New Acoustic Beams Designed for Rapid Lesion Formation: Limitations Near the Skin During Multiple Lesion Treatments
Bibliographic record
Abstract
Minimally invasive surgery by intense focused ultrasound beams producing defined lesions is being studied extensively by different groups. Lesion formation from a single pulse, depending on treatment time, tissue temperature, and pulse repetition of about 1 minute, should produce little damage near the skin. However, this scheme results in unacceptably long treatment times when used on larger tumors. A possible solution is to generate more rapid treatment times, or larger lesion volumes per pulse. However, hyperthermic temperatures in the overlying normal tissues including the skin may limit these treatments. In a previous presentation, simulations using an "ideal" transducer, pulses as short as 4 s and rapid stirring of the coupling bolus would reduce the temperature rise near the skin. Thus pulse repetitions as short of 10 s would be acceptable. However, real transducer beams show large aberrations which can greatly increase the near-field intensities, and make them unacceptable for hyperthermia therapy. Some artifacts are be caused by clamping of the transducer, others are related to thickness variations of the transducers which generate heterogenous phase shifts from different parts of the transducer which produce unwanted spreads at beam's focus. The authors present detailed amplitude and phase scans near different transducers demonstrating the artifacts, and confirm them using novel ultrasound/magnetic-resonance phantoms showing the measured temperatures at the focus, and at 1 cm depth from the "skin" where the heating is considerably larger than that predicted by theory. Finally, we will discuss solutions for problems in the near field by improving the transducer mounting and reducing the unwanted phase shifts.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".