TY - JOUR
T1 - Diffusion-regularized susceptibility tensor imaging (DRSTI) of tissue microstructures in the human brain
AU - Bao, Lijun
AU - Xiong, Congcong
AU - Wei, Wenping
AU - Chen, Zhong
AU - van Zijl, Peter C.M.
AU - Li, Xu
N1 - Funding Information:
We thank the developers of STI_Suite and COSMOS_STI for sharing their toolboxes. This work was supported in part by NNSF of China under Grant 62071405, Natural Science Foundation of Fujian Province of China 2019J01047, NIH/NIBIB grant P41EB015909, and NNSF of China 11761141010, U1632274. In vivo human imaging was conducted at the F.M. Kirby Research Center for Functional Brain Imaging of Johns Hopkins University.
Funding Information:
We thank the developers of STI_Suite and COSMOS_STI for sharing their toolboxes. This work was supported in part by NNSF of China under Grant 62071405 , Natural Science Foundation of Fujian Province of China 2019J01047, NIH/NIBIB grant P41EB015909, and NNSF of China 11761141010 , U1632274 . In vivo human imaging was conducted at the F.M. Kirby Research Center for Functional Brain Imaging of Johns Hopkins University.
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2021/1
Y1 - 2021/1
N2 - Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.
AB - Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.
KW - Deep gray matter nuclei
KW - Fiber pathways
KW - In vivo human brain
KW - Susceptibility tensor imaging
KW - Tensor spectral decomposition
KW - Tissue microstructures
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U2 - 10.1016/j.media.2020.101827
DO - 10.1016/j.media.2020.101827
M3 - Article
C2 - 33166777
AN - SCOPUS:85095416557
SN - 1361-8415
VL - 67
JO - Medical image analysis
JF - Medical image analysis
M1 - 101827
ER -