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Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): A Platform for Pragmatic Evidence Generation for Stroke and Dementia Prevention

Award Number: R01NS102233
ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 02/01/2023
PERIOD OF PERFORMANCE END DATE: 01/31/2028

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Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): A Platform for Pragmatic Evidence Generation for Stroke and Dementia Prevention - Project Summary It is a common clinical occurrence that neuroimaging scans obtained in the course of routine clinical care discover covert cerebrovascular disease (CCD), comprising covert brain infarction (CBI) and white matter disease (WMD), in patients with no history of stroke or transient ischemic attack. Indeed, epidemiologic studies indicate that covert CBI are far more common than clinically-evident strokes and these imaging findings are strong, independent risk factors for future stroke and dementia. However, there are no proven preventive treatments or guidelines for initiating risk factor-modifying therapy. While there is strong evidence that antiplatelet therapy and statin therapy are effective in preventing recurrent stroke in patients with prior stroke, it is unclear the degree to which these results apply to patients with CCD. Additionally, patients and providers are rarely aware of these findings, even when they are detected. As part of our previous grant (R01-NS102233), we developed a natural language processing (NLP) algorithm to identify incidentally discovered (id-) CCD from neuroimaging reports, which we ported into a large integrated healthcare system. We identified a cohort of almost a quarter million patients over age 50 who received either a head CT or MRI and were stroke- and dementia- free at the time of the index scan. Key findings of our analyses include: NLP can identify id-CBI and id-WBD from neuroimage reports as well as human readers; that id-CCD is present in about one-third of these scans in an age- and vascular risk factor dependent manner; that id-CCD increases the risk of future stroke and future dementia by approximately 2- to 3-fold; that NLP is able to extract additional important prognostic information on WMD severity from routinely obtained imaging reports; and finally, these patients are generally not given risk factor modifying treatment following the discovery of id-CCD. Given the difficulty of recruiting this at risk population, we now propose to leverage this NLP system as a platform to plan and conduct prospective randomized comparative effectiveness studies to identify optimal treatment strategies for id-CCD. Thus, our aims are: Aim 1: To inform the enrollment criteria of prevention clinical trials and ensure consistency of findings, we will expand the cohort to Kaiser Permanente Northern California and further characterize patients with id-CCD regarding their future stroke and dementia risk. Aim 2: To determine optimal treatment algorithms, we will leverage established simulation models to estimate the treatment effects of different risk factor modification algorithms in patients with id-CCD on future stroke and dementia. Aim 3: To determine optimal recruitment strategies in demographically diverse populations, we will examine the feasibility of recruiting this novel population based on NLP-identified findings both prospectively (i.e. concurrent with clinical identification) and retrospectively (as identified from pre-existing scans). Aim 4: Based on the above findings we will plan a multicenter clinical trial for the prevention of stroke and dementia in this population with CCD.


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: 2026 ( Subtotal = $952,876 )
2026	2026	TUFTS MEDICAL CENTER PARENT, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	6	4/17/2026	EXTENSION WITH OR WITHOUT FUNDS	$952,876
														Subtotal = $952,876

Issue Date FY: 2024 ( Subtotal = $0 )
2024	2020	TUFTS MEDICAL CENTER PARENT, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	12/12/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $0 )
2023	2020	TUFTS MEDICAL CENTER, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	1/19/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2022 ( Subtotal = $0 )
2022	2020	TUFTS MEDICAL CENTER, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	4/19/2022	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2020 ( Subtotal = $520,509 )
2020	2020	TUFTS MEDICAL CENTER, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	5/29/2020	NON-COMPETING CONTINUATION	$520,509
														Subtotal = $520,509

Issue Date FY: 2019 ( Subtotal = $531,215 )
2019	2019	TUFTS MEDICAL CENTER, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	3	5/17/2019	NON-COMPETING CONTINUATION	$531,215
														Subtotal = $531,215

Issue Date FY: 2018 ( Subtotal = $681,151 )
2018	2018	TUFTS MEDICAL CENTER, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	6/18/2018	NON-COMPETING CONTINUATION	$681,151
														Subtotal = $681,151

Issue Date FY: 2017 ( Subtotal = $711,929 )
2017	2017	TUFTS MEDICAL CENTER, INC.	800 WASHINGTON ST	BOSTON	MA	02111	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	1	4/20/2017	NEW	$711,929
														Subtotal = $711,929

Grand Total All Awards = $3,397,680

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Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): A Platform for Pragmatic Evidence Generation for Stroke and Dementia Prevention

Award Number: R01NS102233

ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 02/01/2023

PERIOD OF PERFORMANCE END DATE: 01/31/2028

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