Left Atrial Intracardiac Echocardiography to Assist Zero Fluoroscopy Pulse Field Atrial Fibrillation Ablation—A Beginner's Guide
Bibliographic record
Abstract
Background: Pulsed-field ablation (PFA) has emerged as a novel energy source for the management of atrial fibrillation (AF), offering improved tissue selectivity and a better safety profile. Although fluoroscopy has traditionally guided catheter positioning, the integration of intracardiac echocardiography (ICE), particularly from a left atrial (LA) vantage point, presents an opportunity for real-time visualization and enhanced procedural precision. In this paper, we describe a workflow for LA-ICE-guided PFA, without using fluoroscopy, and present preliminary data from our centre. Methods: All patients who underwent PFA for AF since December 2024 were screened, and those who underwent LA-ICE-guided ablation were included in the study. After patients provided informed consent, procedures were performed under general anesthesia with muscle relaxants to minimize stimulation of extracardiac muscles. Results: LA-ICE-guided PFA was performed in 100 consecutive patients with paroxysmal (73%) and persistent (27%) AF at a single centre. Zero-fluoroscopy (ZF) ablation was successfully performed in 28 patients, without any major complications. The challenges encountered during ZF ablation included enlarged atria, thick interatrial septum, venous tortuosity, aortic root aneurysm, and pacemaker leads. Visualizing the FlexCath sheath while crossing the interatrial septum and confirming its position in the left atrium immediately after crossing does require some effort, especially in a dilated left atrium. Conclusions: LA-ICE facilitates ZF-PFA for AF by offering superior visualization of the LA anatomy, continuous monitoring of catheter orientation, precise catheter positioning, and maintenance of catheter-tissue contact.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".