Abstract 19778: Novel Strategy for Improved Substrate Mapping of the Atria: Omnipolar Catheter and Signal Processing Technology Assesses Electrogram Signals Along Physiologic and Anatomic Directions
Bibliographic record
Abstract
Introduction: Substrate mapping is evolving as a potential strategy for atrial fibrillation ablation. Defining scar borders and functional boundaries is typically under taken with bipolar electrodes. Catheter orientation affects electrogram (EGM) signal amplitude due to an orientation dependence of bipoles. We developed orientation independent Omnipolar Technology (OT) and compared OT EGM amplitude with traditional bipolar (Bi) methods. Methods: Four anesthetized swine were studied in 6 sessions with a 3D mapping system and a multielectrode OT ablation catheter placed in RA and LA locations in 4 rhythms. With the OT catheter in a stable location, 30 successive atrial beats were acquired. OT electrodes provided bipole (Bi) as well as OT signals along both activation (OTa) and surface normal (OTn) directions. Peak to peak amplitudes (Vpp) of OT and Bi signals were compared for magnitude and consistency. Results: As shown in the table, OT signal amplitudes over all atrial locations and rhythms were greater than traditional bipole amplitudes. The coefficients of variation for signal amplitude over successive cardiac beats were substantially less for OTa and OTn (*p < 0.01 with respect to Bi) than for Bi, reflecting electrode pair orientation effects. Conclusions: Distinct electrogram signals were resolved by OT along physiologic (activation) and anatomic (surface normal) directions. Catheter orientation independent OT signal amplitudes were more self-consistent and reliable than those from orientation dependent bipolar electrode pairs. Omnipolar technology approaches may permit more accurate and specific definition of substrate and thus catheter ablation of arrhythmias.
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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) | 0.001 | 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".