SURG-36. IMPACT OF MULTIMODALITY MONITORING USING DIRECT ELECTRICAL STIMULATION TO DETERMINE CORTICOSPINAL TRACT SHIFT AND INTEGRITY IN THE iMRI suite
Bibliographic record
Abstract
Preserving the integrity of the corticospinal tract (CST) while maximizing the extent of tumor resection is one of the key principles of brain tumor surgery to prevent new neurological deficits. The goal of this project was to determine the impact of the use of peri-operative DTI fiber-tracking protocols for localization of the CSTs, in conjunction with intraoperative direct electrical stimulation (DES) on patient neurological outcomes. Fifty-three patients underwent resection of tumors adjacent to the motor gyrus and the underlying CST. Preoperative and postoperative DTI mapping, intraoperative cortical and subcortical direct electrical stimulation (DES) were performed in all patients. Eighteen patients (34%) had a re-resection after the first intraoperative scan. In the immediate postoperative period, 55% of patients developed a new neurological deficit. At the three-month follow up, however, only 6 patients (11%) had a persistent neurological deficit that was worse than the preoperative state. The proximity of the tumor to the CSTs was determined from preoperative studies. Tumor location further than 15 mm from CSTs correlated with better neurological outcomes at one and three months postoperatively (p=0.001 and 0.007 respectively) despite achieving a similar degree of resection (p=0.61). The current of subcortical DES performed with monopolar probe showed a linear correlation with the distance to the CST (R=1.10+/-0.83). Intraoperative imaging demonstrated that CST shifts on average (4.4+/-3.2) mm, but the direction of the shift is unpredictable. Resection of tumor tissue closer than 5 mm to the CST is associated with increased morbidity. In summary, a combination of DTI imaging, subcortical DES, and continuous motor evoked potential (CMEP) monitoring can be used in the iMRI suite to maximize tumor resection and preserve patient neurological function.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".