Subthalamic Nucleus Visualization on Routine Clinical Preoperative MRI Scans: A Retrospective Study of Clinical and Image Characteristics Predicting Its Visualization
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The visualization of the subthalamic nucleus (STN) on magnetic resonance imaging (MRI) is variable. Studies of the contribution of patient-related factors and intrinsic brain volumetrics to STN visualization have not been reported previously. OBJECTIVE: To assess the visualization of the STN during deep brain stimulation (DBS) surgery in a clinical setting. METHODS: Eighty-two patients undergoing pre-operative MRI to plan for STN DBS for Parkinson disease were retrospectively studied. The visualization of the STN and its borders was assessed and scored by 3 independent observers using a 4-point ordinal scale (from 0 = not seen to 3 = excellent visualization). This measure was then correlated with the patients' clinical information and brain volumes. RESULTS: The mean STN visualization scores were 1.68 and 1.63 for the right and left STN, respectively, with a good interobserver reliability (intraclass correlation coefficient: 0.744). Older age and decreased white matter volume were negatively correlated with STN visualization (p < 0.05). CONCLUSION: STN visualization is only fair to good on routine MRI with good concordance of interindividual rating. Advancing age and decreased white matter are associated with poor visualization of the STN. Knowledge about factors contributing to poor visualization of the STN could alert a surgeon to modify the imaging strategy to optimize surgical targeting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it