Contribution of combined intraoperative electrophysiological investigation with 3-T intraoperative MRI for awake cerebral glioma surgery: comprehensive review of the clinical implications and radiological outcomes
Bibliographic record
Abstract
OBJECTIVE: This study aimed to assess the clinical efficiency of combined awake craniotomy with 3-T intraoperative MRI (iMRI)-guided resection of gliomas adjacent to eloquent cortex performed at a single center. It also sought to explore the contribution of iMRI to surgeons' learning process of maximal safe resection of gliomas. METHODS: All patients who underwent an awake craniotomy and iMRI for resection of eloquent area glioma during the 53 months between January 2011 and June 2015 were included. The cases were analyzed for short- and long-term neurological outcome, progression-free survival (PFS), overall survival (OS), and extent of resection (EOR). The learning curve was assessed after dividing the cohort into Group A (first 27 months) and Group B (last 26 months). Statistical analyses included univariate logistic regression analysis on clinical and radiological variables. Kaplan-Meier and Cox regression models were used for further analysis of OS and PFS. A p value < 0.05 was considered statistically significant. RESULTS: One hundred six patients were included in the study. Over an average follow-up period of 24.8 months, short- and long-term worsening of the neurological function was noted in 48 (46.2%) and 9 (8.7%) cases, respectively. The median and mean EOR were 100% and 92%, respectively, and complete radiographic resection was achieved in 64 (60.4%) patients. The rate of gross-total resection (GTR) in the patients with low-grade glioma (89.06% ± 19.6%) was significantly lower than that in patients with high-grade glioma (96.4% ± 9.1%) (p = 0.026). Thirty (28.3%) patients underwent further resection after initial iMRI scanning, with a 10.1% increase of the mean EOR. Multivariate Cox proportional hazards modeling demonstrated that the final EOR was a significant predictor of PFS (HR 0.225, 95% CI 0.070-0.723, p = 0.012). For patients with high-grade glioma, the GTR (p = 0.033), the presence of short-term motor deficit (p = 0.027), and the WHO grade (p = 0.005) were independent prognostic factors of OS. Performing further resection after the iMRI (p = 0.083) and achieving GTR (p = 0.05) demonstrated a PFS benefit trend for the patients affected by a low-grade glioma. Over time, the rate of performing further resection after an iMRI decreased by 26.1% (p = 0.005). A nonsignificant decrease in the rate of short-term (p = 0.101) and long-term (p = 0.132) neurological deficits was equally noted. CONCLUSIONS: Combined awake craniotomy and iMRI is a safe and efficient technique allowing maximal safe resection of eloquent area gliomas with possible subsequent OS and PFS benefits. Although there is a learning curve for applying this technique, it can also improve the surgeon's ability in eloquent glioma surgery.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".