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Diagnosing Growth In Low-Grade Gliomas With And Without Longitudinal Volume Measurements: A Retrospective Observational Study., Hassan M Fathallah-Shaykh, Andrew Deatkine, Elizabeth Coffee, Elias Khayat, Asim K Bag, Xiaosi Han, Paula Province Warren, Markus Bredel, John Fiveash, James Markert, Nidhal Carla Bouaynaya, Louis B Nabors
Diagnosing Growth In Low-Grade Gliomas With And Without Longitudinal Volume Measurements: A Retrospective Observational Study., Hassan M Fathallah-Shaykh, Andrew Deatkine, Elizabeth Coffee, Elias Khayat, Asim K Bag, Xiaosi Han, Paula Province Warren, Markus Bredel, John Fiveash, James Markert, Nidhal Carla Bouaynaya, Louis B Nabors
Henry M. Rowan College of Engineering Departmental Research
BACKGROUND: Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas.
METHODS AND FINDINGS: We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during …