Temperature dependence of acoustic harmonics generated by nonlinear ultrasound beam propagation in <i>ex vivo</i> tissue and tissue-mimicking phantoms
Bibliographic record
Abstract
PURPOSE: Hyperthermia is a cancer treatment technique that could be delivered as a stand-alone modality or in conjunction with chemotherapy or radiation therapy. Noninvasive and real-time temperature monitoring of the heated tissue improves the efficacy and safety of the treatment. A temperature-sensitive acoustic parameter is required for ultrasound-based thermometry. In this paper the amplitude and the energy of the acoustic harmonics of the ultrasound backscattered signal are proposed as suitable parameters for noninvasive ultrasound thermometry. MATERIALS AND METHODS: A commercial high frequency ultrasound imaging system was used to generate and detect acoustic harmonics in tissue-mimicking gel phantoms and ex vivo bovine muscle tissues. The pressure amplitude and the energy content of the backscattered fundamental frequency (p1 and E1), the second (p2 and E2) and the third (p3 and E3) harmonics were detected in pulse-echo mode. Temperature was increased from 26° to 46 °C uniformly through both samples. The amplitude and the energy content of the harmonics and their ratio were measured and analysed as a function of temperature. RESULTS: The average p1, p2 and p3 increased by 69%, 100% and 283%, respectively as the temperature was elevated from 26° to 46 °C in tissue samples. In the same experiment the average E1, E2 and E3 increased by 163%, 281% and 2257%, respectively. A similar trend was observed in tissue-mimicking gel phantoms. CONCLUSIONS: The findings suggest that the harmonics generated due to nonlinear ultrasound beam propagation are highly sensitive to temperature and could potentially be used for noninvasive ultrasound tissue thermometry.
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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".