{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Li H"],"funding":["the Key Research Project of Sichuan Province"],"pagination":["57"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10899552"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["<h4>Objective</h4>To investigate whether T2-weighted imaging (T2WI)-based intratumoral and peritumoral radiomics can predict extranodal extension (ENE) and prognosis in patients with resectable rectal cancer.<h4>Methods</h4>One hundred sixty-seven patients with resectable rectal cancer including T3T4N + cases were prospectively included. Radiomics features were extracted from intratumoral, peritumoral 3 mm, and peritumoral-mesorectal fat on T2WI images. Least absolute shrinkage and selection operator regression were used for feature selection. A radiomics signature score (Radscore) was built with logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each Radscore. A clinical-radiomics nomogram was constructed "],"journal":["Insights into imaging"],"pubmed_title":["T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer."],"pmcid":["PMC10899552"],"funding_grant_id":["2022YFS0249"],"pubmed_authors":["Li H","Chai L","Zhang X","Pang MH","Lu T","Pu H","Yin LL","Li M","Liu YS"],"additional_accession":[]},"is_claimable":false,"name":"T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer.","description":"<h4>Objective</h4>To investigate whether T2-weighted imaging (T2WI)-based intratumoral and peritumoral radiomics can predict extranodal extension (ENE) and prognosis in patients with resectable rectal cancer.<h4>Methods</h4>One hundred sixty-seven patients with resectable rectal cancer including T3T4N + cases were prospectively included. Radiomics features were extracted from intratumoral, peritumoral 3 mm, and peritumoral-mesorectal fat on T2WI images. Least absolute shrinkage and selection operator regression were used for feature selection. A radiomics signature score (Radscore) was built with logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each Radscore. A clinical-radiomics nomogram was constructed ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Feb","modification":"2026-07-15T02:06:02.422Z","creation":"2025-04-07T01:03:52.674Z"},"accession":"S-EPMC10899552","cross_references":{"pubmed":["38411722"],"doi":["10.1186/s13244-024-01625-8"]}}