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Volume 22
Issue 11
10.3390/s22114058
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Communication

Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study

by
Qiyuan An
1,*,
Rafe McBeth
2,3,
Houliang Zhou
1,
Bryan Lawlor
2,
Dan Nguyen
2,
Steve Jiang
2,
Mark S. Link
2 and
Yingying Zhu
1
1
Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA
2
Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
3
Cardiac Electrophysiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
*
Author to whom correspondence should be addressed.
Sensors 2022, 22(11), 4058; https://doi.org/10.3390/s22114058
Submission received: 7 April 2022 / Revised: 23 May 2022 / Accepted: 24 May 2022 / Published: 27 May 2022
(This article belongs to the Special Issue Impact of Sensors in Biomechanics, Health Disease and Rehabilitation)
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Abstract

Atrial fibrillation (AF) is a common cardiac arrhythmia and affects one to two percent of the population. In this work, we leverage the three-dimensional atrial endocardial unipolar/bipolar voltage map to predict the AF type and recurrence of AF in 1 year. This problem is challenging for two reasons: (1) the unipolar/bipolar voltages are collected at different locations on the endocardium and the shapes of the endocardium vary widely in different patients, and thus the unipolar/bipolar voltage maps need aligning to the same coordinate; (2) the collected dataset size is very limited. To address these issues, we exploit a pretrained 3D point cloud registration approach and finetune it on left atrial voltage maps to learn the geometric feature and align all voltage maps into the same coordinate. After alignment, we feed the unipolar/bipolar voltages from the registered points into a multilayer perceptron (MLP) classifier to predict whether patients have paroxysmal or persistent AF, and the risk of recurrence of AF in 1 year for patients in sinus rhythm. The experiment shows our method classifies the type and recurrence of AF effectively.
Keywords: registration; atrial fibrillation; electroanatomical voltage mapping registration; atrial fibrillation; electroanatomical voltage mapping

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MDPI and ACS Style

An, Q.; McBeth, R.; Zhou, H.; Lawlor, B.; Nguyen, D.; Jiang, S.; Link, M.S.; Zhu, Y. Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study. Sensors 2022, 22, 4058. https://doi.org/10.3390/s22114058

AMA Style

An Q, McBeth R, Zhou H, Lawlor B, Nguyen D, Jiang S, Link MS, Zhu Y. Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study. Sensors. 2022; 22(11):4058. https://doi.org/10.3390/s22114058

Chicago/Turabian Style

An, Qiyuan, Rafe McBeth, Houliang Zhou, Bryan Lawlor, Dan Nguyen, Steve Jiang, Mark S. Link, and Yingying Zhu. 2022. "Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study" Sensors 22, no. 11: 4058. https://doi.org/10.3390/s22114058

APA Style

An, Q., McBeth, R., Zhou, H., Lawlor, B., Nguyen, D., Jiang, S., Link, M. S., & Zhu, Y. (2022). Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study. Sensors, 22(11), 4058. https://doi.org/10.3390/s22114058

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