Ultrasound imaging guided precision histotripsy: Effects of pulse settings on ablation properties in rat brain
Bibliographic record
Abstract
A high-frequency 6 MHz miniature handheld histotripsy device with an endoscopic form factor and co-registered high-resolution ultrasound imaging was developed. This device could allow precision histotripsy ablation during minimally invasive brain tumor surgeries with real-time image guidance. This study characterized the outcome of acute histotripsy in the normal in vivo rat brain using the device with a range of histotripsy pulse settings, including number of cycles, pulse repetition frequency, and pressure, as well as other experimental factors. The stability and shape of the bubble cloud were measured during ablations, as well as the post-histotripsy ablation shape in ultrasound B-mode and histology. The results were compared between histological images and the ultrasound imaging data to determine how well ultrasound data reflected observable damage in histology. The results indicated that while pulse settings can have some influence on ablation shape, sample-to-sample variation had a larger influence on ablation shape. This suggests that real-time ablation monitoring is essential for accurate knowledge of outcomes. Ultrasound imaging provided an accurate real-time indication of ablation shape both during ablation and post-ablation.
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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) | 0.001 | 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".