Intracardiac echo-facilitated 3D electroanatomical mapping of ventricular arrhythmias from the papillary muscles: assessing the ‘fourth dimension’ during ablation
Bibliographic record
Abstract
AIMS: Ventricular arrhythmias (VA) originating from a papillary muscle (PM) have recently been described as a distinct clinical entity with peculiar features that make its treatment with catheter ablation challenging. Here, we report our experience using an intracardiac echo-facilitated 3D electroanatomical mapping approach in a case series of patients undergoing ablation for PM VA. METHODS AND RESULTS: Sixteen patients who underwent catheter ablation for ventricular tachycardia (VT) or symptomatic premature ventricular contractions originating from left ventricular PMs were included in the study. A total of 24 procedures (mean 1.5 per patient) were performed: 15 using a retrograde aortic approach and 9 using a transseptal approach. Integrated intracardiac ultrasound for 3D electroanatomical mapping was used in 15 of the 24 procedures. The posteromedial PM was the most frequent culprit for the clinical arrhythmia, and the body was the part of the PM most likely to be the successful site for ablation. The site of ablation was identified based on the best pace map matching the clinical arrhythmia and the site of earliest the activation. At a mean follow-up of 10.5 ± 7 months, only two patients had recurrent arrhythmias following a repeat ablation procedure. CONCLUSION: An echo-facilitated 3D electroanatomical mapping allows for real-time creation of precise geometries of cardiac chambers and endocavitary structures. This is useful during procedures such as catheter ablation of VAs originating from PMs, which require detailed representation of anatomical landmarks. Routine adoption of this technique should be considered to improve outcomes of PM VA 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".