Abstract TP181: Advanced Diffusion and Functional MRI Measures Are Associated with Microstructural Morphology and Cognitive Function in Subacute Ischemic Cerebellar Stroke
Bibliographic record
Abstract
Introduction: The mechanisms of cognitive dysfunction following ischemic cerebellar stroke (CS) are not well understood. Furthermore, traditional clinical stroke MRI protocols often cannot identify subtle and early changes in normal appearing tissue of the cerebellum. We aimed to implement an advanced MRI protocol in subacute CS patients to better understand outcomes. Hypothesis: The MRI markers for tissue microstructure and cerebrovascular function (CVF) in the cerebellum will provide mechanistic insight into post-stroke cognitive dysfunction. Methods: After 4 weeks of stroke onset, 13 first-time subacute mildly-impaired ischemic stroke participants (PPT) were imaged on a 3T Siemens Prisma MRI scanner with an advanced multi-shell diffusion-weighted protocol to map of Non-Gaussian Diffusion (NGD) and a multi-echo resting-state functional protocol with a breath-hold task (rs+BH-fMRI) to map CVF. PPT demographics: 62.6(11.44) years, sex (11 males), race (1 Latino, 2 Asian, 4 black, 6 white), NIHSS median = 1 (IQR 0-3), Montreal Cognitive Assessment (MoCA) median = 25 (IQR 21-28). 3 PPTs were diagnosed with right cerebellar stroke (CS), and 10 PPTs were diagnosed with non-cerebellar subcortical stroke (NCS). Statistical analyses were performed to: 1) identify the group differences between the CS PPTs versus the NCS PPTs for both NGD and rs+BH-fMRI metrics in the normal appearing white and gray matter of the infarcted cerebellum, and 2) for all PPTs, correlate the NGD metrics in the left 'unaffected' cerebellum white matter versus MoCA score. Results: Fig. 1 shows the group comparison for significantly increased NGD (p<0.05) in the infarcted hemisphere of CS PPTs versus NCS PPTs. Classical fractional anisotropy (FA) did not reach significance. Fig. 2 shows the individual rs+BH-fMRI data (Fig. 2), where the amplitude of the CVF response was significantly decreased for the CS PPTs versus NCS PPTs in the infarcted cerebellum (p=0.043). Fig. 3 shows the correlational analysis in the 'unaffected' left cerebellar hemisphere with significantly increased NGD (r=0.473, p=0.038) with respect to MoCA scores. Classical FA did not reach significance. Conclusions: Using advanced MRI protocols we demonstrated that novel NGD metrics and breath-hold based fMRI measures are sensitive to cerebellar morphology post-stroke and correlate with cognitive function. These measures can be used to identify trajectories for recovery and accelerated cognitive impairment after ischemic CS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".