# Neuroimaging-based identification of Traumatic Brain Injury subtypes

> **NIH VA IK2** · OLIN TEAGUE VETERANS CENTER · 2020 · —

## Abstract

Traumatic Brain Injuries (TBIs) are highly prevalent among post-deployment Veterans and are linked
with a variety of chronic cognitive and behavioral symptoms, including problems with learning and
memory, anxiety and other mood issues, executive function deficits, and personality changes. Such
symptoms often have severe impacts on Veterans’ functional outcomes and quality of life. These
symptoms are induced by neurological damage, as TBI is known to cause diffuse axonal injuries that
impair the normal networked communication between brain regions, affecting behavior and cognition.
However, current techniques to assess different types of TBI, and thus to predict resulting outcomes,
do not use neurobiological information in the assessment. Instead, judgments of TBI severity are made
based primarily on the post-traumatic symptoms such as amnesia or loss of consciousness.
Unfortunately, these post-traumatic symptom-based assessments are not strongly predictive of
functional outcomes. Thus, there is both a clinical and a research need to identify more refined and
precise TBI subtypes that are based on neurobiological measures and that predict functional outcomes.
 The applicant, Dr. Gordon, is an acknowledged expert in advanced neuroimaging techniques, and
particularly in examining human brain networks using noninvasive MRI-based approaches. Through his
primary VA appointment at the VISN 17 Center of Excellence for Research on Returning War Veterans,
Dr. Gordon has access to a large pool of extensively characterized Veterans with and without TBI, as
well as to a research-dedicated MRI scanner. Further, Dr. Gordon has established collaborations with
external researchers who are experts in advanced classification of neuroimaging data for the purposes
of subtype identification. In short, Dr. Gordon is in an ideal position to conduct the necessary research
to identify neurobiologically-informed subtypes of TBI.
 In the proposed study, Dr. Gordon will use neuroimaging techniques to characterize axonal tract
damage and disruption of networked communication in 100 Veterans (including 70 with a post-
traumatic symptom-defined history of TBI). He will then employ advanced data clustering techniques to
identify subtypes of TBI that are both based on neurobiological measures of structural and network
damage, and explain a high degree of variance in outcome measures of functioning in everyday life. He
will identify which neurobiological measures allow identification of subtypes that best explain variance
in outcomes. He will then conduct extensive behavioral characterization of the identified subtypes.
 In summary, this project will identify neurobiologically-informed subtypes of TBI in the population that
predict functional outcomes better than classic severity assessments. If successful, this work will
influence both clinical treatment and scientific investigation of TBI. In particular, identification of
neurobiologically-based TBI subtypes could enable improve...

## Key facts

- **NIH application ID:** 9834683
- **Project number:** 5IK2CX001680-02
- **Recipient organization:** OLIN TEAGUE VETERANS CENTER
- **Principal Investigator:** Evan M. Gordon
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2019-01-01 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9834683

## Citation

> US National Institutes of Health, RePORTER application 9834683, Neuroimaging-based identification of Traumatic Brain Injury subtypes (5IK2CX001680-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9834683. Licensed CC0.

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