Abstract 15798: Real Time MRI Based Atrial Cryoablation
Bibliographic record
Abstract
Introduction: Balloon cryoablation is being increasingly used for pulmonary vein isolation. Acute determination of lesion permanency cannot be ascertained directly, but is inferred by PV occlusion and acute PV isolation. We aimed to determine if direct confirmation of vessel occlusion and lesion formation could be visualized in real time in a MRI system using a novel MRI compatible cryo balloon catheter. Methods: We used a canine model (n=3) and a MRI compatible cryo balloon catheter built for animal use (Medtronic CryoCath, Montreal, Canada). The procedure was performed in a 3T (Verio, Siemens) MR scanner. The MRI compatible 28 mm cryo balloon was advanced into the right atrium (RA) via the femoral vein under MRI guidance. Gadolinium based contrast (Multihance) was injected to confirm vessel occlusion. The superior vena cava (SVC) - RA junction was frozen for 3 mins. Post ablation, late gadolinium enhancement MRI (LGE-MRI) was obtained acutely to confirm the ablation. The heart was excised to confirm the tissue changes. Results: Panel A shows the inflated balloon at the SVC ostium. Panel B shows contrast injected in the SVC confirming its occlusion. Panel C is an MR image taken during the freeze cycle. Panel D is an LGE-MRI showing enhancement along the SVC wall confirming ablation. Panel E is an axial view of the SVC confirming circumferential ablation with no apparent gaps. The ablation completeness was confirmed in pathology. Conclusion: A real time MR-based balloon cryo ablation system was implemented. It allows real time confirmation of vessel occlusion, visualization of a freeze zone and visual confirmation of tissue changes from ablation in the pre-clinical setting.
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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 | 0.000 |
| 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) | 0.004 | 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".