A phase I study of MR-HIFU hyperthermia (HT) with radiation (RT) and chemotherapy (CT) for recurrent rectal cancer.
Bibliographic record
Abstract
78 Background: HT may improve cancer control and quality of life by sensitizing tumors to RT and CT. Inoperable recurrent rectal cancer has marginal outcomes with current retreatment regimens. We report the results from a first-in-human phase I study of MR-HIFU hyperthermia combined with RT and CT for recurrent rectal cancer. Methods: This ethics-approved study enrolled 6 patients fit for re-irradiation and chemotherapy; and with a MRI-visible and HIFU-accessible lesion. Patients received 30.6 Gy (17 fractions) and daily oral capecitabine, plus MR-HIFU HT immediately before RT on days 1, 8, and 15. Primary objectives were safety (acute toxicity) and treatment feasibility. Secondary objectives included late toxicity, pain palliation, quality of life, and radiologic response. HT was delivered with the Sonalleve MR-HIFU system on a 3T MRI. MR-based feedback control parameters were prescribed to achieve a mean temperature of 42.5°C in an 18 mm diameter target region for 30 minutes without exceeding 45°C. Results: One patient withdrew after completing 1/3 HT sessions due to scheduling and sedation difficulties. Five patients completed HT, RT and CT. There were no intraoperative complications, no adverse events or unintended tissue damage attributable to HT, RT, or CT. Table shows the best single continuous HT and mean temperatures (T90, T10), cumulative time in range (TIR), cumulative number of equivalent minutes at 43 o C(CEM43) and day 90 imaging response. Sonication and MRI suite times were 36±13 and 226±78min. Conclusions: MR-HIFU HT was safely delivered in patients with recurrent rectal cancer. Treatment planning and patient set-up times decreased while beam-on time increased with experience. MR-HIFU HT combined with RT and CT appears feasible for primary tumours. Clinical trial information: NCT02528175. [Table: see text]
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".