Intraoperative magnetic resonance imaging–augmented transoral resection of axial disease
Bibliographic record
Abstract
OBJECT: Because transoral decompression of the cervicomedullary junction is compromised by a narrow surgical corridor, the adequacy of decompression/resection may be difficult to determine. This is problematic as spinal hardware may obscure postoperative radiological assessment, or the patient may require reoperation. The authors report three patients in whom high-field intraoperative magnetic resonance (MR) images were acquired at various stages during the transoral resection of C-2 lesions causing craniocervical junction compression. METHODS: In all three patients the lesions involved the cervicomedullary junction: one case each of plasmacytoma and metastatic breast carcinoma involving the odontoid process and C-2 vertebral body, and one case of basilar invagination with a Chiari type I malformation. All three patients presented with progressive myelopathy. Surgery-planning MR imaging studies, performed after the induction of anesthesia, demonstrated the lesion and its relationship to the planned surgical corridor. Transoral exposure was achieved through placement of a Crockard retractor system. In one case the soft palate was divided. Interdissection MR imaging revealed that adequate decompression had been achieved in all cases. In the two patients with carcinoma, posterior instrumentation was placed to achieve spinal stabilization. Planned suboccipital decompression and fixation was averted in the third case because MR imaging demonstrated that excellent decompression had been achieved. CONCLUSIONS: Intraoperatively acquired MR images were instrumental in determining the adequacy of surgical decompression. In one patient the MR images changed the planned surgical procedure. Importantly, the acquisition of intraoperative MR images did not adversely affect operative time or neurosurgical techniques, including the instrumentation procedure.
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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) | 0.001 | 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".