Simulating thermal effects of <scp>MR</scp>‐guided focused ultrasound in cortical bone and its surrounding tissue
Bibliographic record
Abstract
PURPOSE: Magnetic resonance-guided focused ultrasound (MRgFUS) is emerging as a treatment alternative for osteoid osteoma and painful bone metastases. This study describes a new simulation platform that predicts the distribution of heat generated by MRgFUS when applied to bone tissue. METHODS: Calculation of the temperature distribution was performed using two mathematical models. The first determined the propagation and absorption of acoustic energy through each medium, and this was performed using a multilayered approximation of the Rayleigh integral method. The ultrasound energy distribution derived from these equations could then be converted to heat energy, and the second mathematical model would then use the heat generated to determine the final temperature distribution using a finite-difference time-domain application of Pennes' bio-heat transfer equation. Anatomical surface geometry was generated using a modified version of a mesh-based semiautomatic segmentation algorithm, and both the acoustic and thermodynamic models were calculated using a parallelized algorithm running on a graphics processing unit (GPU) to greatly accelerate computation time. A series of seven porcine experiments were performed to validate the model, comparing simulated temperatures to MR thermometry and assessing spatial, temporal, and maximum temperature accuracy in the soft tissue. RESULTS: voxels in under 30 s for a simulated 20 s of heating and 40 s of cooling, with a maximum time per calculated voxel of less than 0.3 μs. Accuracy was assessed by comparing the soft tissue thermometry to the simulation in the soft tissue adjacent to bone using four metrics. The maximum temperature difference between the simulation and thermometry in a region of interest around the bone was measured to be 5.43 ± 3.51°C average absolute difference and a percentage difference of 16.7%. The difference in heating location resulted in a total root-mean-square error of 4.21 ± 1.43 mm. The total size of the ablated tissue calculated from the thermal dose approximation in the simulation was, on average, 67.6% smaller than measured from the thermometry. The cooldown was much faster in the simulation, where it decreased by 14.22 ± 4.10°C more than the thermometry in 40 s after sonication ended. CONCLUSIONS: The use of a Rayleigh-based acoustic model combined with a discretized bio-heat transfer model provided a rapid three-dimensional calculation of the temperature distribution through bone and soft tissue during MRgFUS application, and the parallelized GPU algorithm provided the computational speed that would be necessary for an intraoperative treatment planning software platform.
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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 | 0.002 |
| 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".