3T MRI evaluation of the accuracy of atlas-based subthalamic nucleus identification
Bibliographic record
Abstract
Modulation of the activity of the subthalamic nucleus (STN) using deep brain stimulation (DBS) in patients with advanced Parkinson's disease is the most common procedure performed today by functional neurosurgeons. The STN contours cannot be entirely identified on common 1.5 T images; in particular, the ventromedial border of the STN often blends with the substantia nigra. 3 T magnetic resonance imaging (MRI) provides better resolution and can improve the identification of the STN borders. In this work, we have directly identified the STN using 3 T MR imaging to validate the accuracy of a computer-aided atlas-based procedure for automatic STN identification. Coordinates of the STN were obtained from the Talairach and Tournoux atlas and transformed into the coordinates of the Montreal Neurological Institute (MNI) standard brain volume, creating a mask representation of the STN. 3 T volumetric T1 and T2 weighted (T1w and T2w, respectively) acquisitions were obtained for ten patients. The MNI standard brain volume was registered onto each patient MRI, using a new approach based on global affine, region-of-interest affine, and local nonrigid registrations. The estimated deformation field was then applied to the STN atlas-based mask, providing its location on the patient MRI. The entire procedure required on average about 20 min. Because STN is easily identifiable on 3 T T2w-MRIs, it was manually delineated; the coordinates of the center of mass of the manually and automatically identified structures were compared. Additionally, volumetric overlapping indices were calculated and the spatial relationship between the midcommissural point and the STN center of mass was investigated. All indices indicated, on average, good agreement between manually and automatically identified structures; displacement of the centers of mass of the manually and automatically identified structures was less than or equal to 2.35 mm, and more than 80% of the manually identified volume was covered by the automatic localization, on average. Bland-Altman analysis indicated that the automatic STN identification was within the limits of agreement with the manual localization on 3 T MRIs. Automatic atlas-based STN localization provides an accurate and user-friendly tool and can enhance target identification when 1.5 T scanners with limited capability to identify the STN boundaries are used.
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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 | 0.001 |
| 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".