Journal of neurotrauma
August 7, 2026 · via Europe PMC
Region-Specific Brain Imaging Correlates of Repetitive Head Impact Exposure in Nonconcussed High School Football Players.
Holcomb JM, Bell NM, Miller LE, +9 more, Davenport EM
AI summary — for doctors, generated from the abstract only
In high school football players without concussion, greater cumulative head impact exposure correlated with frontal cortex MRI changes.
What was studied
Imaging study of 87 player-seasons comparing pre- to postseason mean diffusivity and resting fMRI power with cumulative impact exposure, with noncollision athlete controls.
Key findings
- Impact exposure correlated positively with mean diffusivity change and inversely with fMRI power change in the frontal cortex.
- High-exposure players (n = 13) differed from low-exposure players and non-collision controls; low-exposure players did not differ from controls.
- Biomechanical modeling placed high-impact regions where imaging abnormalities occurred; MEG showed no associations.
Clinical relevance
Subconcussive impacts may produce brain changes without any diagnosed concussion.
Who should care
Limitations
Observational imaging changes of uncertain clinical significance in a small high-exposure group.
Reduce cumulative head impact exposure in youth football.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Repetitive, nonconcussive head impacts in collision sports are associated with lasting neurophysiological effects. This study investigates region-specific changes in neocortical mean diffusivity (MD) and resting-state functional magnetic resonance imaging (fMRI) power spectral density (fMRI-PSD) that correlate with cumulative nonconcussive linear risk-weighted exposure (RWE-Lin) sustained over one high school football season. Pre- to postseason percent changes in MD (%ΔMD) and fMRI-PSD (%ΔfMRI-PSD) were calculated for football players without diagnosed concussions during the season of observation (= 87 player-seasons). Voxelwise linear regression analyses examined relationships between RWE-Lin with neocortical %ΔMD and %ΔfMRI-PSD. False discovery rate-corrected alpha thresholds of 0.0125 accounted for multiple comparisons and directionality within each test. While controlling for age, body mass index, days between scans, position group (skill vs. line), level (junior varsity vs. varsity), and concussion history, RWE-Lin was significantly positively correlated with %ΔMD (= 1.12 × 10) and inversely correlated with %ΔfMRI-PSD in the frontal cortex (= 7.36 × 10). Football players were stratified into high RWE-Lin (= 13) and low RWE-Lin (= 37) groups using the Jenks natural breaks algorithm. Noncollision athletes (NCAs,= 11) served as external controls. When comparing imaging measures across the three groups, the high RWE-Lin football group showed significant differences from both NCA and low RWE-Lin football groups in frontal %ΔMD and %ΔfMRI-PSD (< 0.05). No significant imaging differences were observed between NCA and low RWE-Lin football groups. Biomechanical modeling localized high-risk impact regions that have high spatial correspondence to the observed imaging abnormalities. Exploratoryvoxelwise analyses of magnetoencephalography spectral power detected no significant voxelwise associations with RWE-Lin. In the absence of diagnosed concussion, high-impact football players exhibit abnormal structural and neurovascular changes in the frontal cortex. These regions overlap with those identified to be at greatest risk from biomechanical modeling and those implicated in the pathogenesis of chronic traumatic encephalopathy. Importantly, these imaging abnormalities were not generally observed in football players with lower RWE-Lin. These findings suggest that limiting the number and severity of head impacts may be an effective strategy to mitigate subclinical brain injury in American football.
DOI
10.1177/08977151261474842
PMID
42563522
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
Want more like this?
Browse more from the feed. A free account unlocks the full feed, saving and communities.
Back to the research feed