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A Comprehensive Clinical fMRI Software Solution to Enable Mapping of Critical Functional Networks and Cerebrovascular Reactivity in the Brain

Award Number: R01CA258788
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 03/21/2022
PERIOD OF PERFORMANCE END DATE: 02/28/2027

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A Comprehensive Clinical fMRI Software Solution to Enable Mapping of Critical Functional Networks and Cerebrovascular Reactivity in the Brain - Project Summary Functional localization of eloquent brain areas for patients undergoing surgery for brain tumors, epilepsy, or other neurological diseases is crucial to prevent post-surgical deficits and reduce morbidity. Task-based (tb) functional MRI (fMRI), which detects blood oxygenation level–dependent (BOLD) signal changes while a patient performs task paradigms, is a standard-of-care clinical procedure for presurgical mapping of eloquent cortices. Two major limitations of clinical tb-fMRI are a patient's inability to perform the task and lesion-induced impairment of neurovascular coupling (which drives the BOLD signal). Resting-state (rs) fMRI, which measures synchronized BOLD signal oscillations during rest, can be used to map brain networks with minimal requirements for patient compliance and has been demonstrated to accurately localize motor and language areas for presurgical planning. Cerebrovascular reactivity (CVR) mapping, accessed by dynamic BOLD imaging during a hypercapnia task such as breath-holding, can be used to identify areas with potential false-negative fMRI results due to neurovascular uncoupling (NVU) and has been suggested as an emerging standard to be used with clinical fMRI. Currently, there are no commercially available FDA-cleared software tools for localizing the resting-state networks (RSNs) or CVR. Clinical investigators have relied on research software packages that are either not clinically integrated or not yet optimized and validated in large patient populations. Thus, a vetted software solution is urgently needed to enable these state-of-the-art fMRI methods to benefit patients beyond the limitations of tb-fMRI. We hypothesize that enhancing, optimizing, and validating our preliminary software and integrating it with an established commercial fMRI platform will create robust solutions for clinical mapping of RSN and CVR. Through three specific aims, the software solutions will be optimized and tested with rs-fMRI and CVR datasets from approximately 350 patients with brain tumors or epilepsy at three institutions. Aim 1 is to create the software for mapping RSNs and determine optimized workflows for localizing eloquent areas including primary visual, motor (hands, tongue, and feet), and language (primary and secondary) areas. Both seed-based correlation and independent component analysis will be incorporated. Aim 2 is to create the software for mapping CVR and determine the optimized workflow for identifying and visualizing brain areas with potential false-negative fMRI results. The software will include a multiple-latency general linear model and a unique graphical user interface to visualize the NVU. Aim 3 is to test and validate the software with presurgical fMRI datasets. The results will be compared against those obtained from (1) processed using widely used research software packages, (2) tb- fMRI, and (3) intraoperative direct cortical stimulation. This research is anticipated to create robust and clinically available software that will greatly increase the patient population who can benefit from presurgical fMRI and will improve confidence in functional localization for surgical planning. This will directly benefit patients by preserving their post-surgical functions while allowing surgeons to safely maximize the resection of brain lesions.


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: 2025 ( Subtotal = $549,581 )
2025	2025	THE UNIVERISTY OF TEXAS M.D. ANDERSON CANCER CENTER	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Detection and Diagnosis Research	001	4	5/22/2025	NON-COMPETING CONTINUATION	$54,957
2025	2025	THE UNIVERISTY OF TEXAS M.D. ANDERSON CANCER CENTER	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Detection and Diagnosis Research	000	4	2/14/2025	NON-COMPETING CONTINUATION	$494,624
														Subtotal = $549,581

Issue Date FY: 2024 ( Subtotal = $362,261 )
2024	2024	THE UNIVERISTY OF TEXAS MD ANDERSON CANCER CENTER, A COMPONENT OF THE UNIVERISTY OF TEXAS SYSTEM	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Detection and Diagnosis Research	000	3	1/30/2024	NON-COMPETING CONTINUATION	$343,195
2024	2024	THE UNIVERISTY OF TEXAS MD ANDERSON CANCER CENTER, A COMPONENT OF THE UNIVERISTY OF TEXAS SYSTEM	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Detection and Diagnosis Research	001	3	4/16/2024	NON-COMPETING CONTINUATION	$19,066
														Subtotal = $362,261

Issue Date FY: 2023 ( Subtotal = $373,701 )
2023	2023	UNIVERSITY OF TEXAS M. D. ANDERSON CANCER CENTER, THE	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Detection and Diagnosis Research	000	2	4/6/2023	NON-COMPETING CONTINUATION	$373,701
														Subtotal = $373,701

Issue Date FY: 2022 ( Subtotal = $402,421 )
2022	2022	UNIVERSITY OF TEXAS M. D. ANDERSON CANCER CENTER, THE	1515 HOLCOMBE BLVD	HOUSTON	TX	77030	HARRIS	USA	Cancer Detection and Diagnosis Research	000	1	3/21/2022	NEW	$402,421
														Subtotal = $402,421

Grand Total All Awards = $1,687,964

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A Comprehensive Clinical fMRI Software Solution to Enable Mapping of Critical Functional Networks and Cerebrovascular Reactivity in the Brain

Award Number: R01CA258788

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 03/21/2022

PERIOD OF PERFORMANCE END DATE: 02/28/2027

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