Three-tesla magnetic resonance imaging of the ventrolateral thalamus: a correlative anatomical description
Bibliographic record
Abstract
OBJECT: Surgery for tremor targets the ventrolateral nuclei of the thalamus. An initial radiological estimation of this target can be further refined through intraoperative physiological confirmation. Direct visualization of these nuclei has not yet been described. The improved signal-to-noise ratio associated with 3-tesla (3T) magnetic resonance (MR) imaging makes increased spatial resolution possible, which may aid in the identification of subtle morphological features. This study was conducted to describe the anatomy of the nuclei and fiber projections within the ventral thalamus by using 3T MR imaging. METHODS: Using a commercially available 3T MR unit, the authors obtained images of a formalin-fixed, paraffin-embedded brain. Slices with a 2-mm thickness and 0.2-mm gap were obtained parallel to the anterior commissure-posterior commissure (AC-PC) line. The brain was then sectioned through the cerebral hemispheres to obtain tissue slices encompassing the same levels. Adjacent 10-microm paraffin sections from the middle of each level were stained with Luxol fast blue and cresyl violet. The MR image and histological sections at the level of the AC-PC line were then compared in detail. In a separate study, the human thalamus was scanned in vivo using 3T and 1.5T MR imaging for anatomical comparison. CONCLUSIONS: The anatomy of the nuclei and fiber projections within the ventrolateral thalamus in humans can be described using 3T MR imaging. The findings were reproducible in vivo with 3T but not 1.5T MR imaging. Additional studies are needed to confirm the accuracy of this observation for clinical purposes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".