This project proposes to build computer-aided diagnostic (CAD) software for use in identifying cortical malformations known as Focal Cortical Dysplasias (FCDs), which are a common cause of epileptic seizures. The intent is for the software, used by a neuroradiologist at a clinical workstation, to decrease the time- intensive nature of the current diagnostic procedure, while simultaneously increasing sensitivity of dysplasia identification, thus reducing the number of missed lesions and making neuroradiologists more effective and more efficient. Epilepsy is a common neurological disorder, characterized by recurrent unprovoked seizures, that exacts a large toll upon society in terms of both quality of life and health care costs. Malformations of Cortical Development (MCD) are the most common cause of seizures in children and the second most common cause in adults. Focal Cortical Dysplasia is a common form of MCD that is responsible for the vast majority of treatment resistant epilepsy in patients with MCD, and is intractable to any form of pharmacological intervention, requiring surgical resection to remediate. Unfortunately, the radiological diagnosis of FCD is exceedingly difficult in a large percentage of cases due to their focal and subtle nature. Thus, while resection of these dysplasias can often cure seizures, they can be missed for years or decades, resulting in increased neurological damage and degradation of quality of life due to chronic seizures. In principle high resolution MRI can be used to increase diagnostic accuracy. While this is becoming more common in clinical practice, the need for high patient throughput, lack of clinical information and inexperience often results i these lesions being missed on routine clinical reads by neuroradiologists. The project will build upon a foundation of existing technology for the generation of quantitative measures of the human brain based on MRI imaging, known in the neuroimaging research domain as FreeSurfer. The project will make use of an existing MRI dataset of 20 subjects with histologically-confirmed FCD, labeled by a neuroradiologist, and 20 control subjects with epilepsy that is not due to FCD. The project has two aims: development and performance evaluation of a graphical user interface (GUI) software tool making use of FreeSurfer-based measures that neuroradiologists will use at a clinical workstation in a new diagnostic work- flow, an aim that will be greatly facilitated by our close collaboration with two senior neuroradiologist both experienced with the diagnosis of FCD;and an aim to begin the work necessary to meet FDA regulations covering the planned commercial product. The latter aim is important for the long-term project goal of advancing the state of other clinical diagnostic procedures through the building of additional CAD tools making use of FreeSurfer's brain measures, including diseases as varied as Huntington's disease, Alzheimer's disease, tumor monitoring and hydrocephalus.

Public Health Relevance

The proposal is to build software for computer-aided diagnosis of Focal Cortical Dysplasia (FCD), a malformation of brain development that is a common cause of epileptic seizures in children and adults. The proposed software will offer a neuroradiologist a faster and more accurate diagnostic procedure over the currently difficult means. By identifying abnormalities otherwise missed, the ensuing surgical removal of an abnormality can often cure seizures.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
Project #
1R41NS083101-01A1
Application #
8590833
Study Section
Special Emphasis Panel (ZRG1-SBIB-T (10))
Program Officer
Babcock, Debra J
Project Start
2013-09-15
Project End
2014-08-31
Budget Start
2013-09-15
Budget End
2014-08-31
Support Year
1
Fiscal Year
2013
Total Cost
$359,391
Indirect Cost
Name
Corticometrics, LLC
Department
Type
DUNS #
078509164
City
Chelsea
State
MA
Country
United States
Zip Code
02150
Wachinger, Christian; Golland, Polina; Kremen, William et al. (2015) BrainPrint: a discriminative characterization of brain morphology. Neuroimage 109:232-48