Magnetic Resonance–Guided High-Intensity-Focused Ultrasound for Palliation of Painful Skeletal Metastases: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Bone is one of the most common sites of metastases, with bone metastases-related pain representing a significant source of morbidity among patients with cancer. Magnetic resonance-guided focused ultrasound is a noninvasive, outpatient modality with the potential for treating painful bone metastases. The aim of this study is to report our initial experience with magnetic resonance-guided focused ultrasound in the treatment of bone metastases and our preliminary analysis of urinary cytokine levels after therapy. METHODS: This was a single-center pilot study of 10 patients with metastatic cancer to investigate the feasibility of magnetic resonance-guided focused ultrasound for primary pain control in device-accessible skeletal metastases. Treatments were performed on a clinical magnetic resonance-guided focused ultrasound system using a volumetric ablation technique. Primary efficacy was assessed using Brief Pain Inventory scores and morphine equivalent daily dose intake at 3 time points: before, day 14, and day 30 after the magnetic resonance-guided focused ultrasound treatment. Urine cytokines were measured 3 days before treatment and 2 days after the treatment. RESULTS: Of the 10 patients, 8 were followed up 14 days and 6 were followed up 30 days after the treatment. At day 14, 3 patients (37.5%) exhibited partial pain response and 4 patients (50%) exhibited an indeterminate response, and at day 30 after the treatment, 5 patients (83%) exhibited partial pain response. No treatment-related adverse events were recorded. Of the urine cytokines measured, only Transforming growth factor alpha (TGFα) demonstrated an overall decrease, with a trend toward statistical significance ( P = .078). CONCLUSION: Our study corroborates magnetic resonance-guided focused ultrasound as a feasible and safe modality as a primary, palliative treatment for painful bone metastases and contributes to the limited body of literature using magnetic resonance-guided focused ultrasound for this clinical indication.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".