Evaluation of regional myocardial function using automated wall motion analysis of cine MR images: Contribution of parametric images, contraction times, and radial velocities

J Magn Reson Imaging. 2007 Oct;26(4):1127-32. doi: 10.1002/jmri.21103.

Abstract

Purpose: To develop fast and robust procedures for a clinical evaluation of regional myocardial contractile function.

Materials and methods: Parametric analysis of main motion was applied to steady-state free-precession (SSFP) cine MR images. From the time-signal intensity curve associated with each pixel, parametric maps of mean high and low amplitudes and transition times between muscle and cavity were automatically computed. Then, regional time to first contraction, T(fc), mean contraction time, T(mc) and radial component of the endocardial velocity, V(m) were estimated from these parametric maps and a user-defined endocardial end-diastolic contour. The method was applied to short-axis slices in 22 subjects: eight controls, 13 myocardial infarctions (MIs), and one left bundle branch block (LBBB).

Results: Typical patterns of normality and pathology on parametric maps are indicated. For controls, the mean values +/- standard deviations (SDs) of T(fc), T(mc), and V(m) were: 70 +/- 25 msec, 318 +/- 43 msec, and 4.6 +/- 1.8 cm second(-1). An apex to base gradient of T(fc), a significant septal delay in T(fc) and T(mc), and a decrease of V(m) between the lateral and septal walls were observed. For MI, T(fc) and T(mc) increased and V(m) decreased significantly in pathological segments. For LBBB, large delays were estimated in the septal wall.

Conclusion: The proposed method is promising for clinical assessment of regional wall contraction.

MeSH terms

  • Adult
  • Aged
  • Automation
  • Diastole
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging, Cine / methods*
  • Male
  • Middle Aged
  • Models, Statistical
  • Movement
  • Myocardial Contraction*
  • Myocardial Infarction / pathology*
  • Myocardium / pathology*
  • Reproducibility of Results
  • Time Factors