Direct nanodroplet and microbubble comparison for high intensity focused ultrasound ablation enhancement and safety
Bibliographic record
Abstract
High intensity focused ultrasound (HIFU) surgery often requires hours of ablation in order to treat an entire tumor. Both perfluorocarbon gaseous microbubbles and vaporized liquid droplets are known enhancers of HIFU thermal ablation. Microbubbles, however, often lead to surface or skin lesions. Furthermore, they have a relatively short half-life in vivo (minutes) rendering them insufficiently stable for an entire HIFU surgery, which can last several hours. Many droplet formulations require very high pressures to activate. Our aim was to design an agent that could shorten ablation procedures without sacrificing safety. We designed and investigated a perfluorocarbon nanodroplet composed of a 1:1 ratio of dodecafluoropentane and decafluorobutane. These are tuned to change phase and activate at only 2 MPa peak negative pressure with common HIFU pulse lengths, enabling focused and targeted activation. Additionally, they are stable at body temperature.
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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".