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Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics

  • Jonathan D. Suever
  • , Gregory J. Wehner
  • , Christopher M. Haggerty
  • , Linyuan Jing
  • , Sean M. Hamlet
  • , Cassi M. Binkley
  • , Sage P. Kramer
  • , Andrea C. Mattingly
  • , David K. Powell
  • , Kenneth C. Bilchick
  • , Frederick H. Epstein
  • , Brandon K. Fornwalt

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

Background: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30–40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis. Methods and Results: We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30–40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing. Conclusions: Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow.

Original languageEnglish
Article number94
JournalJournal of Cardiovascular Magnetic Resonance
Volume16
Issue number1
DOIs
StatePublished - Dec 5 2014

Bibliographical note

Publisher Copyright:
© 2014 © 2014 THE AUTHORS. Published by Elsevier Inc on behalf of the Society for Cardiovascular Magnetic Resonance

Funding

This work was supported by a National Institutes of Health (NIH) Director’s Early Independence Award (DP5 OD-012132); a grant from the National Institute of General Medical Science (8 P20 GM103527) of the National Institutes of Health; the University of Kentucky Cardiovascular Research Center, grant UL1TR000117 from the National Center for Research Resources (NCRR), funded by the Office of the Director, National Institutes of Health and supported by the NIH Roadmap for Medical Research. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding sources.

FundersFunder number
Department of Pediatrics and Saha Cardiovascular Research Center, University of KentuckyP20 GM103527, T32 HL091812, KL2 TR000116, UL1 TR000117, DP5 OD012132, S10 RR029541, KL2 RR033171
National Institutes of Health (NIH)DP5 OD-012132
National Institutes of Health (NIH)
National Institute of General Medical Sciences8 P20 GM103527
National Institute of General Medical Sciences
National Center for Research Resources
Office of the Director
Saha Cardiovascular Research Center, University of Kentucky
National Center for Advancing Translational Sciences (NCATS)UL1TR000117
National Center for Advancing Translational Sciences (NCATS)

    Keywords

    • Cardiac mechanics
    • Cardiovascular magnetic resonance
    • DENSE

    ASJC Scopus subject areas

    • Radiological and Ultrasound Technology
    • Radiology Nuclear Medicine and imaging
    • Cardiology and Cardiovascular Medicine
    • Family Practice

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