomography."],"pmcid":["PMC11453003"],"funding_grant_id":["82203036","2024A1515012799","SL2024A04J01991"],"pubmed_authors":["Li Y","Li J","Lian G","Gao M","Huang Y","Cheng B","Guo T","Huang K","Chen S"],"additional_accession":[]},"is_claimable":false,"name":"A radiomics model for predicting perineural invasion in stage II-III colon cancer based on computer tomography.","description":"<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. ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2025-04-04T02:36:25.716Z","creation":"2025-04-04T02:36:25.716Z"},"accession":"S-EPMC11453003","cross_references":{"pubmed":["39367321"],"doi":["10.1186/s12885-024-12951-x"]}}