AI Article Synopsis

  • Glioblastoma is a common and aggressive brain tumor, but many existing public datasets are limited by factors like small sample sizes and inconsistent data quality.
  • The UPenn-GBM dataset addresses these issues by providing a comprehensive collection of data from 630 patients, including advanced MRI scans and detailed clinical information.
  • This dataset aims to facilitate better research in glioblastoma by enabling more accurate predictive and diagnostic studies through its high-quality imaging and annotations.

Article Abstract

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of: a) number of subjects, b) lack of consistent acquisition protocol, c) data quality, or d) accompanying clinical, demographic, and molecular information. Toward alleviating these limitations, we contribute the "University of Pennsylvania Glioblastoma Imaging, Genomics, and Radiomics" (UPenn-GBM) dataset, which describes the currently largest publicly available comprehensive collection of 630 patients diagnosed with de novo glioblastoma. The UPenn-GBM dataset includes (a) advanced multi-parametric magnetic resonance imaging scans acquired during routine clinical practice, at the University of Pennsylvania Health System, (b) accompanying clinical, demographic, and molecular information, (d) perfusion and diffusion derivative volumes, (e) computationally-derived and manually-revised expert annotations of tumor sub-regions, as well as (f) quantitative imaging (also known as radiomic) features corresponding to each of these regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338035PMC
http://dx.doi.org/10.1038/s41597-022-01560-7DOI Listing

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