Farshid Sepehrband1,2, Kieran O’Brien1,3, and Markus Barth1
1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 2Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States, 3Siemens Healthcare Pty Ltd, Brisbane, Australia
Several diffusion-weighted MRI
techniques for modeling tissue microstructure have been developed and validated
during the past two decades. While offering various neuroanatomical inferences,
these techniques differ in their proposed optimal acquisition design, which
impede clinicians and researchers to benefit from all potential inference
methods, particularly when limited time is available. We examined the
performance of the most common diffusion models with respect to acquisition
parameters at 7T when limiting the acquisition time to about 10 minutes. The most
balanced compromise among all combinations in terms of the robustness of the
estimates was a two-shell scheme with b-values of 1,000 and 2,500 s/mm2
with 75 diffusion-encoding gradients, 25 and 50 samples for low and high
b-values, respectively.
