Imaging 4D morphology and dynamics of mitral annulus in humans using cardiac cine MR feature tracking

Sci Rep. 2018 Jan 8;8(1):81. doi: 10.1038/s41598-017-18354-2.

Abstract

Feature tracking in cine cardiac magnetic resonance (CMR) is a quantitative technique to assess heart structure and function. We investigated 4-dimensional (4D) dynamics and morphology of the mitral annulus (MA) using a novel tracking system based on radially rotational long-axis cine CMR series. A total of 30 normal controls and patients with mitral regurgitation were enrolled. The spatiotemporal changes of the MA were characterized by an in-house developed program. Dynamic and morphological parameters extracted from all 18 radial slices were used as references and were compared with those from subsequently generated sub-datasets with different degrees of sparsity. An excellent agreement was found among all datasets including routine 2-, 3- and 4-chamber views for MA dynamics such as peak systolic velocity (Sm) and mitral annular plane systolic excursion (MAPSE). MA morphology for size and shape was addressed adequately by as few as 6 radial slices, but poorly by only three routine views. Patients with regurgitation showed significantly reduced mitral dynamics and mild annular deformation, which was consistent between three routine views and 18 reference slices. In conclusion, feature tracking cine CMR provided a comprehensive and distinctive profile for 4D MA dynamics and morphology, which may help in studying different cardiac diseases.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Case-Control Studies
  • Heart Function Tests
  • Humans
  • Image Processing, Computer-Assisted
  • Imaging, Three-Dimensional* / methods
  • Magnetic Resonance Imaging, Cine* / methods
  • Middle Aged
  • Mitral Valve / diagnostic imaging*
  • Mitral Valve / pathology*
  • Mitral Valve Insufficiency / diagnostic imaging*
  • Mitral Valve Insufficiency / pathology*
  • Mitral Valve Insufficiency / physiopathology
  • Observer Variation
  • Reproducibility of Results
  • Severity of Illness Index