Abstracts

Rationale: Identification of epileptogenic lesions plays an important role in presurgical evaluation of patients with epilepsy. Identification of subtle focal cortical lesions is a particular challenge, as there can be a variety of findings on structural MRI ranging from normal to obvious FLAIR abnormalities. Several groups have put forward methods to identify these lesions, generally relying on either training based on manually identified lesions or comparison to a normative database. We have implemented a multi-contrast tissue classification method using local information that assists with visual identification of lesions as areas with intermediate gray matter probability. However, other non-lesional brain regions can also be identified as having intermediate gray matter probability. Here, we describe a surface-based approach to help distinguish epileptogenic lesions from other areas with intermediate probabilities, such as the gray-white junction and primary motor, sensory and visual cortices. Methods: MRIs were obtained on 5 healthy volunteers (2 females, ages 21-40) and 10 patients with epilepsy. Study data were acquired on NIH Clinical Center 3T Philips Achieva MRI Scanners. Imaging included 3D volumetric images (MPRAGE, T2, FLAIR, and Gradient Echo). Tissue classification into cortical gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) was carried out as described in Scott et al.1 Training data sets utilized training masks created in FreeSurfer using images from 5 healthy volunteers. Classifier training and implementation was performed in Python using logistic regression. Gray matter probability maps were created and viewed on surfaces parallel to the gray-white junction (GWJ) created using AFNI. Gray matter probability maps were inspected along each surface moving from subcortical white matter through the gray-white junction into cortical gray matter. Areas of intermediate probability above and below the GWJ were visually evaluated and compared to fMRI finger tapping areas of activation, as well as areas of cortical dysplasia visible on the raw MR images. Results: 7 patients with presumed cortical dysplasia (3 pathologically confirmed) were studied. Upon visual inspection, 6 cases had blurring of the gray-white junction on T1 images and 1 patient had cortical thickening only. Using quantitative analysis, intermediate MPRAGE GM-WM intensity was seen in 4 cases. FLAIR and T2 intensity changes were variable on visual and quantitative analysis, most visible in the subcortical white matter. 6 out of 7 showed intermediate gray matter probability using our classification procedure. When viewed using surfaces, these areas of intermediate probability were seen to extend into the subcortical white matter. In one case with cortical thickening only, the lesion appeared identical to normal gray matter on both visual and quantitative analysis. Other nonlesional regions of intermediate probability were also observed in primary visual, sensory, and motor cortices, as confirmed by fMRI finger tapping regions of activation. Conclusions: In an extension of our previously reported findings, identification of subtle areas of focal cortical dysplasia can be augmented by visualizing gray-matter probability maps on surfaces that step through cortical depths from subcortical white matter into cortical gray matter. This is likely a result of blurring of the GWJ described in type II focal cortical dysplasias, and is similar to the “extension” images used in methods such as those described by Huppertz et al.2 Regions of intermediate probability are also seen in primary cortices, resembling regions identified using myelin mapping techniques.  Funding: This work was supported by the NIH Intramural Research Program.