The evaluation of steerable ultrasonic catheters for minimally invasive MRI‐guided cardiac ablation
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to develop steerable MR-compatible ultrasound catheters suitable for minimally invasive MRI-guided cardiac ablation therapies. METHODS: MRI-compatible ultrasound steerable catheters were developed and tested for their overall tissue heating performance and safety. Ultrasound transducers were mounted on a monodirectional deflectable catheter tip that was made to be MRI-compatible. Catheter safety was assessed on the potential to form hot spots at the distal end of the catheter throughout fast spin echo and thermometry scans. Heating experiments were performed on phantoms and ex vivo porcine cardiac samples. RESULTS: During catheter safety experiments, a maximum temperature increase of 11.35 ± 0.83°C was evident after a 12-min, 40-s fast spin echo scan with a whole body specific absorption rate (SAR) of 1.9 W/kg and 1.07 ± 0.22°C during thermometry scans (flip angle = 90°; scan time = 12 min, 41 s; whole body SAR = 0.34 W/kg). Temperature elevations induced by the sonication were shown to be on the order of 38.1 ± 5.2°C for phantom experiments and 49.3 ± 9.7°C for ex vivo cardiac samples. CONCLUSION: Steerable ultrasound catheters have the potential to be safely placed in an MR system with little concern of catheter self-heating and driven to heat surrounding structures to cause ablations. In addition, these catheters have the added benefit of a deflectable tip that allows the treatment of multiple targets from within the bore of the MR scanner.
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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 | 0.002 |
| 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 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".