Manganese-Enhanced Magnetic Resonance Imaging as a Diagnostic and Dispositional Tool after Mild-Moderate Blast Traumatic Brain Injury
Bibliographic record
Abstract
Traumatic brain injury (TBI) caused by explosive munitions, known as blast TBI, is the signature injury in recent military conflicts in Iraq and Afghanistan. Diagnostic evaluation of TBI, including blast TBI, is based on clinical history, symptoms, and neuropsychological testing, all of which can result in misdiagnosis or underdiagnosis of this condition, particularly in the case of TBI of mild-to-moderate severity. Prognosis is currently determined by TBI severity, recurrence, and type of pathology, and also may be influenced by promptness of clinical intervention when more effective treatments become available. An important task is prevention of repetitive TBI, particularly when the patient is still symptomatic. For these reasons, the establishment of quantitative biological markers can serve to improve diagnosis and preventative or therapeutic management. In this study, we used a shock-tube model of blast TBI to determine whether manganese-enhanced magnetic resonance imaging (MEMRI) can serve as a tool to accurately and quantitatively diagnose mild-to-moderate blast TBI. Mice were subjected to a 30 psig blast and administered a single dose of MnCl2 intraperitoneally. Longitudinal T1-magnetic resonance imaging (MRI) performed at 6, 24, 48, and 72 h and at 14 and 28 days revealed a marked signal enhancement in the brain of mice exposed to blast, compared with sham controls, at nearly all time-points. Interestingly, when mice were protected with a polycarbonate body shield during blast exposure, the marked increase in contrast was prevented. We conclude that manganese uptake can serve as a quantitative biomarker for TBI and that MEMRI is a minimally-invasive quantitative approach that can aid in the accurate diagnosis and management of blast TBI. In addition, the prevention of the increased uptake of manganese by body protection strongly suggests that the exposure of an individual to blast risk could benefit from the design of improved body armor.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".