Cardiovascular Magnetic Resonance to Predict Appropriate Implantable Cardioverter Defibrillator Therapy in Ischemic and Nonischemic Cardiomyopathy Patients Using Late Gadolinium Enhancement Border Zone: Comparison of Four Analysis Methods
Late gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in...
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| Vydáno v: | Circulation. Cardiovascular imaging Ročník 10; číslo 9 |
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01.09.2017
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| Abstract | Late gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM) patients and to evaluate 4 LGE border-zone algorithms.
ICM and NICM patients who underwent LGE cardiac magnetic resonance imaging prior to ICD implantation were retrospectively included. Two semiautomatic algorithms, expectation maximization, weighted intensity, a priori information and a weighted border zone algorithm, were compared with a modified full-width half-maximum and a 2-3SD threshold-based algorithm (2-3SD). Hazard ratios were calculated per 1% increase in LGE. A total of 74 ICM and 34 NICM were followed for 63 months (1-140) and 52 months (0-133), respectively. ICM patients had 27 appropriate ICD events, and NICM patients had 7 ICD events. In ICM patients with primary prophylactic ICD, LGE border zone predicted ICD therapy in univariable and multivariable analysis measured by the expectation maximization, weighted intensity, a priori information, weighted border zone, and modified full-width half-maximum algorithms (hazard ratios 1.23, 1.22, and 1.05, respectively;
<0.05; negative predictive value 92%). For NICM, total LGE by all 4 methods was the strongest predictor (hazard ratios, 1.03-1.04;
<0.05), though the number of events was small.
Appropriate ICD therapy can be predicted in ICM patients with primary prevention ICD by quantifying the LGE border zone. In NICM patients, total LGE but not LGE border zone had predictive value for ICD therapy. However, the algorithms used affects the predictive value of these measures. |
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| AbstractList | Late gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM) patients and to evaluate 4 LGE border-zone algorithms.
ICM and NICM patients who underwent LGE cardiac magnetic resonance imaging prior to ICD implantation were retrospectively included. Two semiautomatic algorithms, expectation maximization, weighted intensity, a priori information and a weighted border zone algorithm, were compared with a modified full-width half-maximum and a 2-3SD threshold-based algorithm (2-3SD). Hazard ratios were calculated per 1% increase in LGE. A total of 74 ICM and 34 NICM were followed for 63 months (1-140) and 52 months (0-133), respectively. ICM patients had 27 appropriate ICD events, and NICM patients had 7 ICD events. In ICM patients with primary prophylactic ICD, LGE border zone predicted ICD therapy in univariable and multivariable analysis measured by the expectation maximization, weighted intensity, a priori information, weighted border zone, and modified full-width half-maximum algorithms (hazard ratios 1.23, 1.22, and 1.05, respectively;
<0.05; negative predictive value 92%). For NICM, total LGE by all 4 methods was the strongest predictor (hazard ratios, 1.03-1.04;
<0.05), though the number of events was small.
Appropriate ICD therapy can be predicted in ICM patients with primary prevention ICD by quantifying the LGE border zone. In NICM patients, total LGE but not LGE border zone had predictive value for ICD therapy. However, the algorithms used affects the predictive value of these measures. Late gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM) patients and to evaluate 4 LGE border-zone algorithms.BACKGROUNDLate gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM) patients and to evaluate 4 LGE border-zone algorithms.ICM and NICM patients who underwent LGE cardiac magnetic resonance imaging prior to ICD implantation were retrospectively included. Two semiautomatic algorithms, expectation maximization, weighted intensity, a priori information and a weighted border zone algorithm, were compared with a modified full-width half-maximum and a 2-3SD threshold-based algorithm (2-3SD). Hazard ratios were calculated per 1% increase in LGE. A total of 74 ICM and 34 NICM were followed for 63 months (1-140) and 52 months (0-133), respectively. ICM patients had 27 appropriate ICD events, and NICM patients had 7 ICD events. In ICM patients with primary prophylactic ICD, LGE border zone predicted ICD therapy in univariable and multivariable analysis measured by the expectation maximization, weighted intensity, a priori information, weighted border zone, and modified full-width half-maximum algorithms (hazard ratios 1.23, 1.22, and 1.05, respectively; P<0.05; negative predictive value 92%). For NICM, total LGE by all 4 methods was the strongest predictor (hazard ratios, 1.03-1.04; P<0.05), though the number of events was small.METHODS AND RESULTSICM and NICM patients who underwent LGE cardiac magnetic resonance imaging prior to ICD implantation were retrospectively included. Two semiautomatic algorithms, expectation maximization, weighted intensity, a priori information and a weighted border zone algorithm, were compared with a modified full-width half-maximum and a 2-3SD threshold-based algorithm (2-3SD). Hazard ratios were calculated per 1% increase in LGE. A total of 74 ICM and 34 NICM were followed for 63 months (1-140) and 52 months (0-133), respectively. ICM patients had 27 appropriate ICD events, and NICM patients had 7 ICD events. In ICM patients with primary prophylactic ICD, LGE border zone predicted ICD therapy in univariable and multivariable analysis measured by the expectation maximization, weighted intensity, a priori information, weighted border zone, and modified full-width half-maximum algorithms (hazard ratios 1.23, 1.22, and 1.05, respectively; P<0.05; negative predictive value 92%). For NICM, total LGE by all 4 methods was the strongest predictor (hazard ratios, 1.03-1.04; P<0.05), though the number of events was small.Appropriate ICD therapy can be predicted in ICM patients with primary prevention ICD by quantifying the LGE border zone. In NICM patients, total LGE but not LGE border zone had predictive value for ICD therapy. However, the algorithms used affects the predictive value of these measures.CONCLUSIONSAppropriate ICD therapy can be predicted in ICM patients with primary prevention ICD by quantifying the LGE border zone. In NICM patients, total LGE but not LGE border zone had predictive value for ICD therapy. However, the algorithms used affects the predictive value of these measures. |
| Author | Chaudhry, Uzma Heiberg, Einar Jablonowski, Robert van der Pals, Jesper Arheden, Håkan Engblom, Henrik Borgquist, Rasmus Wu, Katherine C Carlsson, Marcus |
| Author_xml | – sequence: 1 givenname: Robert surname: Jablonowski fullname: Jablonowski, Robert organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 2 givenname: Uzma surname: Chaudhry fullname: Chaudhry, Uzma organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 3 givenname: Jesper surname: van der Pals fullname: van der Pals, Jesper organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 4 givenname: Henrik surname: Engblom fullname: Engblom, Henrik organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 5 givenname: Håkan surname: Arheden fullname: Arheden, Håkan organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 6 givenname: Einar surname: Heiberg fullname: Heiberg, Einar organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 7 givenname: Katherine C surname: Wu fullname: Wu, Katherine C organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 8 givenname: Rasmus surname: Borgquist fullname: Borgquist, Rasmus organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.) – sequence: 9 givenname: Marcus surname: Carlsson fullname: Carlsson, Marcus email: Marcus.Carlsson@med.lu.se organization: From the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.). Marcus.Carlsson@med.lu.se |
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| Keywords | implanted cardioverter defibrillator ischemic cardiomyopathy late gadolinium enhancement nonischemic cardiomyopathy cardiac magnetic resonance imaging |
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| Title | Cardiovascular Magnetic Resonance to Predict Appropriate Implantable Cardioverter Defibrillator Therapy in Ischemic and Nonischemic Cardiomyopathy Patients Using Late Gadolinium Enhancement Border Zone: Comparison of Four Analysis Methods |
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