Diffusion tensor imaging and the Montreal cognitive assessment for assessing severe traumatic brain injury
Bibliographic record
Abstract
Objective To investigate any correlation between diffusion tensor imaging (DTI) results and Montreal cognitive assessment (MoCA) scores after severe traumatic brain injury (TBI).Methods Eight male pa-tients with chronic severe TBI were given the MoCA (including memory,attention,speech and executive function).DTI was used to quantify the fractional anisotropy (FA) of white matter fiber tracts in the radial and longitudinal fasciculus,under longitudinal fasciculus,internal capsule,corpus callosum genu and body,and the cingulate cortex.Pearson correlation coefficients were calculated to quantify the correlation between the FA values and MoCA scores.Results There was a positive correlation between FA in the corpus callosum body,corpus callosum genu and the superior longitudinal fasciculus and MoCA total scores.Conclusion The MoCA scores of patients with chronic severe TBI are related to white matter damage in the corpus callosum body,corpus callosum genu and the superior longitudinal fasciculus. Key words: Brain injury; Cognitive impairment; Montreal cognitive assessment; Diffusion tensor imaging ; Rehabilitation
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".