MUSC inventors have developed an automated, computer-based solution to aid the clinician in analyzing MRI images to detect hippocampal atrophy (HA) that is commonly seen in patients with medial temporal lobe epilepsy (MTLE). Manual morphometry is sensitive to detecting HA, but time-consuming and subject to human error. Automated MRI morphometry can provide rapid, unbiased, and quantitative results via Z-scores to allow for accurate assistance in proper detection of HA and other brain abnormalities. This technology can be utilized to map the locations of the brain in which tissue is abnormally small or large when compared to a normal population. The utilization of Z-scores allows for quantification of the area to assist in clinical diagnosis of abnormal areas of brain tissue.
Magnetic Resonance Imaging (MRI) is one of several imaging techniques used by clinicians to help diagnose a variety of brain disorders. Typically, the image generated by these techniques is examined visually by a trained physician and, if necessary, processed digitally to emphasize or enhance areas of interest. However, relying on visual diagnoses for brain disorders involving small or large brain areas can miss differences between the patient and the normal population, which can result in misdiagnoses and incorrect treatments.
Allows for objective and automated detection of brain abnormalities
Key Words: Magnetic resonance imaging, MRI, brain abnormalities, Parkinson’s, Alzheimer’s dementia, epilepsy
Publications: Bonilha, Leonardo, et al. "Automated MRI analysis for identification of hippocampal atrophy in temporal lobe epilepsy." Epilepsia 50.2 (2009): 228-233.
Authors: L. Bonilha, J. Edwards
MUSC-FRD Technology ID: P0944