Evaluation of the diffusion MRI white matter tract integrity model using myelin histology and Monte-Carlo simulations
Zihan Zhou,
Qiqi Tong,
Lei Zhang,
Qiuping Ding,
Hui Lu,
Laura E. Jonkman,
Junye Yao,
Hongjian He,
Keqing Zhu,
Jianhui Zhong
Affiliations
Zihan Zhou
Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
Qiqi Tong
Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
Lei Zhang
China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China; Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, China
Qiuping Ding
Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
Hui Lu
China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China
Laura E. Jonkman
Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands
Junye Yao
Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
Hongjian He
Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China; Corresponding authors.
Keqing Zhu
China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China; Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, China; Corresponding authors.
Jianhui Zhong
Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China; Department of Imaging Sciences, University of Rochester, United States
Quantitative evaluation of brain myelination has drawn considerable attention. Conventional diffusion-based magnetic resonance imaging models, including diffusion tensor imaging and diffusion kurtosis imaging (DKI),11 AD: Axial diffusivity; AK: Axial kurtosis; AVF: Axonal volume fraction; AWF: Axonal Water Fraction; DTI: Diffusion Tensor Imaging; DKI: Diffusion Kurtosis Imaging; dMRI: Diffusion magnetic resonance imaging; TE: Echo time; FOV: Field-of-view; FA: Fractional anisotropy; LFB: Luxor fast blue; MD: Mean diffusivity; MK: Mean kurtosis; MRI: Magnetic resonance imaging; MVF: Myelin volume fraction; PLP: Proteolipid protein; RESOLVE: Readout segmentation of long variable echo train; RD: Radial diffusivity; RK: Radial kurtosis; TR: Repetition time; ROI: Region-of-interest; WM: White matter; WMTI: White Matter Tract Integrity. have been used to infer the microstructure and its changes in neurological diseases. White matter tract integrity (WMTI) was proposed as a biophysical model to relate the DKI-derived metrics to the underlying microstructure. Although the model has been validated on ex vivo animal brains, it was not well evaluated with ex vivo human brains. In this study, histological samples (namely corpus callosum) from postmortem human brains have been investigated based on WMTI analyses on a clinical 3T scanner and comparisons with gold standard myelin staining in proteolipid protein and Luxol fast blue. In addition, Monte Carlo simulations were conducted to link changes from ex vivo to in vivo conditions based on the microscale parameters of water diffusivity and permeability. The results show that WMTI metrics, including axonal water fraction AWF, radial extra-axonal diffusivity De⊥, and intra-axonal diffusivity Dawere needed to characterize myelin content alterations. Thus, WMTI model metrics are shown to be promising candidates as sensitive biomarkers of demyelination.
