Associations of Enlarged Perivascular Spaces With Brain Lesions, Brain Age, and Clinical Outcomes in Chronic Traumatic Brain Injury
Bibliographic record
Abstract
<h3>Background and Objectives</h3> Enlarged perivascular spaces (ePVS) have been identified as a key signature of glymphatic system dysfunction in neurological conditions. The incidence and clinical implications of ePVS after traumatic brain injury (TBI) are not yet understood. We investigated whether individuals with chronic moderate-severe TBI had an increased burden of ePVS, and whether ePVS burden is modulated by the presence of focal lesions, older brain age, and poorer sleep quality. We examined whether increased burden of ePVS was associated with poorer cognitive and emotional outcomes. <h3>Methods</h3> Using a cross-sectional design, participants with a single moderate-severe chronic TBI (sustained ≥ 10 years ago) were recruited from an inpatient rehabilitation program. Control participants were recruited from the community. Participants underwent 3T brain MRI, neuropsychological assessment, and clinical evaluations. ePVS burden in white matter was quantified using automated segmentation. The relationship between number of ePVS, group membership, focal lesions, brain age, current sleep quality, and outcome was modelled using negative binomial and linear regressions. <h3>Results</h3> This study included 100 participants with TBI (70% male; <i>M</i> = 56.8 years), and 75 control participants (54.3% male; <i>M</i> = 59.8 years). The TBI group had a significantly greater burden of ePVS (prevalence ratio rate (<i>PRR</i>) = 1.29, <i>p</i> = 0.013, CI<sub>95%</sub> [1.05, 1.57]). The presence of bilateral lesions was associated with greater ePVS burden (<i>PRR</i> = 1.41, <i>p</i> = 0.021, CI<sub>95%</sub> [1.05, 1.90]). There was no association between ePVS burden, sleep quality (<i>PRR</i> = 1.01, <i>p</i> = 0.491, CI<sub>95%</sub> [0.98, 1.048]) and sleep duration (<i>PRR</i> = 1.03, <i>p</i> = 0.556, CI<sub>95%</sub> [0.92, 1.16]). ePVS was associated with verbal memory (β = -0.42, <i>p</i> = 0.006, CI<sub>95%</sub> [-0.72, -0.12]), but not with other cognitive domains. Burden of ePVS was not associated with emotional distress (β = -0.70, <i>p</i> = 0.461, CI<sub>95%</sub> [-2.57, 1.17) or brain age (<i>PRR</i> = 1.00, <i>p</i> = 0.665, CI<sub>95%</sub> [0.99, 1.02]). <h3>Discussion</h3> TBI is associated with a greater burden of ePVS, especially when there have been bilateral brain lesions. ePVS was associated with reduced verbal memory performance. ePVS may indicate ongoing impairments in glymphatic system function in the chronic post-injury period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".