Minna M Kylmälä1,2, Teijo Konttila3, Paula Vesterinen1,2, Sari M Kivistö4, Kirsi Lauerma4, Mats Lindholm3, Heikki Väänänen3, Matti Stenroos3, Markku S Nieminen1, Helena Hänninen1, Lauri Toivonen1. 1. Division of Cardiology, Heart and Lung Center, Helsinki University Central Hospital, Helsinki, Finland. 2. BioMag Laboratory, Hospital District of Helsinki and Uusimaa HUSLAB, Helsinki University Central Hospital, Helsinki, Finland. 3. Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland. 4. Department of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital, Helsinki, Finland.
Abstract
BACKGROUND: Assessment of myocardial infarct (MI) size is important for therapeutic and prognostic reasons. We used body surface potential mapping (BSPM) to evaluate whether single-lead electrocardiographic variables can assess MI size. METHODS: We performed BSPM with 120 leads covering the front and back chest (plus limb leads) on 57 patients at different phases of MI: acutely, during healing, and in the chronic phase. Final MI size was determined by contrast-enhanced cardiac magnetic resonance imaging (DE-CMR) and correlated with various computed depolarization- and repolarization-phase BSPM variables. We also calculated correlations between BSPM variables and enzymatic MI size (peak CK-MBm). RESULTS: BSPM variables reflecting the Q- and R wave showed strong correlations with MI size at all stages of MI. R width performed the best, showing its strongest correlation with MI size on the upper right back, there representing the width of the "reciprocal Q wave" (r = 0.64-0.71 for DE-CMR, r = 0.57-0.64 for CK-MBm, P < 0.0001). Repolarization-phase variables showed only weak correlations with MI size in the acute phase, but these correlations improved during MI healing. T-wave variables and the QRSSTT integral showed their best correlations with DE-CMR defined MI size on the precordial area, at best r = -0.57, P < 0.0001 in the chronic phase. The best performing BSPM variables could differentiate between large and small infarcts at all stages of MI. CONCLUSIONS: Computed, single-lead electrocardiographic variables can estimate the final infarct size at all stages of MI, and differentiate large infarcts from small.
BACKGROUND: Assessment of myocardial infarct (MI) size is important for therapeutic and prognostic reasons. We used body surface potential mapping (BSPM) to evaluate whether single-lead electrocardiographic variables can assess MI size. METHODS: We performed BSPM with 120 leads covering the front and back chest (plus limb leads) on 57 patients at different phases of MI: acutely, during healing, and in the chronic phase. Final MI size was determined by contrast-enhanced cardiac magnetic resonance imaging (DE-CMR) and correlated with various computed depolarization- and repolarization-phase BSPM variables. We also calculated correlations between BSPM variables and enzymatic MI size (peak CK-MBm). RESULTS: BSPM variables reflecting the Q- and R wave showed strong correlations with MI size at all stages of MI. R width performed the best, showing its strongest correlation with MI size on the upper right back, there representing the width of the "reciprocal Q wave" (r = 0.64-0.71 for DE-CMR, r = 0.57-0.64 for CK-MBm, P < 0.0001). Repolarization-phase variables showed only weak correlations with MI size in the acute phase, but these correlations improved during MI healing. T-wave variables and the QRSSTT integral showed their best correlations with DE-CMR defined MI size on the precordial area, at best r = -0.57, P < 0.0001 in the chronic phase. The best performing BSPM variables could differentiate between large and small infarcts at all stages of MI. CONCLUSIONS: Computed, single-lead electrocardiographic variables can estimate the final infarct size at all stages of MI, and differentiate large infarcts from small.
Authors: Minna M Kylmälä; Teijo Konttila; Paula Vesterinen; Mats Lindholm; Heikki Väänänen; Matti Stenroos; Markku S Nieminen; Helena Hänninen; Lauri Toivonen Journal: Ann Noninvasive Electrocardiol Date: 2012-11-22 Impact factor: 1.468
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Authors: C P Juergens; C Fernandes; E T Hasche; S Meikle; G Bautovich; C A Currie; S B Freedman; R W Jeremy Journal: J Am Coll Cardiol Date: 1996-03-01 Impact factor: 24.094
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Authors: Pauli Pöyhönen; Minna Kylmälä; Paula Vesterinen; Sari Kivistö; Miia Holmström; Kirsi Lauerma; Heikki Väänänen; Lauri Toivonen; Helena Hänninen Journal: BMC Cardiovasc Disord Date: 2018-02-08 Impact factor: 2.298