Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias

NeuroImage
Yee-Leng TanRobert Knowlton

Abstract

Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identification/localization; nevertheless, many FCDs are small or subtle, and difficult to find on routine radiological inspection. We aimed to automatically detect subtle or visually-unidentifiable FCDs by building a classifier based on an optimized cortical surface sampling of combined MRI and PET features. Cortical surfaces of 28 patients with histopathologically-proven FCDs were extracted. Morphology and intensity-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface, and fed to a 2-step (Support Vector Machine and patch-based) classifier. Classifier performance was assessed compared to manual lesion labels. Our classifier using combined feature selections from MRI and PET outperformed both quantitative MRI and multimodal visual analysis in FCD detection (93% vs 82% vs 68%). No false positives were identified in the controls, whereas 3.4% of the vertices outside FCD lesions were also classified to be lesional ("extralesional clusters"). Patients with type I o...Continue Reading

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Mar 30, 2018·European Journal of Nuclear Medicine and Molecular Imaging·Serge DesarnaudFrancine Chassoux
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Jul 10, 2021·Frontiers in Neuroscience·Daichi Sone, Iman Beheshti
Dec 24, 2021·CNS Neuroscience & Therapeutics·Li KangJiahui Xu

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