<title>Feasibility of monitoring HIFU prostate cancer therapy using elastography</title>
Bibliographic record
Abstract
The objective of this study is to investigate the feasibility of elastographic monitoring of High Intensity Focused Ultrasound (HIFU) therapy of prostate cancer. Elastography is an imaging technique based on strain estimation in soft tissues under quasi-static compression. Since pathological tissues and HIFU-induced lesions exhibit different elastic properties than normal tissues, elastography is potentially able to achieve these goals. An ultrasound scanner was connected to a PC to acquire RF images. This setup is compatible with a HIFU device used for prostate cancer therapy by transrectal route. The therapy transducer and the biplane-imaging probe are covered with a balloon filled with a coupling liquid. Compression of the prostate is applied by inflating the balloon, while imaging sector scans of the prostate. In-vivo elastograms of the prostate were acquired before HIFU treatment. Problems inherent to in-vivo acquisitions are reported, such as undesired tangential displacements during the radial compression. This study shows the potential for in-vivo elastogram acquisition of HIFU-induced lesions in the human prostate.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".