Vasanth Ravikumar1, Elizabeth Annoni2, Preethy Parthiban2, Sharon Zlochiver2, Henri Roukoz3, Siva K Mulpuru4, Elena G Tolkacheva2. 1. Department of Electrical Engineering, University of Minnesota, Minneapolis, Minnesota, USA. 2. Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA. 3. Division of Cardiovascular, Medical School, University of Minnesota, Minneapolis, Minnesota, USA. 4. Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Abstract
BACKGROUND: Catheter ablation is associated with limited success rates in patients with persistent atrial fibrillation (AF). Currently, existing mapping systems fail to identify critical target sites for ablation. Recently, we proposed and validated several techniques (multiscale frequency [MSF], Shannon entropy [SE], kurtosis [Kt], and multiscale entropy [MSE]) to identify pivot point of rotors using ex-vivo optical mapping animal experiments. However, the performance of these techniques is unclear for the clinically recorded intracardiac electrograms (EGMs), due to the different nature of the signals. OBJECTIVE: This study aims to evaluate the performance of MSF, MSE, SE, and Kt techniques to identify the pivot point of the rotor using unipolar and bipolar EGMs obtained from numerical simulations. METHODS: Stationary and meandering rotors were simulated in a 2D human atria. The performances of new approaches were quantified by comparing the "true" core of the rotor with the core identified by the techniques. Also, the performances of all techniques were evaluated in the presence of noise, scar, and for the case of the multielectrode multispline and grid catheters. RESULTS: Our results demonstrate that all the approaches are able to accurately identify the pivot point of both stationary and meandering rotors from both unipolar and bipolar EGMs. The presence of noise and scar tissue did not significantly affect the performance of the techniques. Finally, the core of the rotors was correctly identified for the case of multielectrode multispline and grid catheter simulations. CONCLUSION: The core of rotors can be successfully identified from EGMs using novel techniques; thus, providing motivation for future clinical implementations.
BACKGROUND: Catheter ablation is associated with limited success rates in patients with persistent atrial fibrillation (AF). Currently, existing mapping systems fail to identify critical target sites for ablation. Recently, we proposed and validated several techniques (multiscale frequency [MSF], Shannon entropy [SE], kurtosis [Kt], and multiscale entropy [MSE]) to identify pivot point of rotors using ex-vivo optical mapping animal experiments. However, the performance of these techniques is unclear for the clinically recorded intracardiac electrograms (EGMs), due to the different nature of the signals. OBJECTIVE: This study aims to evaluate the performance of MSF, MSE, SE, and Kt techniques to identify the pivot point of the rotor using unipolar and bipolar EGMs obtained from numerical simulations. METHODS: Stationary and meandering rotors were simulated in a 2D human atria. The performances of new approaches were quantified by comparing the "true" core of the rotor with the core identified by the techniques. Also, the performances of all techniques were evaluated in the presence of noise, scar, and for the case of the multielectrode multispline and grid catheters. RESULTS: Our results demonstrate that all the approaches are able to accurately identify the pivot point of both stationary and meandering rotors from both unipolar and bipolar EGMs. The presence of noise and scar tissue did not significantly affect the performance of the techniques. Finally, the core of the rotors was correctly identified for the case of multielectrode multispline and grid catheter simulations. CONCLUSION: The core of rotors can be successfully identified from EGMs using novel techniques; thus, providing motivation for future clinical implementations.
Authors: Shivaram P Arunachalam; Elizabeth M Annoni; Siva K Mulpuru; Paul A Friedman; Elena G Tolkacheva Journal: Conf Proc IEEE Eng Med Biol Soc Date: 2016-08
Authors: Brian J Hansen; Jichao Zhao; Ning Li; Alexander Zolotarev; Stanislav Zakharkin; Yufeng Wang; Josh Atwal; Anuradha Kalyanasundaram; Suhaib H Abudulwahed; Katelynn M Helfrich; Anna Bratasz; Kimerly A Powell; Bryan Whitson; Peter J Mohler; Paul M L Janssen; Orlando P Simonetti; John D Hummel; Vadim V Fedorov Journal: JACC Clin Electrophysiol Date: 2018-11-01
Authors: Sanghamitra Mohanty; Prasant Mohanty; Chintan Trivedi; Carola Gianni; Domenico G Della Rocca; Luigi Di Biase; Andrea Natale Journal: Circ Arrhythm Electrophysiol Date: 2018-03
Authors: Vasanth Ravikumar; Elizabeth M Annoni; Siva K Mulpuru; Henri Roukoz; Elena G Tolkacheva Journal: Annu Int Conf IEEE Eng Med Biol Soc Date: 2018-07
Authors: Susumu Tao; Samuel F Way; Joshua Garland; Jonathan Chrispin; Luisa A Ciuffo; Muhammad A Balouch; Saman Nazarian; David D Spragg; Joseph E Marine; Ronald D Berger; Hugh Calkins; Hiroshi Ashikaga Journal: PLoS One Date: 2017-07-05 Impact factor: 3.240
Authors: Shohreh Honarbakhsh; Richard J Schilling; Rui Providencia; Emily Keating; Simon Sporton; Martin Lowe; Pier D Lambiase; Anthony Chow; Mark J Earley; Ross J Hunter Journal: J Cardiovasc Electrophysiol Date: 2018-10-14
Authors: Vasanth Ravikumar; Sanket Thakare; Xiangzhen Kong; Henri Roukoz; Elena G Tolkacheva Journal: Front Physiol Date: 2022-01-20 Impact factor: 4.566