High Intensity Focused Ultrasound Optimal Device Design for Targeted Prostate Cancer Treatment: A Numerical Study
Bibliographic record
Abstract
A parametric study was performed to design a device capable of treating small targeted regions within the prostate using high intensity focused ultrasound, while sparing the surrounding organs and minimizing the number of elements. The optimal focal length (L), operating frequency (f), element size (a) and central opening radius for lodging an imaging probe (r) of a device that would safely treat tissue within the prostate were obtained. Images from the Visible Human Project were used to determine simulated organ sizes and treatment locations. Elliptical tumors were placed throughout the simulated prostate and their lateral and axial limits were selected as test locations. Using graphics processors, the acoustic field and Bio-Heat Transfer Equation were solved to calculate the heating produced during a simulated treatment. L, f, a and r were varied from 45 to 75 mm, 2.25 to 3 MHz, 1.5 to 8 times the wavelength and 9 to 12.5 mm, respectively. The resulting optimal device was a 761-element concentric-ring transducer with L = 68 mm, f = 2.75 MHz, a = 2.05λ and r = 9 mm. Simulated thermal lesions showed that it was possible to treat target tumors consistent with reported locations and sizes for prostate cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".