Imaging alone versus microelectrode recording–guided targeting of the STN in patients with Parkinson’s disease
Bibliographic record
Abstract
OBJECTIVE: The clinical results of deep brain stimulation (DBS) of the subthalamic nucleus (STN) are highly dependent on accurate targeting and target implantation. Several targeting tactics are in current use, including image-only and/or electrophysiologically guided approaches using microelectrode recordings (MERs). The purpose of the present study was to make an appraisal of imaging only-based versus imaging with the addition of intraoperative MER-guided STN electrode targeting. METHODS: The authors evaluated 100 consecutive patients undergoing STN DBS. The position of the STN target was estimated from preoperative MR images (direct target) or in relation to the position of the anterior and posterior commissures (indirect target). MERs were obtained for each trajectory. The authors tracked which targets were adjusted intraoperatively as a consequence of MER data. The final placement of 182 total STN electrodes was validated by intraoperative macrostimulation through the implanted DBS electrodes. The authors compared the image-based direct, indirect, MER-guided target adjustments and the final coordinates of the electrodes as seen on postoperative MRI. RESULTS: In approximately 80% of the trajectories, there was a good correspondence between the imaging-based and the MER-guided localization of the STN target. In approximately 20% of image-based targeting trajectories, however, the electrophysiological data revealed that the trajectory was suboptimal, missing the important anatomical structures to a significant extent. The greatest mismatch was in the superior-inferior axis, but this had little impact because it could be corrected without changing trajectories. Of more concern were mismatches of 2 mm or more in the mediolateral (x) or anteroposterior (y) planes, discrepancies that necessitated a new targeting trajectory to correct for the mis-targeting. The incidence of mis-targetting requiring a second MER trajectory on the first and second sides was similar (18% and 22%). CONCLUSIONS: According to the present analysis, approximately 80% of electrodes were appropriately targeted using imaging alone. In the other 20%, imaging alone led to suboptimal targeting that could be corrected by a trajectory course correction guided by the acquired MER data. The authors' results suggest that preoperative imaging is insufficient to obtain optimal results in all patients undergoing STN DBS.
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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".