Editorial: Advances in surgical approaches for the treatment of glioma
Bibliographic record
Abstract
Advances in surgical approaches for the treatment of glioma Presently, maximal-safe resection is still the primary pursuit for surgically treating glioma.Accordingly, there are a variety of novel techniques being developed.Therefore, this Research Topic aimed to summarize advances in glioma surgery along with emerging auxiliary techniques.On the whole, there are four aspects to consider: balancing between the extent of resection and preserving neurological function, shortening intraoperative examination time while improving the accuracy of detection, minimizing surgical incision while achieving total resection, and utilizing in vivo histological testing just before completion of resection while guaranteeing patient safety. Clinical studiesIntraoperative direct electrical stimulation (DES) can directly identify neural networks crucial for brain function and remains the gold standard for eloquent cortex localization (1, 2).Although there remains some debate (3, 4), awake brain mapping plus DES is generally associated with more extensive resection, better overall survival, and fewer severe persistent neurological deficits compared with resection under general anesthesia (5-8).Wang et al. presented their experience in awake craniotomy with intraoperative DES mapping for gliomas invading eloquent areas. With a similar surgical strategy, Yao et al. reviewed their single-center experience of treating diffuse lower grade glioma (DLGG) in the central lobe (including precentral and postcentral gyri and paracentral lobule). Both studies reported favorable results. Moreover, Wang et al. established a high sensitivity of the Montreal Cognitive Assessment (MoCA), a relatively brief screening tool for assessment of this population's cognitive impairment.Compared with awake surgery, surgery under general anesthesia is less time-consuming, with lower intraoperative risk (9, 10).Cui et al. reported their experience of removing glioma under general anesthesia assisted by intraoperative multimodal techniques (combined use of neuronavigation, iMRI, with/without DES/neuromonitoring).The large sample size (nearly 500 patients) was the strength of this study.The researchers confirmed that the application of Frontiers in Oncology frontiersin.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.021 | 0.018 |
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".