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Thesen, T; DuBois, J M; Quinn, B T; Carlson, C; Halgren, E; Wang, H; Neilman, V; French, J; Devinsky, O; Kuzniecky, R
"Automatic detection of "MRI-negative" epileptogenic cortical malformations with surface-based MRI morphometry" [Meeting Abstract]
Epilepsy currents 2011 2011; 11(1):-
Rationale: Magnetic resonance imaging has revolutionized the detection of small structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine visual inspection. Here we used morphometric MRI to quantify imaging features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries that went undetected by routine clinical visual inspection. Methods: 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 and gray-white matter contrast (GWC). 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 establish the effectiveness of the technique, we compared the detected structural abnormalities to resection margins, seizure onset zones based on intracranial EEG and pathological features using post-resection histology. Results: We report optimal parameters by which cortical thickness and GWC features detected previously occult lesions. We present sensitivity and specificity measures for each threshold and smoothing level to allow for selection of parameters based on clinical need. Conclusions: This automated approach may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore may improve identification of patients with intractable focal epilepsy who may benefit from surgery

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