title: Detection of epileptogenic cortical malformations with surface-based MRI morphometry.
abstract: Magnetic resonance imaging has revolutionized the detection of structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine visual inspection. Here we use an automated, surface-based method for quantifying morphometric features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries. Using MRI morphometry at 3T with surface-based spherical averaging techniques that precisely align anatomical structures between individual brains, we compared single patients with known lesions to a large normal control group to detect clusters of abnormal cortical thickness, gray-white matter contrast, local gyrification, sulcal depth, jacobian distance and curvature. To assess the effects of threshold and smoothing on detection sensitivity and specificity, we systematically varied these parameters with different thresholds and smoothing levels. To test the effectiveness of the technique to detect lesions of epileptogenic character, we compared the detected structural abnormalities to expert-tracings, intracranial EEG, pathology and surgical outcome in a homogeneous patient sample. With optimal parameters and by combining thickness and GWC, the surface-based detection method identified 92% of cortical lesions (sensitivity) with few false positives (96% specificity), successfully discriminating patients from controls 94% of the time. The detected structural abnormalities were related to the seizure onset zones, abnormal histology and positive outcome in all surgical patients. However, the method failed to adequately describe lesion extent in most cases. Automated surface-based MRI morphometry, if used with optimized parameters, may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore could improve identification of patients with intractable focal epilepsy who may benefit from surgery.
authors.affiliation: Comprehensive Epilepsy Center, Department of Neurology, New York University, New York, New York, United States of America. thomas.thesen@med.nyu.edu
authors.forename: Thomas
authors.initials: T
authors.lastname: Thesen
authors.forename: Brian T
authors.initials: BT
authors.lastname: Quinn
authors.forename: Chad
authors.initials: C
authors.lastname: Carlson
authors.forename: Orrin
authors.initials: O
authors.lastname: Devinsky
authors.forename: Jonathan
authors.initials: J
authors.lastname: DuBois
authors.forename: Carrie R
authors.initials: CR
authors.lastname: McDonald
authors.forename: Jacqueline
authors.initials: J
authors.lastname: French
authors.forename: Richard
authors.initials: R
authors.lastname: Leventer
authors.forename: Olga
authors.initials: O
authors.lastname: Felsovalyi
authors.forename: Xiuyuan
authors.initials: X
authors.lastname: Wang
authors.forename: Eric
authors.initials: E
authors.lastname: Halgren
authors.forename: Ruben
authors.initials: R
authors.lastname: Kuzniecky
mesh_terms: D000328:Adult; D001931:Brain Mapping / Q000379:methods; D002540:Cerebral Cortex / Q000002:abnormalities* / Q000000981:diagnostic imaging* / Q000473:pathology; D002648:Child; D004569:Electroencephalography; D004827:Epilepsy / Q000151:congenital / Q000000981:diagnostic imaging* / Q000209:etiology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009421:Nervous System Malformations / Q000150:complications / Q000000981:diagnostic imaging* / Q000473:pathology; D011859:Radiography; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D055815:Young Adult