{"id":5759,"date":"2023-09-04T03:36:15","date_gmt":"2023-09-04T03:36:15","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/tcga-lgg-mask\/"},"modified":"2023-09-13T12:09:10","modified_gmt":"2023-09-13T12:09:10","slug":"tcga-lgg-mask","status":"publish","type":"tcia_analysis_result","link":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/tcga-lgg-mask\/","title":{"rendered":"TCGA-LGG-MASK"},"featured_media":0,"template":"","cancer_types":["Low Grade Glioma"],"citations":[4763,4764,2925],"full_export":"

Summary<\/span><\/h2>

This collection contains 406 ROI masks in MATLAB format defining the low grade glioma (LGG) tumour region on T1-weighted (T1W), T2-weighted (T2W), T1-weighted post-contrast (T1CE) and T2-flair (T2F) MR images of 108 different patients from the TCGA-LGG<\/a> collection. From this subset of 108 patients, 81 patients have ROI masks drawn for the four MRI sequences (T1W, T2W, T1CE and T2F), and 27 patients have ROI masks drawn for three or less of the four MRI sequences. The ROI masks were used to extract texture features in order to develop radiomic-based multivariable models for the prediction of isocitrate dehydrogenase 1 (IDH1) mutation, 1p\/19q codeletion status, histological grade and tumour progression.\u00a0<\/p>

Clinical data (188 patients in total from the TCGA-LGG collection, some incomplete depending on the clinical attribute), VASARI scores (188 patients in total from the TCGA-LGG collection, 178 complete) with feature keys, and source code<\/a> used in this study are also available with this collection. Please contact Martin Valli\u00e8res (mart.vallieres@gmail.com<\/a>) of the Medical Physics Unit of McGill University for any scientific inquiries about this dataset.<\/p>