Catheter-based polarimetric imaging to complement MRI for deep brain stimulation neurosurgery
Bibliographic record
Abstract
Significance: Deep brain stimulation (DBS) is an established treatment for movement disorders and other neurological conditions. Accurate localization of small deep brain nuclei, such as the subthalamic nucleus (STN) and internal pallidum (GPi), is crucial for successful DBS outcomes. However, magnetic resonance imaging (MRI), commonly used for DBS planning, lacks the resolution and contrast needed to directly delineate these target structures. Aim: We aim to explore the potential of catheter-based polarization-sensitive optical coherence tomography (PS-OCT) as a complementary imaging tool for high-resolution visualization of tissue surrounding the DBS insertion trajectory. Approach: We simulated DBS implantation surgery at three targets in a post-mortem nonhuman primate head. PS-OCT, using advanced reconstruction algorithms for absolute depth-resolved birefringence, was compared with MRI for its ability to visualize and differentiate structural details. Results: PS-OCT provided more detailed and accurate structural information than MRI while maintaining consistency with MRI results. Its compact form factor and imaging paradigm integrate seamlessly into the surgical workflow, offering new insights for intraoperative decision-making. Conclusions: studies.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".