Epilepsy affects 65 million people worldwide; approximately 30% of them do not respond to medications but can be cured by surgery. Focal cortical dysplasia (FCD), a major pathology for medically intractable epilepsies, is frequently missed by visual analysis of the conventional MRI, making surgical treatment very difficult. We propose to develop a novel quantitative MRI acquisition and analysis framework specific for epilepsy patients, which could provide more sensitive and specific measures of brain structure, thereby improving FCD detection and subtype prediction. To this end, the quantitative framework will be developed and validated in three steps: (1) Develop high-resolution Magnetic Resonance Fingerprinting (MRF) scan that allows simultaneous quantification of multiple tissue property maps efficiently, accurately and precisely. These quantitative maps have shown to be more sensitive and specific on detecting and characterizing subtle signal abnormalities. (2) Develop image post-processing methods to analyze quantitative maps, which will provide quantitative measurements that highlight additional morphological features, such as gray-white boundary blurring, abnormal cortical thickness and folding. (3) Develop machine-learning-based feature screening and prediction tools to characterize group-level features differentiating FCD subtypes, and predict individual-level FCD location and subtyping. Because detection and subtype prediction of FCD are both associated with seizure outcomes, epileptologists can use this tool to provide more personalized and customized counseling. The result of our proposed work promises a paradigm shift by converting the current standard-care of visual/qualitative MRI review to a quantitative framework, including data acquisition, post-processing and decision support tool, that would eventually lead to better treatment planning, reduction in unnecessary pre-surgical evaluation tests (especially invasive evaluation), and improved post-operative seizure outcomes in patients with devastating and disabling medically intractable epilepsy. The quantitative nature of our acquisition/analysis methods also makes it possible to be uniformly adopted by other centers with high consistency.
Epilepsy affects 65 million people worldwide; approximately 30% of them do not respond to medications but can be cured by surgery. Focal cortical dysplasia, a major pathology for medically intractable epilepsies, are frequently missed by visual analysis of the conventional MRI, making surgical treatment very difficult. Here we propose to develop and validate novel, noninvasive and quantitative MRI acquisition and post-processing techniques, in order to guide epilepsy surgery and make more patients seizure-free.
