Abstract

Background

Diffusion kurtosis imaging (DKI) has the potential to provide microstructural insights into myelin and axonal pathology with additional kurtosis parameters. To our knowledge, few studies are available in the current literature using DKI by tract-based spatial statistics (TBSS) analysis in patients with multiple sclerosis (MS). The aim of this study is to assess the performance of commonly used parameters derived from DKI and diffusion tensor imaging (DTI) in detecting microstructural changes and associated pathology in relapsing remitting MS (RRMS).

Methods

Thirty-six patients with RRMS and 49 age and sex matched healthy controls underwent DKI. The brain tissue integrity was assessed by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr), mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Kr) of DKI and FA, MD, Da and Dr of DTI. Group differences in these parameters were compared using TBSS (P < 0.01, corrected). To compare the sensitivity of these parameters in detecting white matter (WM) damage, the percentage of the abnormal voxels based on TBSS analysis, relative to the whole skeleton voxels for each parameter was calculated.

Results

The sensitivities in detecting WM abnormality in RRMS were MK (78.2%) > Kr (76.7%) > Ka (53.5%) and Dr (78.8%) > MD (76.7%) > FA (74.1%) > Da (28.3%) for DKI, and Dr (79.8%) > MD (79.5%) > FA (68.6%) > Da (40.1%) for DTI. DKI-derived diffusion parameters (FA, MD, and Dr) were sensitive for detecting abnormality in WM regions with coherent fiber arrangement; however, the kurtosis parameters (MK and Kr) were sensitive to discern abnormalities in WM regions with complex fiber arrangement.

Conclusions

The diffusion and kurtosis parameters could provide complementary information for revealing brain microstructural damage in RRMS. Dr and DKI_Kr may be regarded as useful surrogate markers for reflecting pathological changes in RRMS.

Details

Title
Evaluation of patients with relapsing-remitting multiple sclerosis using tract-based spatial statistics analysis: diffusion kurtosis imaging
Author
Li, Hai Qing; Yin, Bo; Chao, Quan; Geng, Dao Ying; Yu, Hai; Yi Fang Bao; Liu, Jun; Yu Xin Li
Publication year
2018
Publication date
2018
Publisher
BioMed Central
e-ISSN
14712377
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2089867659
Copyright
Copyright © 2018. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.