Diffusion-prepared 3D gradient spin-echo sequence for improved oscillating gradient diffusion MRI

© 2020 International Society for Magnetic Resonance in Medicine..

PURPOSE: Oscillating gradient (OG) enables the access of short diffusion times for time-dependent diffusion MRI (dMRI); however, it poses several technical challenges for clinical use. This study proposes a 3D oscillating gradient-prepared gradient spin-echo (OGprep-GRASE) sequence to improve SNR and shorten acquisition time for OG dMRI on clinical scanners.

METHODS: The 3D OGprep-GRASE sequence consisted of global saturation, diffusion encoding, fat saturation, and GRASE readout modules. Multiplexed sensitivity-encoding reconstruction was used to correct the phase errors between multiple shots. We compared the scan time and SNR of the proposed sequence and the conventional 2D-EPI sequence for OG dMRI at 30-90-mm slice coverage. We also examined the time-dependent diffusivity changes with OG dMRI acquired at frequencies of 50 Hz and 25 Hz and pulsed-gradient dMRI at diffusion times of 30 ms and 60 ms.

RESULTS: The OGprep-GRASE sequence reduced the scan time by a factor of 1.38, and increased the SNR by 1.74-2.27 times compared with 2D EPI for relatively thick slice coverage (60-90 mm). The SNR gain led to improved diffusion-tensor reconstruction in the multishot protocols. Image distortion in 2D-EPI images was also reduced in GRASE images. Diffusivity measurements from the pulsed-gradient dMRI and OG dMRI showed clear diffusion-time dependency in the white matter and gray matter of the human brain, using both the GRASE and EPI sequences.

CONCLUSION: The 3D OGprep-GRASE sequence improved scan time and SNR and reduced image distortion compared with the 2D multislice acquisition for OG dMRI on a 3T clinical system, which may facilitate the clinical translation of time-dependent dMRI.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:85

Enthalten in:

Magnetic resonance in medicine - 85(2021), 1 vom: 05. Jan., Seite 78-88

Sprache:

Englisch

Beteiligte Personen:

Wu, Dan [VerfasserIn]
Liu, Dapeng [VerfasserIn]
Hsu, Yi-Cheng [VerfasserIn]
Li, Haotian [VerfasserIn]
Sun, Yi [VerfasserIn]
Qin, Qin [VerfasserIn]
Zhang, Yi [VerfasserIn]

Links:

Volltext

Themen:

3D-GRASE
Diffusion-time dependency
Journal Article
Oscillating gradient
Research Support, Non-U.S. Gov't
Signal-to-noise ratio | scan time

Anmerkungen:

Date Completed 10.05.2021

Date Revised 10.05.2021

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1002/mrm.28401

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM312205244