In vivo 3D high resolution cardiac diffusion weighted MRI: a motion compensated diffusion-prepared balanced steady-state free precession approach

Nguyen, Christopher; Fan, Zhaoyang; Sharif, Behzad; He, Yi; Dharmakumar, Rohan; Berman, Daniel S.; Li, Debiao

doi:10.1186/1532-429x-16-s1-o83

Cited by 1 publication

(1 citation statement)

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“…Nevertheless, there has been considerable recent progress towards achieving higher-resolution diffusion MRI (2). On the data-acquisition side, some of the major advances have been driven by the use of simultaneous multi-slice (SMS) (3)(4)(5) and volumetric (6)(7)(8)(9)(10)(11)(12) excitation methods, which yield substantially higher SNR efficiency relative to standard 2D spatial encoding methods. Related approaches acquire multiple sets of low-reslution high-SNR images with RF encoding, and computationally fuse these low-resolution images together into a "super-resolved" high resolution image (13)(14)(15)(16)(17)(18)(19)(20).…”

Section: Introductionmentioning

confidence: 99%

Fast submillimeter diffusion MRI using gSlider‐SMS and SNR‐enhancing joint reconstruction

Haldar

Liu

Liao

et al. 2020

Magnetic Resonance in Med

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Purpose:We evaluate a new approach for achieving diffusion MRI data with high spatial resolution, large volume coverage, and fast acquisition speed. Theory and Methods: A recent method called gSlider-SMS enables whole-brain submillimeter diffusion MRI with high signal-to-noise ratio (SNR) efficiency.However, despite the efficient acquisition, the resulting images can still suffer from low SNR due to the small size of the imaging voxels. This work proposes to mitigate the SNR problem by combining gSlider-SMS with a regularized SNR-enhancing reconstruction approach. Results: Illustrative results show that, from gSlider-SMS data acquired over a span of only 25 minutes on a 3T scanner, the proposed method is able to produce 71 MRI images (64 diffusion encoding orientations with b = 1500 s/mm 2 , and 7 images without diffusion weighting) of the entire in vivo human brain with nominal 0.66 mm spatial resolution. Using data acquired from 75 minutes of acquisition as a gold standard reference, we demonstrate that the proposed SNR-enhancement procedure leads to substantial improvements in estimated diffusion parameters compared to conventional gSlider reconstruction. Results also demonstrate that the proposed method has advantages relative to denoising methods based on low-rank matrix modeling. A theoretical analysis of the trade-off between spatial resolution and SNR suggests that the proposed approach has high efficiency.Conclusions: The combination of gSlider-SMS with advanced regularized reconstruction enables high-resolution quantitative diffusion MRI from a relatively fast acquisition. K E Y W O R D Sconstrained reconstruction, denoising, diffusion MRI, fast imaging, high resolution

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