biostudies-literatureJayaprakasam VSNational Cancer InstituteNCI NIH HHS971-980https://www.ebi.ac.uk/biostudies/studies/S-EPMC9018044biostudies-literatureUnknown32(2)<h4>Objective</h4>To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer.<h4>Methods</h4>This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A mEuropean radiologyMRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer.PMC9018044P30 CA008748Bates DDBWeiser MRFuqua JLBajwa RParoder VGollub MJJayaprakasam VSCercek AGangai NPetkovska ISosa REGibbs PGolia Pernicka JSfalseMRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer.<h4>Objective</h4>To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer.<h4>Methods</h4>This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A m2022-01-01T00:00:00Z2022 Feb2025-04-19T17:57:11.567Z2025-04-19T17:57:11.567ZS-EPMC90180443432758010.1007/s00330-021-08144-w