Investigation of power and frequency for 3D conformal MRI-controlled transurethral ultrasound therapy with a dual frequency multi-element transducer
Bibliographic record
Abstract
Transurethral ultrasound therapy uses real-time magnetic resonance (MR) temperature feedback to enable the 3D control of thermal therapy accurately in a region within the prostate. Previous canine studies showed the feasibility of this method in vivo. The aim of this study was to reduce the procedure time, while maintaining targeting accuracy, by investigating new combinations of treatment parameters. Simulations and validation experiments in gel phantoms were used, with a collection of nine 3D realistic target prostate boundaries obtained from previous preclinical studies, where multi-slice MR images were acquired with the transurethral device in place. Acoustic power and rotation rate were varied based on temperature feedback at the prostate boundary. Maximum acoustic power and rotation rate were optimised interdependently, as a function of prostate radius and transducer operating frequency. The concept of dual frequency transducers was studied, using the fundamental frequency or the third harmonic component depending on the prostate radius. Numerical modelling enabled assessment of the effects of several acoustic parameters on treatment outcomes. The range of treatable prostate radii extended with increasing power, and tended to narrow with decreasing frequency. Reducing the frequency from 8 MHz to 4 MHz or increasing the surface acoustic power from 10 to 20 W/cm(2) led to treatment times shorter by up to 50% under appropriate conditions. A dual frequency configuration of 4/12 MHz with 20 W/cm(2) ultrasound intensity exposure can treat entire prostates up to 40 cm(3) in volume within 30 min. The interdependence between power and frequency may, however, require integrating multi-parametric functions in the controller for future optimisations.
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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".