Radiation enhancement using focussed ultrasound-stimulated microbubbles for head and neck cancer: A phase 1 clinical trial
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Preclinical research demonstrated that the exposure of microbubbles (intravascular gas microspheres) to focussed ultrasound within the targeted tumour upregulates pro-apoptotic pathways and enhances radiation-induced tumour cell death. This study aimed to assess the safety and efficacy of magnetic resonance (MR)-guided focussed ultrasound-stimulated microbubbles (MRgFUS-MB) for head and neck cancers (HN). MATERIALS AND METHODS: This prospective phase 1 clinical trial included patients with newly diagnosed or recurrent HN cancer (except nasopharynx malignancies) for whom locoregional radiotherapy with radical- or palliative-intent as deemed appropriate. Patients with contraindications for microbubble administration or contrast-enhanced MR were excluded. MR-coupled focussed ultrasound sonicated intravenously administered microbubbles within the MR-guided target volume. Patients receiving 5-10 and 33-35 radiation fractions were planned for 2 and 3 MRgFUS-MB treatments, respectively. Primary endpoint was toxicity per CTCAEv5.0. Secondary endpoint was tumour response at 3 months per RECIST 1.1 criteria. RESULTS: Twelve patients were enrolled between Jun/2020 and Nov/2023, but 1 withdrew consent. Eleven patients were included in safety analysis. Median follow-up was 7 months (range, 0.3-38). Most patients had oropharyngeal cancer (55 %) and received 20-30 Gy/5-10 fractions (63 %). No systemic toxicity or MRgFUS-MB-related adverse events occurred. The most severe acute adverse events were radiation-related grade 3 toxicities in 6 patients (55 %; dermatitis in 3, mucositis in 1, dysphagia in 6). No radiation necrosis or grade 4/5 toxicities were reported. 8 patients were included in the 3-month tumour response assessment: 4 had partial response (50 %), 3 had complete response (37.5 %), and 1 had progressive disease (12.5 %). CONCLUSIONS: MRgFUS-MB treatment was safe and associated with high rates of tumour response at 3 months.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".