Ying Xiong1, Yi Sui2,3, Shun Zhang1, Xiaohong Joe Zhou2,3, Shaolin Yang3,4, Yang Fan5, Qiang Zhang6, Wenzhen Zhu7. 1. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan, 430030, People's Republic of China. 2. Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, USA. 3. Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA. 4. Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA. 5. GE Healthcare, Beijing, People's Republic of China. 6. Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan, 430030, People's Republic of China. zhangqiang_glia@126.com. 7. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan, 430030, People's Republic of China. zhuwenzhen8612@163.com.
Abstract
OBJECTIVES: To investigate brain microstructural changes in white matter and gray matter of type 2 diabetes mellitus (T2DM) patients using diffusion kurtosis imaging. METHODS: Diffusion kurtosis imaging (b values = 0, 1250, and 2500 s/mm2) was performed for 30 T2DM patients and 28 controls. FMRIB Software Library with tract-based spatial statistics was used to analyze intergroup differences in fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), axial kurtosis (K∥), and radial kurtosis (K⊥) of multiple white matter regions. Atlas-based ROI analysis was conducted in gray matter structures and some fiber tracts. Correlations between MK changes and clinical measurements were determined. RESULTS: In whole-brain tract-based spatial statistics analysis, T2DM patients exhibited abnormalities in 29.6%, 30.4%, 35.4%, 10.5%, and 26.0% of white matter regions as measured by FA, MD, MK, K∥, and K⊥, respectively, when compared to the controls. MK reduction was contributed more by the decreased K⊥. In atlas-based analysis, MK detected more ROIs (27/48) with white matter microstructural changes than FA (13/48) and MD (17/48). MK decreased in bilateral thalamus and caudate, while FA showed statistically significant difference only in the left caudate. MK values negatively correlated with disease duration in the genu of corpus callosum and anterior corona radiata (R = -0.512 and -0.459) and positively correlated with neuropsychological scores in the cingulum (hippocampus) (R = 0.466 and 0.440). CONCLUSIONS: Diffusion kurtosis imaging detects more brain regions with white matter and gray matter microstructural alterations of T2DM patients than DTI metrics. It provides valuable information for studying the pathology of diabetic encephalopathy and may lead to better imaging biomarkers for monitoring disease progression. KEY POINTS: • Diffusion kurtosis imaging detects more brain regions with microstructural alterations in white matter and gray matter of T2DM patients than DTI. • Mean kurtosis changes are associated with disease severity and impaired neuropsychological function in T2DM. • Diffusion kurtosis imaging demonstrates potential to assess cognitive impairment in T2DM patients and predict disease progression.
OBJECTIVES: To investigate brain microstructural changes in white matter and gray matter of type 2 diabetes mellitus (T2DM) patients using diffusion kurtosis imaging. METHODS: Diffusion kurtosis imaging (b values = 0, 1250, and 2500 s/mm2) was performed for 30 T2DM patients and 28 controls. FMRIB Software Library with tract-based spatial statistics was used to analyze intergroup differences in fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), axial kurtosis (K∥), and radial kurtosis (K⊥) of multiple white matter regions. Atlas-based ROI analysis was conducted in gray matter structures and some fiber tracts. Correlations between MK changes and clinical measurements were determined. RESULTS: In whole-brain tract-based spatial statistics analysis, T2DM patients exhibited abnormalities in 29.6%, 30.4%, 35.4%, 10.5%, and 26.0% of white matter regions as measured by FA, MD, MK, K∥, and K⊥, respectively, when compared to the controls. MK reduction was contributed more by the decreased K⊥. In atlas-based analysis, MK detected more ROIs (27/48) with white matter microstructural changes than FA (13/48) and MD (17/48). MK decreased in bilateral thalamus and caudate, while FA showed statistically significant difference only in the left caudate. MK values negatively correlated with disease duration in the genu of corpus callosum and anterior corona radiata (R = -0.512 and -0.459) and positively correlated with neuropsychological scores in the cingulum (hippocampus) (R = 0.466 and 0.440). CONCLUSIONS: Diffusion kurtosis imaging detects more brain regions with white matter and gray matter microstructural alterations of T2DM patients than DTI metrics. It provides valuable information for studying the pathology of diabetic encephalopathy and may lead to better imaging biomarkers for monitoring disease progression. KEY POINTS: • Diffusion kurtosis imaging detects more brain regions with microstructural alterations in white matter and gray matter of T2DM patients than DTI. • Mean kurtosis changes are associated with disease severity and impaired neuropsychological function in T2DM. • Diffusion kurtosis imaging demonstrates potential to assess cognitive impairment in T2DM patients and predict disease progression.
Entities:
Keywords:
Diffusion kurtosis imaging; Diffusion tensor imaging; Gray matter; Type 2 diabetes mellitus; White matter
Authors: Abdulmajeed Alotaibi; Christopher Tench; Rebecca Stevenson; Ghadah Felmban; Amjad Altokhis; Ali Aldhebaib; Rob A Dineen; Cris S Constantinescu Journal: Brain Sci Date: 2021-01-22