Intraoperative Magnetic Resonance Imaging for Skull Base Surgery
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Skull base surgery has evolved over the past several decades. Major improvements in the imaging of skull base pathology led to better target localization and better surgical planning. The objectives of this study were to assess the use of intraoperative magnetic resonance (MR) imaging in the management of a series of patients with skull base pathology. We hypothesized that high-quality intraoperative MR imaging would have an impact on surgery in this patient group. STUDY DESIGN: Prospective, non-randomized, cohort study. METHODS: Thirty-one patients with skull base lesions underwent surgery in a 1.5-Tesla intraoperative MR suite. The concepts of a moving magnet, high magnetic field strength, and radiofrequency coil design are presented. RESULTS: Eleven of 31 patients had the course of surgery significantly altered by the information acquired from the images obtained during surgery. CONCLUSIONS: Intraoperative MR imaging is a valuable adjunct to skull base surgery. One third of patients had altered surgery as a result of this adjunct. Intraoperative MR imaging is of particular value in the treatment of pituitary adenomas and benign skull base tumors.
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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 | 0.000 |
| 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".