3D conformal MRI-controlled transurethral ultrasound prostate therapy: validation of numerical simulations and demonstration in tissue-mimicking gel phantoms
Bibliographic record
Abstract
MRI-controlled transurethral ultrasound therapy uses a linear array of transducer elements and active temperature feedback to create volumes of thermal coagulation shaped to predefined prostate geometries in 3D. The specific aims of this work were to demonstrate the accuracy and repeatability of producing large volumes of thermal coagulation (>10 cc) that conform to 3D human prostate shapes in a tissue-mimicking gel phantom, and to evaluate quantitatively the accuracy with which numerical simulations predict these 3D heating volumes under carefully controlled conditions. Eleven conformal 3D experiments were performed in a tissue-mimicking phantom within a 1.5T MR imager to obtain non-invasive temperature measurements during heating. Temperature feedback was used to control the rotation rate and ultrasound power of transurethral devices with up to five 3.5 × 5 mm active transducer elements. Heating patterns shaped to human prostate geometries were generated using devices operating at 4.7 or 8.0 MHz with surface acoustic intensities of up to 10 W cm(-2). Simulations were informed by transducer surface velocity measurements acquired with a scanning laser vibrometer enabling improved calculations of the acoustic pressure distribution in a gel phantom. Temperature dynamics were determined according to a FDTD solution to Pennes' BHTE. The 3D heating patterns produced in vitro were shaped very accurately to the prostate target volumes, within the spatial resolution of the MRI thermometry images. The volume of the treatment difference falling outside ± 1 mm of the target boundary was, on average, 0.21 cc or 1.5% of the prostate volume. The numerical simulations predicted the extent and shape of the coagulation boundary produced in gel to within (mean ± stdev [min, max]): 0.5 ± 0.4 [-1.0, 2.1] and -0.05 ± 0.4 [-1.2, 1.4] mm for the treatments at 4.7 and 8.0 MHz, respectively. The temperatures across all MRI thermometry images were predicted within -0.3 ± 1.6 °C and 0.1 ± 0.6 °C, inside and outside the prostate respectively, and the treatment time to within 6.8 min. The simulations also showed excellent agreement in regions of sharp temperature gradients near the transurethral and endorectal cooling devices. Conformal 3D volumes of thermal coagulation can be precisely matched to prostate shapes with transurethral ultrasound devices and active MRI temperature feedback. The accuracy of numerical simulations for MRI-controlled transurethral ultrasound prostate therapy was validated experimentally, reinforcing their utility as an effective treatment planning tool.
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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".