Shijie Zhou1, John L Sapp2, B Milan Horáček3, James W Warren4, Paul J MacInnis4, Jason Davis5, Ihab Elsokkari5, Rajin Choudhury5, Ratika Parkash5, Chris Gray5, Martin Gardner5, Ciorsti J MacIntyre5, Amir AbdelWahab5. 1. Alliance for Cardiovascular Diagnostic and Treatment Innovation, Institute of Computational Medicine, Johns Hopkins University, Baltimore, Maryland. 2. Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, Canada; Department of Physiology and Biophysics, Dalhousie University, Halifax, Canada. Electronic address: john.sapp@nshealth.ca. 3. School of Biomedical Engineering, Dalhousie University, Halifax, Canada. 4. Department of Physiology and Biophysics, Dalhousie University, Halifax, Canada. 5. Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, Canada.
Abstract
BACKGROUND: To facilitate catheter ablation of ventricular tachycardia (VT), we previously developed an automated method to identify sources of left ventricular (LV) activation in real time using 12-lead electrocardiography (ECG), the accuracy of which depends on acquisition of a complete electroanatomic (EA) map. OBJECTIVE: The purpose of this study was to assess the feasibility of using a registered cardiac computed tomogram (CT) rather than an EA map to permit real-time localization and avoid errors introduced by incomplete maps. METHODS: Before LV VT ablation, 10 patients underwent CT imaging and 3-dimensional reconstruction of the cardiac surface to create a triangle mesh surface, which was registered to the EA map during the procedure and imported into custom localization software. The software uses QRS integrals from leads III, V2, and V6; derives personalized regression coefficients from pacing at ≥5 sites with known locations; and estimates the location of unknown activation sites on the 3-dimensional patient-specific LV endocardial surface. Localization accuracy was quantified for VT exit sites in millimeters by comparing the calculated against the known locations. RESULTS: The VT exit site was identified for 20 VTs using activation and entrainment mapping, supplemented by pace-mapping at the scar margin. The automated localization software achieved incremental accuracy with additional pacing sites and had a mean localization error of 6.9 ± 5.7 mm for the 20 VTs. CONCLUSION: Patient-specific CT geometry is feasible for use in real-time automated localization of ventricular activation and may avoid reliance on a complete EA map.
BACKGROUND: To facilitate catheter ablation of ventricular tachycardia (VT), we previously developed an automated method to identify sources of left ventricular (LV) activation in real time using 12-lead electrocardiography (ECG), the accuracy of which depends on acquisition of a complete electroanatomic (EA) map. OBJECTIVE: The purpose of this study was to assess the feasibility of using a registered cardiac computed tomogram (CT) rather than an EA map to permit real-time localization and avoid errors introduced by incomplete maps. METHODS: Before LV VT ablation, 10 patients underwent CT imaging and 3-dimensional reconstruction of the cardiac surface to create a triangle mesh surface, which was registered to the EA map during the procedure and imported into custom localization software. The software uses QRS integrals from leads III, V2, and V6; derives personalized regression coefficients from pacing at ≥5 sites with known locations; and estimates the location of unknown activation sites on the 3-dimensional patient-specific LV endocardial surface. Localization accuracy was quantified for VT exit sites in millimeters by comparing the calculated against the known locations. RESULTS: The VT exit site was identified for 20 VTs using activation and entrainment mapping, supplemented by pace-mapping at the scar margin. The automated localization software achieved incremental accuracy with additional pacing sites and had a mean localization error of 6.9 ± 5.7 mm for the 20 VTs. CONCLUSION:Patient-specific CT geometry is feasible for use in real-time automated localization of ventricular activation and may avoid reliance on a complete EA map.
Authors: Ryan Missel; Prashnna K Gyawali; Jaideep Vitthal Murkute; Zhiyuan Li; Shijie Zhou; Amir AbdelWahab; Jason Davis; James Warren; John L Sapp; Linwei Wang Journal: Comput Biol Med Date: 2020-09-23 Impact factor: 4.589
Authors: Shijie Zhou; Amir AbdelWahab; B Milan Horáček; Paul J MacInnis; James W Warren; Jason S Davis; Ihab Elsokkari; David C Lee; Ciorsti J MacIntyre; Ratika Parkash; Chris J Gray; Martin J Gardner; Curtis Marcoux; Rajin Choudhury; Natalia A Trayanova; John L Sapp Journal: Circ Arrhythm Electrophysiol Date: 2020-06-15
Authors: Shijie Zhou; Amir AbdelWahab; John L Sapp; Eric Sung; Konstantinos N Aronis; James W Warren; Paul J MacInnis; Rushil Shah; B Milan Horáček; Ronald Berger; Harikrishna Tandri; Natalia A Trayanova; Jonathan Chrispin Journal: JACC Clin Electrophysiol Date: 2020-11-25