Background: Estimation of diffuse myocardial fibrosis, substrate for adverse events such as heart failure and arrhythmias in patients with various cardiac disorders, is presently done by histopathology or cardiac magnetic resonance. We sought to develop a non-contrast method to estimate the amount of diffuse myocardial fibrosis leveraging dual energy computed tomography (DECT) in phantoms and a suitable small animal model.
Methods and results: Phantoms consisted of homogenized bovine myocardium with varying amounts of Type 1 collagen. Fifteen mice underwent sham surgery, no procedure, or transverse aortic constriction (TAC) for 5 or 8 weeks to produce moderate or severe fibrosis, respectively. Phantoms and ex vivo mouse hearts were imaged on a single source, DECT scanner equipped with kVp switching. Monochromatic images were reconstructed at 40-140 keV. Linear discriminant analysis (LDA) was performed on mean myocardial CT numbers derived from single energy (70 keV) images as well as images reconstructed across multiple energies. Classification of myocardial fibrosis severity as low, moderate or severe was more often correct using the multi-energy CT/LDA approach vs. single energy CT/LDA in both phantoms (80.0% vs. 70.0%) and mice (93.3% vs. 33.3%).
Conclusions: DECT myocardial imaging with multi-energy analysis better classifies myocardial fibrosis severity compared to a single energy-based approach. Non-contrast DECT can accurately and non-invasively estimate the extent of diffuse myocardial fibrosis in phantom and animal models. These data support further evaluation of this approach for in vivo myocardial fibrosis estimation.
Keywords: Dual energy computed tomography; Myocardial fibrosis.
Copyright © 2017. Published by Elsevier Inc.