Valentina O Puntmann1, Gerry Carr-White2, Andrew Jabbour3, Chung-Yao Yu3, Rolf Gebker4, Sebastian Kelle4, Rocio Hinojar5, Adelina Doltra4, Niharika Varma6, Nicholas Child6, Toby Rogers7, Gonca Suna8, Eduardo Arroyo Ucar9, Ben Goodman9, Sitara Khan8, Darius Dabir10, Eva Herrmann11, Andreas M Zeiher12, Eike Nagel13. 1. Guys and St Thomas' NHS Trust, London, England; King's College Hospital NHS Trust, London, England; Department of Cardiology, University Hospital Frankfurt, Frankfurt-am Main, Germany; Department of Cardiac Imaging, King's College London, London, England. Electronic address: vppapers@icloud.com. 2. Guys and St Thomas' NHS Trust, London, England; King's College Hospital NHS Trust, London, England. 3. St Vincent's University, Sydney, Australia. 4. German Heart Institute Berlin, Berlin, Germany. 5. Guys and St Thomas' NHS Trust, London, England; Department of Cardiology, University Hospital Ramón y Cajal, Madrid, Spain. 6. Guys and St Thomas' NHS Trust, London, England; Department of Cardiac Imaging, King's College London, London, England. 7. King's College Hospital NHS Trust, London, England; Department of Cardiac Imaging, King's College London, London, England. 8. King's College Hospital NHS Trust, London, England; Cardiovascular Division, King's College London, London, England. 9. Guys and St Thomas' NHS Trust, London, England. 10. Guys and St Thomas' NHS Trust, London, England; Department of Radiology, University of Bonn, Bonn, Germany. 11. Institute of Biostatistics and Mathematical Modelling at Goethe University Frankfurt; Frankfurt am Main, Germany. 12. Department of Cardiology, University Hospital Frankfurt, Frankfurt-am Main, Germany. 13. Guys and St Thomas' NHS Trust, London, England; King's College Hospital NHS Trust, London, England; Department of Cardiology, University Hospital Frankfurt, Frankfurt-am Main, Germany; Department of Cardiac Imaging, King's College London, London, England; Institute of Experimental and Translational Cardiac Imaging, DZHK Centre for Cardiovascular Imaging, Goethe University Frankfurt, Frankfurt am Main, Germany.
Abstract
OBJECTIVES: The study sought to examine prognostic relevance of T1 mapping parameters (based on a T1 mapping method) in nonischemic dilated cardiomyopathy (NIDCM) and compare them with conventional markers of adverse outcome. BACKGROUND: NIDCM is a recognized cause of poor clinical outcome. NIDCM is characterized by intrinsic myocardial remodeling due to complex pathophysiological processes affecting myocardium diffusely. Lack of accurate and noninvasive characterization of diffuse myocardial disease limits recognition of early cardiomyopathy and effective clinical management in NIDCM. Cardiac magnetic resonance (CMR) supports detection of diffuse myocardial disease by T1 mapping. METHODS: This is a prospective observational multicenter longitudinal study in 637 consecutive patients with dilated NIDCM (mean age 50 years [interquartile range: 37 to 76 years]; 395 males [62%]) undergoing CMR with T1 mapping and late gadolinium enhancement (LGE) at 1.5-T and 3.0-T. The primary endpoint was all-cause mortality. A composite of heart failure (HF) mortality and hospitalization was a secondary endpoint. RESULTS: During a median follow-up period of 22 months (interquartile range: 19 to 25 months), we observed a total of 28 deaths (22 cardiac) and 68 composite HF events. T1 mapping indices (native T1 and extracellular volume fraction), as well as the presence and extent of LGE, were predictive of all-cause mortality and HF endpoint (p < 0.001 for all). In multivariable analyses, native T1 was the sole independent predictor of all-cause and HF composite endpoints (hazard ratio: 1.1; 95% confidence interval: 1.06 to 1.15; hazard ratio: 1.1; 95% confidence interval: 1.05 to 1.1; p < 0.001 for both), followed by the models including the extent of LGE and right ventricular ejection fraction, respectively. CONCLUSIONS: Noninvasive measures of diffuse myocardial disease by T1 mapping are significantly predictive of all-cause mortality and HF events in NIDCM. We provide a basis for a novel algorithm of risk stratification in NIDCM using a complementary assessment of diffuse and regional disease by T1 mapping and LGE, respectively.
OBJECTIVES: The study sought to examine prognostic relevance of T1 mapping parameters (based on a T1 mapping method) in nonischemic dilated cardiomyopathy (NIDCM) and compare them with conventional markers of adverse outcome. BACKGROUND:NIDCM is a recognized cause of poor clinical outcome. NIDCM is characterized by intrinsic myocardial remodeling due to complex pathophysiological processes affecting myocardium diffusely. Lack of accurate and noninvasive characterization of diffuse myocardial disease limits recognition of early cardiomyopathy and effective clinical management in NIDCM. Cardiac magnetic resonance (CMR) supports detection of diffuse myocardial disease by T1 mapping. METHODS: This is a prospective observational multicenter longitudinal study in 637 consecutive patients with dilated NIDCM (mean age 50 years [interquartile range: 37 to 76 years]; 395 males [62%]) undergoing CMR with T1 mapping and late gadolinium enhancement (LGE) at 1.5-T and 3.0-T. The primary endpoint was all-cause mortality. A composite of heart failure (HF) mortality and hospitalization was a secondary endpoint. RESULTS: During a median follow-up period of 22 months (interquartile range: 19 to 25 months), we observed a total of 28 deaths (22 cardiac) and 68 composite HF events. T1 mapping indices (native T1 and extracellular volume fraction), as well as the presence and extent of LGE, were predictive of all-cause mortality and HF endpoint (p < 0.001 for all). In multivariable analyses, native T1 was the sole independent predictor of all-cause and HF composite endpoints (hazard ratio: 1.1; 95% confidence interval: 1.06 to 1.15; hazard ratio: 1.1; 95% confidence interval: 1.05 to 1.1; p < 0.001 for both), followed by the models including the extent of LGE and right ventricular ejection fraction, respectively. CONCLUSIONS: Noninvasive measures of diffuse myocardial disease by T1 mapping are significantly predictive of all-cause mortality and HF events in NIDCM. We provide a basis for a novel algorithm of risk stratification in NIDCM using a complementary assessment of diffuse and regional disease by T1 mapping and LGE, respectively.
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