Volumetric MRI‐guided high‐intensity focused ultrasound for noninvasive, in vivo determination of tissue thermal conductivity: Initial experience in a pig model
Bibliographic record
Abstract
PURPOSE: To estimate the local thermal conductivity of porcine thigh muscle at temperatures required for magnetic resonance imaging (MRI)-guided high-intensity focused ultrasound (MRgHIFU) surgery (60-90°C). MATERIALS AND METHODS: Using MRgHIFU, we performed 40 volumetric ablations in the thigh muscles of four pigs. Thirty-five of the sonications were successful. We used MRI to monitor the resulting temperature increase. We then determined local thermal conductivity by analyzing the spatiotemporal spread of temperature during the cooling period. RESULTS: The thermal conductivity of MRgHIFU-treated porcine thigh muscle fell within a narrow range (0.52 ± 0.05 W/[m*K]), which is within the range reported for porcine thigh muscle at temperatures of <40°C (0.52 to 0.62 W/[m*K]). Thus, there was little change in the thermal conductivity of porcine thigh muscle at temperatures required for MRgHIFU surgery compared to lower temperatures. CONCLUSION: Our MRgHIFU-based approach allowed us to estimate, with good reproducibility, the local thermal conductivity of in vivo deep tissue in real time at temperatures of 60°C to 90°C. Therefore, our method provides a valuable tool for quantifying the influence of thermal conductivity on temperature distribution in tissues and for optimizing thermal dose delivery during thermal ablation with clinical MRgHIFU.
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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 | 0.001 |
| 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".