An update on the role of focused ultrasound in neuro-oncology
Bibliographic record
Abstract
PURPOSE OF REVIEW: Brain tumor treatment presents challenges for patients and clinicians, with prognosis for many of the most common brain tumors being poor. Focused ultrasound (FUS) can be deployed in several ways to circumvent these challenges, including the need to penetrate the blood-brain barrier and spare healthy brain tissue. This article reviews current FUS applications within neuro-oncology, emphasizing ongoing or recently completed clinical trials. RECENT FINDINGS: Most clinical interest in FUS for neuro-oncology remains focused on exploring BBB disruption to enhance the delivery of standard-of-care therapeutics. More recently, the application of FUS for radiosensitization, liquid biopsy, and sonodynamic therapy is garnering increased clinical attention to assist in tumor ablation, early detection, and phenotypic diagnosis. Preclinical studies show encouraging data for the immunomodulatory effects of FUS, but these findings have yet to be tested clinically. SUMMARY: FUS is a burgeoning area of neuro-oncology research. Data from several forthcoming large clinical trials should help clarify its role in neuro-oncology care.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".