Faculty Collaboration Database

High-resolution reduced field of view diffusion tensor imaging using spatially selective RF pulses. Magn Reson Med 2014 Dec;72(6):1668-79

Date

01/09/2014

Pubmed ID

24399609

Pubmed Central ID

PMC4090294

DOI

10.1002/mrm.25092

Scopus ID

2-s2.0-84911989663 (requires institutional sign-in at Scopus site)   9 Citations

Abstract

PURPOSE: Diffusion tensor imaging (DTI) plays a vital role in identifying white matter fiber bundles. Achievable imaging resolution and imaging time demands remain the major challenges in detecting small fiber bundles with current clinical DTI sequences.

METHODS: A novel reduced field of view ultra-high-resolution DTI technique named eZOOM (elliptically refocused zonally oblique multislice) was developed. A small circular disk was imaged using spatially selective radiofrequency (RF) pulses, reducing the imaging matrix size. The frequency profile of the spectral-spatial refocusing RF pulse provided intrinsic fat suppression, eliminating the need for fat saturation pulses.

RESULTS: Multislice DTI at a resolution of 0.35 × 0.35 mm in a celery fiber phantom was successfully performed by scanning an 8-cm field of view at 3T. An adequate diffusion-to-noise ratio (DNR >20) was achieved for a 25-min acquisition using a direct-sampling RF receiver. Human subjects (n = 7) were scanned at resolutions of 0.47 × 0.47 mm having a DNR <20 within a 75-min scanning time, requiring further enhancements to increase the signal-to-noise ratio.

CONCLUSIONS: The new eZOOM-DTI method offers multislice DTI at ultra-high imaging resolutions substantially exceeding those available with current echo-planar DTI techniques. Parallel and fast spin echo methods can be combined with eZOOM to improve SNR and DNR in humans.

Author List

Gaggl W, Jesmanowicz A, Prost RW

MESH terms used to index this publication - Major topics in bold

Adipose Tissue
Algorithms
Brain
Diffusion Tensor Imaging
Humans
Image Enhancement
Image Interpretation, Computer-Assisted
Phantoms, Imaging
Radio Waves
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Subtraction Technique
White Matter