Interstitial ultrasound heating applicator for MR-guided thermal therapy.
Bibliographic record
Abstract
The ability to control the shape of thermal coagulation was investigated for various interstitial heating applicators incorporating planar transducers and device rotation. Magnetic-resonance-compatible interstitial ultrasound applicators were constructed and the effects of ultrasound power, frequency, scan rate and heating time on lesion radius were studied in heating experiments in excised liver tissue. Continuous thermal lesions were generated by scanning heating applicators over a 180 angular sector. The region of thermal coagulation was restricted to the prescribed sector. Lesion radius increased with acoustic power and heating time and decreased with increasing frequency. The relationship between the temperature distribution generated by the applicator and the resulting thermal lesion was assessed with MRI. Analysis of MR temperature maps revealed that the temperature distribution could be measured accurately within 2 mm from the surface of the applicator, and the boundary of thermal coagulation was defined by a temperature of 54 +/- 12 degrees C. Calculations of temperature distributions indicated that slower scan rates can overcome the tendency of perfusion to reduce the radius of thermal lesion. This applicator design and delivery strategy make conformal interstitial heating possible.
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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 | 0.001 |
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".