R01NS122184
Project Grant
Overview
Grant Description
Personalized Profiles of Pathology in Pediatric Traumatic Brain Injury - Project Summary/Abstract
Children and adolescents have the highest rate of Traumatic Brain Injury (TBI) in the general population, but current tools for examining structural and functional deficits from MR data have several key limitations.
First, there is no gold standard procedure for considering lesions in imaging analysis, and second, existing tools have been built on adult populations. We propose to develop a workflow that addresses both of these issues and supports the extension of novel tools for advanced, multimodal analysis, and to use that workflow to identify factors associated with outcome.
Personalized Profiles of Pathology (P3) will include registration to age-appropriate templates and lesion segmentation, allowing for voxelwise lesion symptom mapping, morphometric analyses, shape analysis, and network diffusion modeling as part of the package, with options for longitudinal analysis as well. This workflow will include and extend novel pipelines.
Voxelwise lesion symptom mapping examines the correspondence between lesion location and specific symptoms, but has been underpowered in existing applications. Network diffusion modeling uses diffusion MRI data from healthy individuals to model the spread of pathology. While this is currently used on chronically injured patients to estimate the epicenter of injury, in this proposal, longitudinal data will be used to validate predictions of pathology spread. Tract-wise statistical analysis similarly uses healthy data to predict the degree of disconnection based on lesion location. Symmetric multivariate linear reduction reduces high dimensional imaging, cognitive, and clinical data to components, revealing patterns of disruption.
By including all of these individual approaches across multiple sites, P3 will allow for multimodal examination of the impact of TBI on pediatric patients with greater statistical power.
In Aim 1, we will develop and test P3 on cohorts from eight sites. With input from clinical experts in neurology, rehabilitation, neuropsychology, radiology, and brain development, and technical expertise from mathematics, computer science, and neuroimaging analytics, we will ensure that P3 is statistically and computationally valid and clinically relevant.
In Aim 2, we will extract common neuropsychological endpoints from disparate scales across cohorts and use these measures with brain metrics generated by P3 to determine factors associated with outcome and identify subgroups within the patient population.
In Aim 3, we will distribute P3 to a network of beta-testing sites to run locally, allowing for further improvement and validation, and disseminate P3 to the research community. Through meta-analysis or harmonization paired with mega-analysis, we will combine effects across sites and examine consistency in effect size, location, and direction.
Education will occur through tutorials at national and international conferences, site visits, and through written documentation. P3 will be made available online, with continuing support from the development team.
The ultimate goal of P3 is to better understand heterogeneity in post-injury outcome to inform future treatment development.
Children and adolescents have the highest rate of Traumatic Brain Injury (TBI) in the general population, but current tools for examining structural and functional deficits from MR data have several key limitations.
First, there is no gold standard procedure for considering lesions in imaging analysis, and second, existing tools have been built on adult populations. We propose to develop a workflow that addresses both of these issues and supports the extension of novel tools for advanced, multimodal analysis, and to use that workflow to identify factors associated with outcome.
Personalized Profiles of Pathology (P3) will include registration to age-appropriate templates and lesion segmentation, allowing for voxelwise lesion symptom mapping, morphometric analyses, shape analysis, and network diffusion modeling as part of the package, with options for longitudinal analysis as well. This workflow will include and extend novel pipelines.
Voxelwise lesion symptom mapping examines the correspondence between lesion location and specific symptoms, but has been underpowered in existing applications. Network diffusion modeling uses diffusion MRI data from healthy individuals to model the spread of pathology. While this is currently used on chronically injured patients to estimate the epicenter of injury, in this proposal, longitudinal data will be used to validate predictions of pathology spread. Tract-wise statistical analysis similarly uses healthy data to predict the degree of disconnection based on lesion location. Symmetric multivariate linear reduction reduces high dimensional imaging, cognitive, and clinical data to components, revealing patterns of disruption.
By including all of these individual approaches across multiple sites, P3 will allow for multimodal examination of the impact of TBI on pediatric patients with greater statistical power.
In Aim 1, we will develop and test P3 on cohorts from eight sites. With input from clinical experts in neurology, rehabilitation, neuropsychology, radiology, and brain development, and technical expertise from mathematics, computer science, and neuroimaging analytics, we will ensure that P3 is statistically and computationally valid and clinically relevant.
In Aim 2, we will extract common neuropsychological endpoints from disparate scales across cohorts and use these measures with brain metrics generated by P3 to determine factors associated with outcome and identify subgroups within the patient population.
In Aim 3, we will distribute P3 to a network of beta-testing sites to run locally, allowing for further improvement and validation, and disseminate P3 to the research community. Through meta-analysis or harmonization paired with mega-analysis, we will combine effects across sites and examine consistency in effect size, location, and direction.
Education will occur through tutorials at national and international conferences, site visits, and through written documentation. P3 will be made available online, with continuing support from the development team.
The ultimate goal of P3 is to better understand heterogeneity in post-injury outcome to inform future treatment development.
Awardee
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Salt Lake City,
Utah
841121103
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 344% from $707,328 to $3,140,362.
University Of Utah was awarded
Pediatric Traumatic Brain Injury Analysis Tool: Enhancing Outcome Prediction
Project Grant R01NS122184
worth $3,140,362
from the National Institute of Neurological Disorders and Stroke in January 2021 with work to be completed primarily in Salt Lake City Utah United States.
The grant
has a duration of 4 years 10 months and
was awarded through assistance program 93.853 Extramural Research Programs in the Neurosciences and Neurological Disorders.
The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 5/21/26
Period of Performance
1/1/22
Start Date
11/30/26
End Date
Funding Split
$3.1M
Federal Obligation
$0.0
Non-Federal Obligation
$3.1M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01NS122184
Transaction History
Modifications to R01NS122184
Additional Detail
Award ID FAIN
R01NS122184
SAI Number
R01NS122184-2188622446
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75NQ00 NIH National Institute of Neurological Disorders and Stroke
Funding Office
75NQ00 NIH National Institute of Neurological Disorders and Stroke
Awardee UEI
LL8GLEVH6MG3
Awardee CAGE
3T624
Performance District
UT-01
Senators
Mike Lee
Mitt Romney
Mitt Romney
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute of Neurological Disorders and Stroke, National Institutes of Health, Health and Human Services (075-0886) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,345,433 | 100% |
Modified: 5/21/26