Key result
Lumipoint detects critical isthmuses reliably but isolates only the relevant region in ~12% of atypical atrial flutters.
Why the study?
Identifying the critical isthmus region of atrial re-entry tachycardias is challenging, and the quality of Lumipoint software for identifying arrhythmia-relevant critical isthmus regions in atypical atrial flutter needed evaluation.
Does Lumipoint software mapping accurately identify the critical isthmus region in patients with atypical atrial flutter?
Observational (n=33)
Does Lumipoint software mapping accurately identify the critical isthmus region in patients with atypical atrial flutter?
The Lumipoint mapping algorithm reliably detects at least one critical isthmus region in atypical atrial flutter, but requires preselection of the lowest and widest electrical activity minima to improve specificity.
Lumipoint mapping warrants cautious use for isthmus identification in atypical flutter; leaves open the value of refined algorithms in ablation trials.
INTRODUCTION: Identifying the critical isthmus region (CIR) of atrial re-entry tachycardias (AT) is challenging. The Lumipoint® (LP) software, developed for the Rhythmia® mapping system, aims to facilitate the successful ablation of ATs by identifying the CIR. OBJECTIVE: The objective of this study was to evaluate the quality of LP regarding the percentage of arrhythmia-relevant CIR in patients with atypical atrial flutter (AAF). METHODS: In this retrospective study, we analyzed 57 AAF forms. Electrical activity (EA) was mapped over tachycardia cycle length resulting in a two-dimensional EA pattern. The hypothesis was that EA minima suggest potential CIRs with slow-conduction-zone. RESULTS: A total of n = 33 patients were included, with the majority of patients being already preablated (69.7%). LP algorithm identified a mean of 2.4 EA minima and 4.4 suggested CIRs per AAF form. Overall, we observed a low probability of identifying only the relevant CIR (POR) at 12.3% but a high probability that at least one CIR is detected (PALO) at 98.2%. Detailed analysis revealed EA minima depth (≤20%) and width (>50 ms) as the best predictors of relevant CIRs. Wide minima occurred rarely (17.5%), while low minima were more frequently present (75.4%). Minima depth of EA ≤ 20% showed the best PALO/POR overall (95% and 60%, respectively). Analysis in recurrent AAF ablations (five patients) revealed that CIR in de novo AAF was already detected by LP during the index procedure. CONCLUSION: The LP algorithm provides an excellent PALO (98.2%), but poor POR (12.3%) to detect the CIR in AAF. POR improved by preselection of the lowest and widest EA minima. In addition, there might be the role of initial bystander CIRs becoming relevant for future AAFs.
No takes yet. Share an insight, caveat, or question.
Vonderlin et al. (2023) conducted an observational in Atypical atrial flutter (n=33). Lumipoint software algorithm was evaluated on Probability of identifying only the relevant critical isthmus region (POR) and probability that at least one CIR is detected (PALO). The Lumipoint algorithm detected at least one critical isthmus region in 98.2% of atypical atrial flutter cases, but identified only the relevant region in just 12.3% of cases.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: