AIMS: The standard deviation of activation time (SDAT) derived from body surface maps (BSMs) has been proposed as an optimal measure of electrical dyssynchrony in patients with cardiac resynchronization therapy (CRT). The goal of this study was two-fold: (i) to compare the values of SDAT in individual CRT patients with reconstructed myocardial metrics of depolarization heterogeneity using an inverse solution algorithm and (ii) to compare SDAT calculated from 96-lead BSM with a clinically easily applicable 12-lead electrocardiogram (ECG). METHODS AND RESULTS: Cardiac resynchronization therapy patients with sinus rhythm and left bundle branch block at baseline (n = 19, 58% males, age 60 ± 11 years, New York Heart Association Classes II and III, QRS 167 ± 16) were studied using a 96-lead BSM. The activation time (AT) was automatically detected for each ECG lead, and SDAT was calculated using either 96 leads or standard 12 leads. Standard deviation of activation time was assessed in sinus rhythm and during six different pacing modes, including atrial pacing, sequential left or right ventricular, and biventricular pacing. Changes in SDAT calculated both from BSM and from 12-lead ECG corresponded to changes in reconstructed myocardial ATs. A high degree of reliability was found between SDAT values obtained from 12-lead ECG and BSM for different pacing modes, and the intraclass correlation coefficient varied between 0.78 and 0.96 (P < 0.001). CONCLUSION: Standard deviation of activation time measurement from BSM correlated with reconstructed myocardial ATs, supporting its utility in the assessment of electrical dyssynchrony in CRT. Importantly, 12-lead ECG provided similar information as BSM. Further prospective studies are necessary to verify the clinical utility of SDAT from 12-lead ECG in larger patient cohorts, including those with ischaemic cardiomyopathy.

Department of Biomedical Technology Faculty of Biomedical Engineering Czech Technical University Prague Sitna Sq 3105 27201 Kladno Czech Republic

Department of Cardiology Institute for Clinical and Experimental Medicine Vídeňská 1958 9 140 21 Prague 4 Czech Republic

Department of Cardiology University Medical Center Utrecht Heidelberglaan 100 3584 CX Utrecht The Netherlands

Department of Information Engineering Università Politecnica delle Marche via Brecce Bianche 12 60131 Ancona Italy

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Moss AJ, Hall WJ, Cannom DS, Klein H, Brown MW, Daubert JPet al. . Cardiac-resynchronization therapy for the prevention of heart-failure events. N Engl J Med 2009;361:1329–38. PubMed

Tang AS, Wells GA, Talajic M, Arnold MO, Sheldon R, Connolly Set al. . Resynchronization-defibrillation for ambulatory heart failure trial investigators. Cardiac-resynchronization therapy for mild-to-moderate heart failure. N Engl J Med 2010;363:2385–95. PubMed

Gold MR, Thebault C, Linde C, Abraham WT, Gerritse B, Ghio Set al. . Effect of QRS duration and morphology on cardiac resynchronization therapy outcomes in mild heart failure: results from the resynchronization reverses remodeling in systolic left ventricular dysfunction (REVERSE) study. Circulation 2012;126:822–9. PubMed

Sedova K, Repin K, Donin G, Van Dam P, Kautzner J. Clinical utility of body surface potential mapping in CRT patients. Arrhythm Electrophysiol Rev 2021;10:113–9. PubMed PMC

Johnson WB, Vatterott PJ, Peterson MA, Bagwe S, Underwood RD, Bank AJet al. . Body surface mapping using an ECG belt to characterize electrical heterogeneity for different left ventricular pacing sites during cardiac resynchronization: relationship with acute hemodynamic improvement. Heart Rhythm 2017;14:385–91. PubMed

Bank AJ, Gage RM, Curtin AE, Burns KV, Gillberg JM, Ghosh S. Body surface activation mapping of electrical dyssynchrony in cardiac resynchronization therapy patients: potential for optimization. J Electrocardiol 2018;51:534–41. PubMed

Elliott MK, Blauer J, Mehta VS, Sidhu BS, Gould J, Jackson Tet al. . Comparison of electrical dyssynchrony parameters between electrocardiographic imaging and a simulated ECG belt. J Electrocardiol 2021;68:117–23. PubMed

Rosík V, Karas S, Hebláková E, Tyšler M, Filipová S. Portable device for high resolution ECG mapping. Meas Sci Rev 2007;7:4.

Pan J, Tompkins WJ. A real-time QRS detection algorithm. IEEE Trans Biomed Eng 1985;32:230–6. PubMed

Marinucci D, Sbrollini A, Marcantoni I, Morettini M, Swenne CA, Burattini L. Artificial neural network for atrial fibrillation identification in portable devices. Sensors (Switzerland) 2020;20:1–16. PubMed PMC

Boonstra MJ, Roudijk RW, Brummel R, Kassenberg W, Blom LJ, Oostendorp TFet al. . Modeling the His-Purkinje effect in non-invasive estimation of endocardial and epicardial ventricular activation. Ann Biomed Eng 2022;50:343–59. PubMed PMC

Gage RM, Curtin AE, Burns KV, Ghosh S, Gillberg JM, Bank AJ. Changes in electrical dyssynchrony by body surface mapping predict left ventricular remodeling in patients with cardiac resynchronization therapy. Heart Rhythm 2017;14:392–9. PubMed

Rickard J, Jackson K, Biffi M, Vernooy K, Bank A, Cerkvenik Jet al. . The ECG belt for CRT response trial: design and clinical protocol. Pacing Clin Electrophysiol 2020;43:1063–71. PubMed

Gage RM, Khan AH, Syed IS, Bajpai A, Burns KV, Curtin AEet al. . Twelve-lead ECG optimization of cardiac resynchronization therapy in patients with and without delayed enhancement on cardiac magnetic resonance imaging. J Am Heart Assoc 2018;7:e009559. PubMed PMC

Targeted left ventricular lead positioning to the site of latest activation in cardiac resynchronization therapy: a systematic review and meta-analysis