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Xu W, Sun X, Jiang H, Wang X, Wang B, Niu Q, Meng H, Du J, Yang G, Liu B, Zhang H, Tan Y. Diffusion Kurtosis Imaging in Evaluating the Mild Cognitive Impairment of Occupational Aluminum Workers. Acad Radiol 2023; 30:2225-2233. [PMID: 36690563 DOI: 10.1016/j.acra.2022.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 12/02/2022] [Accepted: 12/02/2022] [Indexed: 01/23/2023]
Abstract
RATIONALE AND OBJECTIVES To investigate whether diffusion kurtosis imaging (DKI) can distinguish mild cognitive impairment (MCI) from normal controls (NC) in aluminum (Al)-exposed workers, and to explore the association of DKI with cognitive performance and plasma Al concentration. MATERIALS AND METHODS 28 patients with MCI and 25 NC at Al factory were enrolled in this study. All subjects underwent conventional MRI and DKI scans. The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusivity (MD) and fractional anisotropy (FA) parameters of the hippocampus, substantia nigra, red nucleus, thalamus, anterior cingulate gyrus, genu and crus of the corpus callosum, frontal, parietal and temporal lobe were measured. To compare the parameters between the two groups, the Mann-Whitney rank sum test was used. The correlation of parameter values with cognitive performance and plasma Al concentration was analyzed using Spearman correlation analysis. The receiver operating characteristic (ROC) curve and the Z-scores were used to evaluate the diagnostic efficacy of each parameter. RESULTS Compared with the NC group, the MK, Ka, Kr, and FA values in the MCI group were significantly decreased, and the MD values were significantly increased (p<0.05). For the diagnosis of MCI, MK in the right hippocampus showed the largest AUC (0.924). The MK, Kr, MD and FA values were correlated with the Montreal Cognitive Assessment (MoCA) scores, and MK values in the right hippocampus showed the greatest correlation with MoCA scores (r=0.744, p <0.001). Plasma Al in the MCI group was higher than that in the NC group, although there was no significant difference in plasma Al between the two groups (p=0.057). There was no correlation between DKI parameters and plasma Al. CONCLUSION The DKI method might be a sensitive imaging biomarker to discriminate MCI from NC, and could preliminarily assess the severity of cognitive impairment in Al-exposed workers. MK in the right hippocampus appeared to be the best independent predictor. The mechanism of cognitive decline is an important content of aluminum exposure research. This study indicates that the DKI technique could provide valuable information for the diagnosis of MCI.
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Affiliation(s)
- Wenji Xu
- College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Xiangru Sun
- College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Haoru Jiang
- College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Xiaochun Wang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Bin Wang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Qiao Niu
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Huaxing Meng
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Jiangfeng Du
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Guoqiang Yang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Bo Liu
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yan Tan
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China.; Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China..
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Jin P, Pan Y, Pan Z, Xu J, Lin M, Sun Z, Chen M, Xu M. Alzheimer-like brain metabolic and structural features in cholesterol-fed rabbit detected by magnetic resonance imaging. Lipids Health Dis 2018; 17:61. [PMID: 29587752 PMCID: PMC5870103 DOI: 10.1186/s12944-018-0705-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2017] [Accepted: 03/09/2018] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Hypercholesterolemia is known to increase the risk of AD in later life, the purpose of this study is to illustrate brain metabolic and structural changes in a cholesterol-fed rabbit model of Alzheimer's Disease (AD) by using clinical 3 T Magnetic Resonance Imaging (MRI). METHODS The Institutional Animal Care and Use Committee of Zhejiang Chinese Medical University approved the study. Totally 16 Japanese White Rabbits (JWR) were randomly divided into 2 groups including normal control group fed with routine diet (group NC) and high cholesterol diet group (group CD) fed a 2% cholesterol diet with 0.24 ppm copper in the drinking water for 12 weeks. Magnetic resonance spectroscopy (MRS) and structural image of rabbit brain were performed by using a 3 Tesla (T) MRI scanner with an 8 channel Rabbit coil. The chemical metabolites were identified by LC Model including N-acetylaspartate (NAA), creatine (Cr), glutamate (Glu), glutamine (Gln), Glycerophosphatidylcholine (GPC), phosphorylcholine (PCH), and myoinositol (MI). The relative concentrations (/Cr) were analyzed. Additionally, Amyloid-β (Aβ) accumulation in the brain was measured postmortem. For comparisons of MR and Aβ data between groups, two-tailed t-tests were performed. RESULTS The ratio of NAA/Cr (0.76 ± 0.10) and Glu/Cr (0.90 ± 0.14) in group CD were lower than those in the group NC (0.87 ± 0.06, 1.13 ± 0.22, respectively, P < 0.05). Compared to the group NC (2.88 ± 0.09 cm3, 0.63 ± 0.08 cm3, respectively), the cortical and hippocampal volumes (2.60 ± 0.14 cm3 and 0.47 ± 0.07 cm3, respectively) of rabbits brain decreased in the group CD while the third and lateral ventricular volumes enlarged (44.56 ± 6.01 mm3 vs 31.40 ± 6.14 mm3, 261.40 ± 30.98 mm3 vs 153.81 ± 30.08 mm3, P < 0.05). These metabolic and structural changes were additionally accompanied by the significant increase of Aβ1-42 in the cortex and hippocampus (163.60 ± 16.26 pg/mg and 215.20 ± 69.86 pg/mg, respectively, P < 0.05). CONCLUSION High cholesterol diet can induce the brain metabolic and structural changes of the rabbit including lowered level of NAA and Glu and the atrophy of the brain which were similar to those of human AD.
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Affiliation(s)
- Ping Jin
- The First Affiliated Hospital of Zhejiang Chinese Medical University, No. 54 Youdian Road, Shangcheng District, Hangzhou, Zhejiang 310006 People’s Republic of China
- The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang China
| | - Yongming Pan
- Laboratory Animal Research Center/Comparative Medical Research Institute, Zhejiang Chinese Medical University, No 548 Binwen Road, Binjiang District, Hangzhou, 310053 China
| | - Zhiyong Pan
- The First Affiliated Hospital of Zhejiang Chinese Medical University, No. 54 Youdian Road, Shangcheng District, Hangzhou, Zhejiang 310006 People’s Republic of China
| | - Jianqin Xu
- Laboratory Animal Research Center/Comparative Medical Research Institute, Zhejiang Chinese Medical University, No 548 Binwen Road, Binjiang District, Hangzhou, 310053 China
| | - Min Lin
- The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang China
| | - Zhichao Sun
- The First Affiliated Hospital of Zhejiang Chinese Medical University, No. 54 Youdian Road, Shangcheng District, Hangzhou, Zhejiang 310006 People’s Republic of China
| | - Minli Chen
- Laboratory Animal Research Center/Comparative Medical Research Institute, Zhejiang Chinese Medical University, No 548 Binwen Road, Binjiang District, Hangzhou, 310053 China
| | - Maosheng Xu
- The First Affiliated Hospital of Zhejiang Chinese Medical University, No. 54 Youdian Road, Shangcheng District, Hangzhou, Zhejiang 310006 People’s Republic of China
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