title: Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics.
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.
  
  
  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.
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Suever
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Wehner
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Haggerty
authors.forename: Linyuan
authors.initials: L
authors.lastname: Jing
authors.forename: Sean M
authors.initials: SM
authors.lastname: Hamlet
authors.forename: Cassi M
authors.initials: CM
authors.lastname: Binkley
authors.forename: Sage P
authors.initials: SP
authors.lastname: Kramer
authors.forename: Andrea C
authors.initials: AC
authors.lastname: Mattingly
authors.forename: David K
authors.initials: DK
authors.lastname: Powell
authors.forename: Kenneth C
authors.initials: KC
authors.lastname: Bilchick
authors.forename: Frederick H
authors.initials: FH
authors.lastname: Epstein
authors.affiliation: Department of Pediatrics and Saha Cardiovascular Research Center, University of Kentucky, Lexington, KY, USA. bkf@gatech.edu.
authors.forename: Brandon K
authors.initials: BK
authors.lastname: Fornwalt
mesh_terms: D000818:Animals; D001331:Automation; D001696:Biomechanical Phenomena; D004195:Disease Models, Animal; D006331:Heart Diseases / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007629:Kentucky; D019028:Magnetic Resonance Imaging, Cine; D051379:Mice; D009200:Myocardial Contraction; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D013314:Stress, Mechanical; D013997:Time Factors; D054159:Torsion, Mechanical; D016277:Ventricular Function, Left; D014768:Virginia; D057188:Workflow