Magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) hyperthermia for primary rectal cancer: A virtual feasibility analysis.
Bibliographic record
Abstract
77 Background: MR-HIFU Hyperthermia (HT) is a non-invasive treatment modality with real-time thermometry that ensures accurate and precise heating of a target with minimal effect on adjacent tissue. This energy deposition within a tumour can produce local bioeffects resulting in thermal chemo- and radiosensitization. MR-HIFU has been shown to be safe and feasible in a companion phase I study for recurrent rectal cancer. The purpose of this study is to determine the feasibility of MR-HIFU in treating primary rectal tumours. Methods: With ethics approval, the anatomic characteristics and surrounding structures of rectal tumours diagnosed at Sunnybrook from 2014-2019 were retrospectively analyzed. Three orthogonal views of MR images were used to determine the potential ultrasound (US) beam path and organs at risk (OAR). In part 2 of the study, the gross tumour volume was delineated for 30 rectal tumours (10 low, mid &high). Image datasets were imported into the Sonalleve MR-HIFU workstation for virtual treatment simulation and planning to determine tumour targetability, coverage, optimal patient set-up, and transducer positioning. Results: Of the 105 tumours analyzed, 36, 52, and 17 were low, mid, and high, respectively. The average width of the acoustic window (sciatic notch) for the US beam path was 5.8 ± 1.4cm, average tumour length was 5.24 ± 2.0cm, and average beam path (skin to tumour edge) was 7.3 ± 1.9cm. Eighty one percent of tumours were ≤ 0.3cm from an OAR. Of the 24 virtually simulated tumours to date, 6/8 lower, 6/8 mid, and 1/8 upper rectal tumours were targetable by MR-HIFU. Conclusions: This is the first virtual analysis to evaluate MR-HIFU HT targetability in primary rectal cancer. Results from this study will support MR-HIFU HT as an option to enhance the treatment of primary rectal cancer. Acknowledgments: This study has been funded by the Canadian Cancer Society. Patient & tumour characteristics. [Table: see text]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".