Quantifying precision in cardiac diffusion tensor imaging with second-order motion-compensated convex optimized diffusion encoding

Magn Reson Med. 2018 Sep;80(3):1074-1087. doi: 10.1002/mrm.27107. Epub 2018 Feb 9.

Abstract

Purpose: To quantify the precision of in vivo cardiac DTI (cDTI) acquired with a spin echo, first- and second-order motion-compensated (M1M2), convex optimized diffusion encoding (CODE) sequence.

Methods: Free-breathing CODE-M1M2 cDTI were acquired in healthy volunteers (N = 10) at midsystole and diastole with 10 repeated acquisitions per phase. 95% confidence intervals of uncertainty in reconstructed diffusion tensor eigenvectors (E⃗1, E⃗2, E⃗3), mean diffusivity (MD), fractional anisotropy (FA), and tensor Mode were measured using a bootstrapping approach. Trends in observed tensor metric uncertainty were evaluated as a function of scan duration, image SNR, cardiac phase, and bulk motion artifacts.

Results: For midsystolic scans including 5 signal averages (scan time: ~5min), the median myocardial 95% confidence intervals of uncertainties were: E⃗1: 15.5 ± 1.2°, E⃗2: 31.2 ± 3.5°, E⃗3: 21.8 ± 3.1°, MD: 0.38 ± 0.02 × 10−3mm2/s, FA: 0.20 ± 0.01, and Mode: 1.10 ± 0.08. Uncertainty in all parameters increased for diastolic scans: E⃗1: 31.9 ± 7.1°, E⃗2: 59.6 ± 6.8°, E⃗3: 40.5 ± 6.4°, MD: 0.52 ± 0.09 × 10−3 mm2/s, FA: 0.23 ± 0.01, and Mode: 1.57 ± 0.11. Diastolic cDTI also reported higher MD (MDDIA = 1.91 ± 0.34 × 10−3 mm2/s vs. MDSYS = 1.58 ± 0.09 × 10−3 mm2/s, P = 8 × 10−3) and lower FA values (FADIA = 0.32 ± 0.06 vs. FASYS = 0.37 ± 0.03, P = 0.03).

Conclusion: cDTI precision improved with increasing nondiffusion-weighted (b = 0) image SNR, but gains were minimal for SNR ≥ 25 (~10 averages). cDTI precision was also sensitive to intershot bulk motion artifacts, which led to better precision for midsystolic imaging.

Keywords: cardiac MRI; cardiac diffusion; diffusion tensor imaging.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Anisotropy
  • Artifacts
  • Diastole
  • Diffusion Magnetic Resonance Imaging
  • Diffusion Tensor Imaging*
  • Heart / diagnostic imaging*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Likelihood Functions
  • Phantoms, Imaging
  • Reproducibility of Results
  • Respiration*
  • Signal-To-Noise Ratio