The use of ultrasound-stimulated contrast agents as an adjuvant for collagenase therapy in chronic total occlusions
Bibliographic record
Abstract
AIMS: To investigate the effectiveness of combining collagenase and ultrasound-stimulated microbubble (USMB) treatments in reducing the mechanical force required for crossing a guidewire through CTOs. METHODS AND RESULTS: Experiments were conducted on ex vivo specimens of a rabbit femoral artery CTO model (n=45 total samples). Four primary groups were employed: control (n=6), collagenase only (n=15), USMB only (1 MHz frequency) (n=5), and collagenase+USMB (n=19). In one set of experiments the force required to puncture through CTO samples was measured and it was found that the puncture force was 2.31-fold lower for the combined treatment group relative to the comparable collagenase-only group (p<0.05). In a second set of experiments, the total protein and hydroxyproline content of the supernatant solution adjacent to the CTO was analysed. Significantly higher hydroxyproline levels were measured in collagenase+USMB treated CTOs (0.065 g/mL) compared to collagenase (0.030 g/mL), USMB (0.003 g/mL) and control (0.004 g/mL) (p<0.05), indicating that the combined treatment augmented collagenase degradation. CONCLUSIONS: Ultrasound-stimulated microbubbles improved the effectiveness of collagenase in reducing the force required to cross experimental CTOs. This new approach may have the potential to reduce treatment times and improve the success rates of emerging collagenase-based treatments of CTO.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".