One in 100 people worldwide has epilepsy, which causes substantial morbidity and mortality. A third of individuals with epilepsy do not respond to anticonvulsant medications; in these cases surgical resection of the seizure focus may lead to seizure freedom. However, surgical success depends upon identification of a structural epileptogenic lesion on MRI, and up to 50% of individuals with focal epilepsy have no lesion on standard MRI. Patients without identified lesions often require invasive intracranial monitoring to localize the seizure focus for surgery, with a greater risk of complications. Better tools are needed to identify the seizure onset zone and improve treatment for NLFE. Failure to identify lesions in focal epilepsy may result from two possible causes: 1) a structural lesion exists but is not detectable by current clinical MRI or 2) a structural lesion may not exist, i.e. the tissue abnormality is at the cellular or molecular level, or may not be discrete and spatially localized. This proposal focuses on the undetected structural lesion, aiming to improve upon current MRI techniques to increase the likelihood of finding a lesion responsible for seizures. The most frequently identified histopathology at surgery for NLFE is focal cortical dysplasia (FCD), particularly Type 1 where subtle laminar disorganization is present. We hypothesize that epileptogenic abnormalities, particularly FCD Type 1, can be detected preoperatively in NLFE by identification of 1) increased regional blurring of the cortical grey matter/white matter (GM/WM) boundary, 2) microstructural tissue diffusion abnormalities, and 3) decreased regional cortical thickness. We will apply advanced MRI technologies and computational morphometric analysis to identify these subtle structural abnormalities in individuals with NLFE. The Co-PI (Winawer) has an NIH-funded R01 to identify molecular abnormalities in resected brain tissue of individuals undergoing surgery for NLFE. This provides a framework for recruitment of participants for our imaging study and a unique opportunity to compare histology and imaging in a well-characterized cohort. Our Study Aims are to: 1: Use advanced whole brain 3T MRI paired with computational morphometric analysis and multi-shell diffusion imaging to detect regional blurring of the GM/WM boundary and microstructural tissue diffusion abnormalities, and identify areas of decreased regional cortical thickness in our cohort of individuals with NLFE; and 2: Use high-resolution 7T MRI paired with computational morphometric analysis to detect regional blurring of the GM/WM boundary and reduced cortical thickness in NLFE. Novel computational morphometric techniques will allow objective statistical assessment of structural differences. The immediate goal of our project is to detect epileptogenic lesions undiscovered by current clinical MRI and other noninvasive imaging modalities, and to better understand structural pathologies underlying NLFE. Our long-term goal is to improve surgical outcome in NLFE, resulting in better seizure control and quality of life.

Public Health Relevance

Non-lesional focal epilepsy (NLFE) is a difficult to treat form of epilepsy that consists of recurrent seizures arising from an area of the brain that has no apparent structural abnormality?an ?invisible lesion? ? on routine clinical MRI. We propose to use advances in MRI technology and image analysis to detect epileptogenic lesions missed by current techniques. This also should increase our understanding of the pathology of the ?invisible? lesion that gives rise to seizures, and potentially lead to improvements in seizure control, surgical outcomes, and quality of life for individuals with NLFE.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21NS101303-01A1
Application #
9455067
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Whittemore, Vicky R
Project Start
2017-09-30
Project End
2019-08-31
Budget Start
2017-09-30
Budget End
2018-08-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Neurology
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032