MRI and contrast‐enhanced ultrasound monitoring of prostate microwave focal thermal therapy: An in vivo canine study
Bibliographic record
Abstract
PURPOSE: To compare the value of diffusion-weighted MRI (DWI), dynamic contrast-enhanced (DCE) MRI, and microbubble contrast-enhanced ultrasound (CEUS) for assessment of the thermal lesion created by interstitial microwave heating of the normal canine prostate. MATERIALS AND METHODS: A microwave antenna was inserted into each lobe of the prostate in seven dogs to induce coagulation necrosis. Immediately after therapy the lesion was assessed using CEUS, DCE-MRI, and DWI. The prostates were excised, photographed, and prepared for hematoxylin and eosin staining. Results from posttreatment MRI and ultrasound were compared to histology. RESULTS: The apparent diffusion coefficient (ADC) was slightly lowered within the thermal lesion but was drastically reduced in a ring-like region that corresponds to a grossly appearing red thermal damage zone immediately peripheral to the central coagulum. Both DCE-MRI and CEUS delineated a smaller area of vascular damage, for which the borders lie within the red zone. CONCLUSION: The red zone encompasses a range of vascular responses, including hyperemia and hemostasis, and is known to progress to necrosis and tissue nonviability. DWI clearly depicts this zone as a region of sharply reduced ADC, and may be better than contrast-enhanced imaging for accurate assessment of the eventual full extent of thermal damage.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".