Changes to white matter microstructure in transient ischemic attack: A longitudinal diffusion tensor imaging study
Bibliographic record
Abstract
Transient ischemic attack (TIA) is associated with localized ischemic changes, identifiable by diffusion-weighted imaging. Past research has not considered whether TIA is also associated with diffuse changes to white matter microstructure; further past work has not tracked changes longitudinally. Here we examine whole-brain changes in fractional anisotropy (FA) in individuals with TIA presenting with sensorimotor symptoms. Twenty individuals with a recent (within 30 days) TIA and 12 healthy older adults were recruited. Participants underwent 3.0 T diffusion MRI at baseline; scans were repeated for the TIA group 90 days post-TIA. Track-based spatial statistics (TBSS) was used to conduct a voxel-wise analysis of FA between groups. FA was significantly lower in the TIA group relative to healthy controls, primarily in anterior white matter tracts including: forceps minor, anterior thalamic radiations, cingulum, inferior fronto-occipital fasciculus, and corticospinal tract. TBSS results informed an ROI-based longitudinal examination of FA in the TIA group. There were no changes to TBSS-identified clusters, forceps minor, or the corticospinal tract over time. There was lower FA in the anterior thalamic radiations in the TIA-affected hemisphere at baseline, but no difference between hemispheres at 90 days. In summary, individuals with TIA presenting with sensorimotor symptoms have decreased FA in tracts that are also implicated in sensorimotor function, which outlast the clinical symptoms associated with TIA. This suggests a more profound type of brain damage associated with TIA than has been typically described in past work. Diffusion tensor imaging may have utility as a marker of TIA-associated changes to white matter pathways. Hum Brain Mapp 38:5795-5803, 2017. © 2017 Wiley Periodicals, Inc.
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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".