Xiaojuan Xia1, Björn Wieslander2, David G Strauss3, Galen S Wagner4, Wojciech Zareba5, Arthur J Moss5, Jean-Philippe Couderc5. 1. Heart Research Follow-Up Program, Cardiology Division, University of Rochester Medical Center, 265 Crittenden Boulevard, PO Box 653, Rochester, NY 14642, USA heartjxx@heart.rochester.edu. 2. Clinical Physiology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden. 3. Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, Silver Spring, MD, USA. 4. Duke Clinical Research Institute, Duke University, Durham, NC, USA. 5. Heart Research Follow-Up Program, Cardiology Division, University of Rochester Medical Center, 265 Crittenden Boulevard, PO Box 653, Rochester, NY 14642, USA.
Abstract
AIMS: The Selvester QRS scoring system uses quantitative criteria from the standard 12-lead electrocardiogram (ECG) to estimate the myocardial scar size of patients, including those with left bundle branch block (LBBB). Automation of the scoring system could facilitate the clinical use of this technique which requires a set of multiple QRS patterns to be identified and measured. METHODS AND RESULTS: We developed a series of algorithms to automatically detect and measure the QRS parameters required for Selvester scoring. The 'QUantitative and Automatic REport of Selvester Score' was designed specifically for the analysis of ECGs from patients meeting new strict criteria for complete LBBB. The algorithms were designed using a training (n = 36) and a validation (n = 180) set of ECGs, consisting of signal-averaged 12-lead ECGs (1000 Hz sampling) recorded from 216 LBBB patients from the MADIT-CRT. We assessed the performance of the methods using expert manually adjudicated ECGs. The average of absolute differences between automatic and adjudicated Selvester scoring was 1.2 ± 1.5 points. The range of average differences for continuous measurements of wave locations and interval durations varied between 0 and 6 ms. Erroneous detection of Q, R, S, R', and S' waves (oversensed or missed) were 3, 1, 1, 16, and 6%, respectively. Seven percent of notches detected in the first 40 ms were misdetected. CONCLUSION: We propose an efficient computerized method for the automatic measurement of the Selvester score in patients with the strict LBBB. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: The Selvester QRS scoring system uses quantitative criteria from the standard 12-lead electrocardiogram (ECG) to estimate the myocardial scar size of patients, including those with left bundle branch block (LBBB). Automation of the scoring system could facilitate the clinical use of this technique which requires a set of multiple QRS patterns to be identified and measured. METHODS AND RESULTS: We developed a series of algorithms to automatically detect and measure the QRS parameters required for Selvester scoring. The 'QUantitative and Automatic REport of Selvester Score' was designed specifically for the analysis of ECGs from patients meeting new strict criteria for complete LBBB. The algorithms were designed using a training (n = 36) and a validation (n = 180) set of ECGs, consisting of signal-averaged 12-lead ECGs (1000 Hz sampling) recorded from 216 LBBB patients from the MADIT-CRT. We assessed the performance of the methods using expert manually adjudicated ECGs. The average of absolute differences between automatic and adjudicated Selvester scoring was 1.2 ± 1.5 points. The range of average differences for continuous measurements of wave locations and interval durations varied between 0 and 6 ms. Erroneous detection of Q, R, S, R', and S' waves (oversensed or missed) were 3, 1, 1, 16, and 6%, respectively. Seven percent of notches detected in the first 40 ms were misdetected. CONCLUSION: We propose an efficient computerized method for the automatic measurement of the Selvester score in patients with the strict LBBB. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Uzma Chaudhry; Pyotr G Platonov; Robert Jablonowski; Jean-Philippe Couderc; Henrik Engblom; Xiajuang Xia; Björn Wieslander; Brett D Atwater; David G Strauss; Jesper Van der Pals; Martin Ugander; Marcus Carlsson; Rasmus Borgquist Journal: Ann Noninvasive Electrocardiol Date: 2017-03-01 Impact factor: 1.468
Authors: Xiaojuan Xia; Anne-Christine Ruwald; Martin H Ruwald; Nene Ugoeke; Barbara Szepietowska; Valentina Kutyifa; Mehmet K Aktas; Poul Erik B Thomsen; Wojciech Zareba; Arthur J Moss; Jean-Philippe Couderc Journal: Ann Noninvasive Electrocardiol Date: 2016-08-30 Impact factor: 1.468