Simultaneous multi-slice readout-segmented echo planar imaging for accelerated diffusion-weighted imaging of the breast

Eur J Radiol. 2016 Jan;85(1):274-278. doi: 10.1016/j.ejrad.2015.10.009. Epub 2015 Oct 23.

Abstract

Objectives: Readout-segmented echo planar imaging (rs-EPI) significantly reduces susceptibility artifacts in diffusion-weighted imaging (DWI) of the breast compared to single-shot EPI but is limited by longer scan times. To compensate for this, we tested a new simultaneous multi-slice (SMS) acquisition for accelerated rs-EPI.

Materials and methods: After approval by the local ethics committee, eight healthy female volunteers (age, 38.9 ± 13.1 years) underwent breast MRI at 3T. Conventional as well as two-fold (2× SMS) and three-fold (3× SMS) slice-accelerated rs-EPI sequences were acquired at b-values of 50 and 800 s/mm(2). Two independent readers analyzed the apparent diffusion coefficient (ADC) in fibroglandular breast parenchyma. The signal-to-noise ratio (SNR) was estimated based on the subtraction method. ADC and SNR were compared between sequences by using the Friedman test.

Results: The acquisition time was 4:21 min for conventional rs-EPI, 2:35 min for 2× SMS rs-EPI and 1:44 min for 3× SMS rs-EPI. ADC values were similar in all sequences (mean values 1.62 × 10(-3)mm(2)/s, p=0.99). Mean SNR was 27.7-29.6, and no significant differences were found among the sequences (p=0.83).

Conclusion: SMS rs-EPI yields similar ADC values and SNR compared to conventional rs-EPI at markedly reduced scan time. Thus, SMS excitation increases the clinical applicability of rs-EPI for DWI of the breast.

Keywords: Blipped CAIPIRINHA; Breast; Diffusion-weighted imaging; Readout-segmented echo planar imaging; Simultaneous multi-slice.

MeSH terms

  • Adult
  • Artifacts
  • Breast / pathology*
  • Breast Neoplasms / pathology*
  • Diffusion Magnetic Resonance Imaging / methods*
  • Echo-Planar Imaging / methods*
  • Female
  • Humans
  • Middle Aged
  • Observer Variation
  • Reproducibility of Results
  • Signal-To-Noise Ratio
  • Subtraction Technique