A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas

ABSTRACT: Glioblastoma is the most common malignant brain parenchymal tumor yet remains challenging to treat. The current standard of care—resection and chemoradiation—is limited in part due to the genetic heterogeneity of glioblastoma. Previous studies have identified several tumor genetic biomarkers that are frequently present in glioblastoma and can alter clinical management. Currently, genetic biomarker status is confirmed with tissue sampling, which is costly and only available after tumor resection or biopsy. The purpose of this study was to evaluate a fully automated artificial intelligence approach for predicting the status of several common glioblastoma genetic biomarkers on preoperative MRI. We retrospectively analyzed multisequence preoperative brain MRI from 199 adult patients with gliob

SUBMITTER: Calabrese E 

PROVIDER: S-EPMC7366666 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature