Journal Article

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

Davatzikos, Christos, Akbari, Hamed, Bilello, Michel, Sotiras, Aristeidis, Farahani, Keyvan, Bakas, Spyridon, Rozycki, Martin, Freymann, John B., Kirby, Justin S.

2017

نظرة عامة

Gliomas belong to a group of central nervous system tumors, and consist of various sub-regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for both clinical and computational studies, including radiomic and radiogenomic analyses. Towards this end, we release segmentation labels and radiomic features for all pre-operative multimodal magnetic resonance imaging (MRI) ( n =243) of the multi-institutional glioma collections of The Cancer Genome Atlas (TCGA), publicly available in The Cancer Imaging Archive (TCIA). Pre-operative scans were identified in both glioblastoma (TCGA-GBM, n =135) and low-grade-glioma (TCGA-LGG, n =108) collections via radiological assessment. The glioma sub-region labels were produced by an automated state-of-the-art method and manually revised by an expert board-certified neuroradiologist. An extensive panel of radiomic features was extracted based on the manually-revised labels. This set of labels and features should enable i) direct utilization of the TCGA/TCIA glioma collections towards repeatable, reproducible and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments, as well as ii) performance evaluation of computer-aided segmentation methods, and comparison to our state-of-the-art method. Design Type(s) parallel group design • data integration objective Measurement Type(s) nuclear magnetic resonance assay Technology Type(s) MRI Scanner Factor Type(s) diagnosis Sample Characteristic(s) Homo sapiens • glioma cell Machine-accessible metadata file describing the reported data (ISA-Tab format)

• الناشر: Nature Publishing Group UK,Nature Publishing Group
• موضوع: 631/114/1564 / 631/114/2397 / 631/67/2321 / 692/308/575 / 692/699/67/1922 / Brain Neoplasms - diagnostic imaging / Brain Neoplasms - genetics / Brain tumors / Cancer / Central nervous system / Data Descriptor / DNA, Neoplasm / Genomes / Glioblastoma / Glioma / Glioma - diagnostic imaging / Glioma - genetics / Humanities and Social Sciences / Humans / Image Interpretation, Computer-Assisted / Image processing / Magnetic Resonance Imaging / multidisciplinary / Multimodal Imaging / NMR / Nuclear magnetic resonance / Radiomics / Science / Segmentation