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Model Development for Prediction of Surgical Outcome in Temporal Lobe Epilepsy Patients: Incorporation of the Correlation between Post-Surgical Reorganization Phenotypes and Pre-Surgical Data

Award Number: R01NS112816
ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Model Development for Prediction of Surgical Outcome in Temporal Lobe Epilepsy Patients: Incorporation of the Correlation between Post-Surgical Reorganization Phenotypes and Pre-Surgical Data - Project Summary For epileptic patients who undergo brain resection or ablation interventions, it is the postoperative brain that will dictate seizure status, whether controlled or relapsed. Yet, it is data from the preoperative brain that drives the postoperative prediction process – a critical process for both patient and doctor, and one that is only clinically meaningful when seizure outcomes are predicted presurgically to optimize surgical-decision making. Accordingly, we propose to develop a multi-step model that will establish more accurate predictors of post- surgical seizure outcome in temporal lobe epilepsy (TLE) emphasizing post-surgical status, for it is the areas of the brain spared during surgery that form the neural substrates generating postoperative seizures. A second perspective motivating our project is the need to identify those changes in functional and structural brain network organization that support adaptive versus maladaptive seizure outcomes following brain surgery. These are the network changes (e.g., the new seizure generators) that dispose and place a potential surgical candidate on a specific outcome trajectory. Therefore, identifying the phenotypes of brain reorganization and change, and incorporating their status into presurgical predictive models of outcome will likely prove crucial to enhancing our ability to predict postoperative neuroplastic responses. While existing outcome prediction models in TLE have focused on clinical variables (e.g., lesional status), we choose instead to focus on structural and functional measures of network reorganization (communication dynamics, regional interactions, structural control). This stems from our belief that capturing network changes throughout the whole postsurgical brain offers a better practical method for identifying and predicting the latent seizure foci (epileptogenesis) that will emerge after surgery. Through machine learning techniques we will deliver an algorithm to be used with new, potential surgical patients, an algorithm that utilizes solely presurgical data, but incorporates our innovative prediction about postsurgical brain organization. Accordingly, our approach provides both a methodologic and conceptual (reorganization phenotypes) advance. The scientific premise leading to our hypotheses is that the failure in the literature to account for the impact of unresected/ablated brain regions, and the brain reorganizations these areas compel, has seriously impeded the predictive power of previous outcome models.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2023 ( Subtotal = $451,770 )
2023	2023	THOMAS JEFFERSON UNIVERSITY	1020 WALNUT ST STE 1	PHILADELPHIA	PA	19107	PHILADELPHIA	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	5	3/31/2023	NON-COMPETING CONTINUATION	$451,770
														Subtotal = $451,770

Issue Date FY: 2022 ( Subtotal = $442,761 )
2022	2022	THOMAS JEFFERSON UNIVERSITY	1020 WALNUT ST STE 1	PHILADELPHIA	PA	19107	PHILADELPHIA	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	3/31/2022	NON-COMPETING CONTINUATION	$442,761
														Subtotal = $442,761

Issue Date FY: 2021 ( Subtotal = $442,761 )
2021	2021	THOMAS JEFFERSON UNIVERSITY	1020 WALNUT ST STE 1	PHILADELPHIA	PA	19107	PHILADELPHIA	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	001	3	3/23/2021	NON-COMPETING CONTINUATION	$442,761
2021	2020	THOMAS JEFFERSON UNIVERSITY	1020 WALNUT ST STE 1	PHILADELPHIA	PA	19107	PHILADELPHIA	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	3/16/2021	NON-COMPETING CONTINUATION	$0
														Subtotal = $442,761

Issue Date FY: 2020 ( Subtotal = $442,761 )
2020	2020	THOMAS JEFFERSON UNIVERSITY	1020 WALNUT ST STE 1	PHILADELPHIA	PA	19107	PHILADELPHIA	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	3/27/2020	NON-COMPETING CONTINUATION	$442,761
														Subtotal = $442,761

Issue Date FY: 2019 ( Subtotal = $490,043 )
2019	2019	THOMAS JEFFERSON UNIVERSITY	1020 WALNUT ST STE 1	PHILADELPHIA	PA	19107	PHILADELPHIA	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	1	6/26/2019	NEW	$490,043
														Subtotal = $490,043

Grand Total All Awards = $2,270,096

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Model Development for Prediction of Surgical Outcome in Temporal Lobe Epilepsy Patients: Incorporation of the Correlation between Post-Surgical Reorganization Phenotypes and Pre-Surgical Data

Award Number: R01NS112816

ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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