Suitability of a tumour-mimicking material for the evaluation of high-intensity focused ultrasound ablation under magnetic resonance guidance
Bibliographic record
Abstract
This study tests the suitability of a tumour-mimic for targeting magnetic resonance (MR)-guided high-intensity focused ultrasound (HIFU). An agarose-based tumour-mimic was injected as a warm solution that polymerized in tissue. Thermal characteristics and acoustic absorption of the mimic were observed within the values reported for tissues. The relaxation times at 3T were 1679 ± 15 ms for T1 and 41 ± 1 ms for T2. The mimic was clearly visible on in vivo images. With lower contrast the tumour-mimic was visible on T2-weighted images, where it was possible to detect the ablated tissue surrounding the mimic after sonications. HIFU sonications were performed to induce thermal ablation on and around the mimic using a Sonalleve system (Philips). MR thermometry maps were performed during HIFU. The average temperature when the sonication was done at the tumour-mimic was 67.6 ± 8.0 °C in vitro and 67.6 ± 5.0 °C in vivo. The average temperature for sonications at tissues was 68.4 ± 8.7 °C in vitro (liver) and 66.0 ± 2.6 °C in vivo (muscle), with no significant difference between tissue and tumour-mimic (p > 0.05). The tumour-mimic behaviour when using MR-guided HIFU was similar to tissues, showing that this mimic can be used as an alternative to tumour models for validating MR-guided HIFU devices targeting.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".