Diffusion imaging changes in the treated tract following focused ultrasound thalamotomy for tremor
Bibliographic record
Abstract
We describe diffusion tensor imaging metrics of brain microstructure changes following magnetic resonance guided focused ultrasound (MRgFUS) ablation of the ventral intermediate nucleus of the thalamus for the treatment of tremor in order to explore the mechanisms of tremor reduction post-MRgFUS. Tractography was performed on pre-treatment images to identify the portion of the dentato-rubro-thalamo-cortical tract (DRTT) intersecting the MRgFUS thalamotomy lesions in 17 essential tremor patients. The resulting tract was divided into regions of interest (ROI), which were then analyzed on pre-, one day post-, and three months post-treatment scans. Fractional anisotropy (FA), and mean, axial, and radial diffusivity (MD, AD, and RD) were computed in each ROI at each time point. At both one day and three months post-treatment, we observed decreased FA and increased MD and RD in the section of the treated tract between the lesion and cortex. At three months post-treatment, we additionally observed increased AD in the section between the lesion and cortex, and decreased FA in the section between the dentate nucleus and the decussation of the superior cerebellar peduncles. Diffusion changes at one day post-treatment may reflect local, acute effects such as inflammation and edema, as opposed to chronic degenerative processes such as axonal degeneration and myelin loss that would be expected at later time points. No significant correlations were detected between diffusion measures and clinical effects, suggesting that microstructural changes in the treated portion of the DRTT alone do not fully explain tremor reduction and motivating additional research using higher spatial resolution diffusion imaging and multimodal approaches such as integrating diffusion and functional magnetic resonance imaging data. Our individualized approach, in which patient-specific lesions are incorporated into the tractography analysis, provided novel insight into both immediate and longer term MRgFUS-related microstructural brain changes.
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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 | 0.000 |
| 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) | 0.001 | 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".