A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging

MAGMA. 2016 Apr;29(2):155-95. doi: 10.1007/s10334-015-0521-4. Epub 2016 Jan 25.

Abstract

Cardiovascular magnetic resonance (CMR) has become a key imaging modality in clinical cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac chambers and great vessels. A wide range of CMR sequences have been developed to assess various aspects of cardiac structure and function, and significant advances have also been made in terms of imaging quality and acquisition times. A lot of research has been dedicated to the development of global and regional quantitative CMR indices that help the distinction between health and pathology. The goal of this review paper is to discuss the structural and functional CMR indices that have been proposed thus far for clinical assessment of the cardiac chambers. We include indices definitions, the requirements for the calculations, exemplar applications in cardiovascular diseases, and the corresponding normal ranges. Furthermore, we review the most recent state-of-the art techniques for the automatic segmentation of the cardiac boundaries, which are necessary for the calculation of the CMR indices. Finally, we provide a detailed discussion of the existing literature and of the future challenges that need to be addressed to enable a more robust and comprehensive assessment of the cardiac chambers in clinical practice.

Keywords: Cardiac segmentation; Clinical assessment; MRI.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Heart / diagnostic imaging*
  • Heart Diseases / diagnostic imaging*
  • Heart Diseases / pathology*
  • Heart Function Tests / methods*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods
  • Imaging, Three-Dimensional / methods
  • Machine Learning
  • Magnetic Resonance Imaging, Cine / methods*
  • Myocardium / pathology*
  • Pattern Recognition, Automated / methods
  • Reproducibility of Results
  • Sensitivity and Specificity