Deep Brain Stimulator Electrodes Used for Lesioning: Proof of Principle
Bibliographic record
Abstract
OBJECTIVE: Patients with chronically implanted deep brain stimulator (DBS) electrodes can encounter complications requiring hardware removal. We assessed the safety and efficacy of using implanted DBS electrodes to create a therapeutic lesion before their removal. METHODS: Revision or removal of the DBS electrodes was required in two patients who had previously undergone DBS implantation. We conducted a series of in vitro experiments to confirm that the DBS electrodes could be used to generate radiofrequency lesions and to assess the relationship between radiofrequency parameters and lesion size. With this information, and with the approval of the hospital ethical review board, implanted electrodes were used to create incremental radiofrequency lesions in the thalamus in one patient and in the subthalamic nucleus in another. The procedures were performed under local anesthesia with contiguous contacts of the DBS lead connected to the active and reference sites of the RF generator to create a bipolar lesion. RESULTS: A 51-year-old man with essential tremor and a thalamic DBS required repeated battery changes secondary to tolerance and high voltage demands. Rather than replacing the battery, a radiofrequency thalamotomy was performed by using the existing left DBS electrode. At the 6-month follow-up examination, successful lesioning provided near complete tremor control. A second patient, a 50-year-old man with Parkinson's disease who had undergone bilateral subthalamic deep brain stimulation, developed skin erosion over the DBS hardware. A subthalamic nucleus lesion was made through the right DBS electrode. Lesion position and size were confirmed with magnetic resonance imaging. CONCLUSION: Lesions can be made through chronically implanted DBS electrodes in a safe, graded fashion and can produce therapeutic benefit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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".