Comparison of the characteristics between machine learning and deep learning algorithms for ablation site classification in a novel cloud-based system.

IF 5.6 2区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Heart rhythm Pub Date : 2025-03-17 DOI:10.1016/j.hrthm.2025.03.1955

Masataka Narita, Daisuke Kawano, Naomichi Tanaka, Tsukasa Naganuma, Wataru Sasaki, Kazuhisa Matsumoto, Kazuhiko Kuinose, Hitoshi Mori, Yoshifumi Ikeda, Kazuo Matsumoto, Ritsushi Kato

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引用次数: 0

Abstract

Background: CARTONET is a cloud-based system for the analysis of ablation procedures using the CARTO system. The current CARTONET R14 model employs deep learning, but its accuracy and positive predictive value (PPV) remain under-evaluated.

Objective: This study aimed to compare the characteristics of the CARTONET system between the R12.1 and the R14 models.

Methods: Data from 396 atrial fibrillation ablation cases were analyzed. Using a CARTONET R14 model, the sensitivity and PPV of the automated anatomical location model were investigated. The distribution of potential reconnection sites and confidence level for each site were investigated. We also compared the difference in that data between the CARTONET R12.1, the previous CARTONET version, and the CARTONET R14 models.

Results: We analyzed the overall tags of 39169 points and the gap prediction of 625 segments using the CARTONET R14 model. The sensitivity and PPV of the R14 model significantly improved compared to that of the R12.1 model (R12.1 vs. R14; sensitivity, 71.2% vs. 77.5%, p<0.0001; PPV, 85.6 % vs. 86.2 %, p=0.0184). The incidence of reconnections was highly observed in the posterior area of the RPVs and LPVs (RPV, 98/238 [41.2%]; LPV 190/387 [49.1%]). On the other hand, the possibility of reconnection was highest in the roof area for the RPVs and LPVs (%; RPV, 14 [5.5-41]; LPV, 16 [8-22]).

Conclusion: The R14 model significantly improved sensitivity and PPV compared to the R12.1 model. The tendency for predicting potential reconnection sites was similar to the previous version, the R12 model.

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来源期刊

Heart rhythm 医学-心血管系统

CiteScore

10.50

自引率

5.50%

发文量

1465

审稿时长

24 days

期刊介绍： HeartRhythm, the official Journal of the Heart Rhythm Society and the Cardiac Electrophysiology Society, is a unique journal for fundamental discovery and clinical applicability. HeartRhythm integrates the entire cardiac electrophysiology (EP) community from basic and clinical academic researchers, private practitioners, engineers, allied professionals, industry, and trainees, all of whom are vital and interdependent members of our EP community. The Heart Rhythm Society is the international leader in science, education, and advocacy for cardiac arrhythmia professionals and patients, and the primary information resource on heart rhythm disorders. Its mission is to improve the care of patients by promoting research, education, and optimal health care policies and standards.