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Estimation of myocardial fibrosis in humans with dual energy CT
Affiliation:1. The Ohio State University Davis Heart and Lung Research Institute, 473 W. 12th Ave, Columbus, OH, 43210, USA;2. University of Maryland School of Public Health, Department of Epidemiology and Biostatistics, College Park, MD, 20742, USA;1. Dept. Radiology, Innsbruck Medical University, Austria;2. Dept. Internal Medicine III, Cardiology, Innsbruck Medical University, Austria;1. Radiology and Imaging Sciences - National Institutes of Health Clinical Center, Bethesda, MD, USA;2. Department of Imaging and Pathology, Medical Imaging Research Centre, University Hospitals Leuven, Leuven, Belgium;3. Department of Radiological Sciences, University of California, Los Angeles, CA, USA;4. Department of Bioengineering, University of California, Los Angeles, CA, USA;5. Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, WI, USA
Abstract:BackgroundThe current clinical standard for in vivo imaging of myocardial fibrosis is contrast-enhanced cardiac magnetic resonance (CMR). We sought to validate a novel non-contrast dual energy computed tomography (DECT) method to estimate myocardial fibrosis in patients undergoing CMR with contrast.MethodsAll subjects underwent non-contrast, prospectively-triggered cardiac DECT on a single source scanner with interleaved acquisition between tube voltages of 80 and 140 kVp. Monochromatic images were reconstructed at 11 energies spanning 40–140 keV; a region of interest (ROI) was drawn in the mid-inferoseptal segment, recording mean attenuation value in the ROI, at each energy level. Comparison was made to data from single energy (70 keV) image data. Linear discriminant analysis (LDA) was performed to compare the predictive capability of single vs. multi-energy inferoseptal segment CT attenuation on myocardial fibrosis by both visually assessed LGE (absent/present fibrosis) and CMR T1 mapping-derived myocardial extracellular volume fraction (ECV).ResultsThe multi-energy CT/LDA approach performed better than a single energy approach to discriminate among LGE-CMR classes of present/absence myocardial fibrosis severity, demonstrating correct classification rates of 89% and 71%, respectively. The multi-energy CT/LDA approach also performed better in correctly discriminating normal from elevated ECV, doing so in 89% of patients vs. correct distinction of normal/elevated ECV in only 70% using the single energy approach.ConclusionsNon-contrast cardiac DECT with multi-energy analysis better classifies myocardial fibrosis and extracellular volume compared to what is feasible with non-contrast single energy cardiac CT. These data support further evaluation of this approach to noninvasively assess myocardial fibrosis.
Keywords:Dual energy computed tomography  Myocardial fibrosis
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