Measuring Cortical Thickness in Brain MRI Volumes to Detect Focal Cortical Dysplasia

Nowadays the prevalence of epilepsy is estimated to be around 1% of the population where up to 40% of the patients continue to have seizures despite optimal drug treatment [1]. In patients with drug refractory epilepsy, approximately one-half suffer from localized malformation of cortical development known as focal cortical dysplasia (FCD). There, the epilepsy surgery can yield a high chance of seizure freedom, even up to 80%. However, despite the increased quality of the magnetic resonance imaging (MRI) which is often used in diagnosis of the FCD, lesion identification remains a very difficult task. Strikingly, the clinical experience suggests that this type of lesions can be missed in the initial evaluation in up to 35% of the cases. This is mainly due to a combination of factors including a possibly subtle lesion, the complex convolution of the human cerebral cortex and the dependence on the expertise and attention of the radiologist viewing the MR images. Among others, one of the main cortical anomalies observed in the FCD pathology is focal thickening of the cortex. This manifestation of the disease looks for the algorithms able to detect the changes of the cortical thickness. In the present work, we propose a new algorithm for cortical thickness measurement in T1 weighted (T1-w) MRI images aiming to overcome the major limitation of a number of the existing similar methods which could lead to underor over-estimated thickness of grey matter within sulci: (1) lack of awareness of the partial volume (PV) effect (the presence of multiple tissue classes in a single voxel) present at both the white matter (WM) to gray matter (GM) and the GM to cerebrospinal fluid (CSF) transition, and (2) ignorance of the regions of buried cortex where the CSF between the sulci is not resolved.