Non-contrast estimation of diffuse myocardial fibrosis with dual energy CT: A phantom study

Vidhya Kumar, Kevin E. McElhanon, James K. Min, Xin He, Zhaobin Xu, Eric X. Beck, Orlando P. Simonetti, Noah Weisleder, Subha V. Raman

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)74-80
Number of pages7
JournalJournal of Cardiovascular Computed Tomography
Volume12
Issue number1
DOIs
StatePublished - Jan 2018

Bibliographical note

Publisher Copyright:
© 2017

Funding

The authors have no relevant financial conflicts of interest to disclose. This work was supported in part by the National Institutes of Health ( 5R01HL116533 ) and an OSU Davis Heart and Lung Research Institute Trifit Award.

FundersFunder number
National Institutes of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)R01HL116533

    Keywords

    • Dual energy computed tomography
    • Myocardial fibrosis

    ASJC Scopus subject areas

    • Radiology Nuclear Medicine and imaging
    • Cardiology and Cardiovascular Medicine

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