The Utility of Superselective Rotational Angiography for Frameless Stereotactic Navigation During Craniotomy for Micro-Arteriovenous Malformation
Bibliographic record
Abstract
BACKGROUND: Micro-arteriovenous malformations (AVMs) can present challenges to neurosurgeons with respect to localization during resection. We sought to describe a novel method that merges super-selective 3-dimensional angiographic images with magnetic resonance imaging (MRI) sequences to facilitate frameless stereotaxic navigation during AVM surgery. METHODS: A retrospective analysis was performed comprising cases that employed merging of angiographic and MRI images for navigation purposes. Baseline clinical and imaging features were recorded. The technique and operative experiences were analyzed descriptively and presented alongside detailed illustrative cases. RESULTS: During the review period, 11 cases were identified where this technique was employed. Successful image acquisition and merging was possible in all cases. Complete obliteration of the target pathology was achieved in all cases. Precise localization of the micro-AVMs minimized dissection in eloquent cortex. CONCLUSIONS: Superselective 3-dimensional angiographic images merged to baseline MRI sequences facilitates planning and navigation during surgery for micro-AVMs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".