Advertisement

Diffusion Kurtosis Imaging in Evaluating the Mild Cognitive Impairment of Occupational Aluminum Workers

  • Author Footnotes
    6 Wenji Xu and Xiangru Sun contributed equally to this work.
    Wenji Xu
    Footnotes
    6 Wenji Xu and Xiangru Sun contributed equally to this work.
    Affiliations
    College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.
    Search for articles by this author
  • Author Footnotes
    6 Wenji Xu and Xiangru Sun contributed equally to this work.
    Xiangru Sun
    Footnotes
    6 Wenji Xu and Xiangru Sun contributed equally to this work.
    Affiliations
    College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.
    Search for articles by this author
  • Haoru Jiang
    Affiliations
    College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, China.
    Search for articles by this author
  • Xiaochun Wang
    Affiliations
    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.
    Search for articles by this author
  • Bin Wang
    Affiliations
    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.
    Search for articles by this author
  • Qiao Niu
    Affiliations
    School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China
    Search for articles by this author
  • Huaxing Meng
    Affiliations
    School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China
    Search for articles by this author
  • Jiangfeng Du
    Affiliations
    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.
    Search for articles by this author
  • Guoqiang Yang
    Affiliations
    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.
    Search for articles by this author
  • Bo Liu
    Affiliations
    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.
    Search for articles by this author
  • Hui Zhang
    Affiliations
    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.
    Search for articles by this author
  • Yan Tan
    Correspondence
    Address Correspondence to: Y.T.
    Affiliations
    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.
    Search for articles by this author
  • Author Footnotes
    6 Wenji Xu and Xiangru Sun contributed equally to this work.
Published:January 21, 2023DOI:https://doi.org/10.1016/j.acra.2022.12.003

      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.

      Key Words

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Academic Radiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Batum K
        • Çinar N
        • Sahin S
        • et al.
        The connection between MCI and Alzheimer disease: neurocognitive clues [J].
        Turk J Med Sci. 2015; 45: 1137-1140https://doi.org/10.3906/sag-1404-179
        • Arevalo-Rodriguez I
        • Smailagic N
        • Roqué-Figuls M
        • et al.
        Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI) [J].
        Cochrane Database Syst Rev. 2021; 7CD010783https://doi.org/10.1002/14651858.CD010783
        • Winblad B
        • Palmer K
        • Kivipelto M
        • et al.
        Mild cognitive impairment–beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment [J].
        J Intern Med. 2004; 256: 240-246https://doi.org/10.1111/j.1365-2796.2004.01380.x
        • Ferris S
        • Nordberg A
        • Soininen H
        • et al.
        Progression from mild cognitive impairment to Alzheimer's disease: effects of sex, butyrylcholinesterase genotype, and rivastigmine treatment [J].
        Pharmacogenet Genomics. 2009; 19: 635-646https://doi.org/10.1097/FPC.0b013e32832f8c17
        • Baumgart M
        • Snyder H M
        • Carrillo M C
        • et al.
        Summary of the evidence on modifiable risk factors for cognitive decline and dementia: A population-based perspective [J].
        Alzheimers Dement. 2015; 11: 718-726https://doi.org/10.1016/j.jalz.2015.05.016
        • Zawilla N H
        • Taha F M
        • Kishk N A
        • et al.
        Occupational exposure to aluminum and its amyloidogenic link with cognitive functions [J].
        J Inorg Biochem. 2014; 139: 57-64https://doi.org/10.1016/j.jinorgbio.2014.06.003
        • Lu X
        • Liang R
        • Jia Z
        • et al.
        Cognitive disorders and tau-protein expression among retired aluminum smelting workers [J].
        J Occup Environ Med. 2014; 56: 155-160https://doi.org/10.1097/jom.0000000000000100
        • Li H
        • Xue X
        • Li L
        • et al.
        Aluminum-Induced Synaptic Plasticity Impairment via PI3K-Akt-mTOR Signaling Pathway [J].
        Neurotox Res. 2020; 37: 996-1008https://doi.org/10.1007/s12640-020-00165-5
        • Giulietti G
        • Torso M
        • Serra L.
        Whole brain white matter histogram analysis of diffusion tensor imaging data detects microstructural damage in mild cognitive impairment and alzheimer’s disease patients [J].
        J Magn Reson Imaging. 2018; 48: 767-779https://doi.org/10.1002/jmri.25947
        • Raja R
        • Rosenberg G
        • Caprihan A.
        Review of diffusion MRI studies in chronic white matter diseases [J].
        Neurosci Lett. 2019; 694: 198-207https://doi.org/10.1016/j.neulet.2018.12.007
        • Kumar A
        • Singh S
        • Singh A
        • et al.
        Diffusion tensor imaging based white matter changes and antioxidant enzymes status for early identification of mild cognitive impairment [J].
        Int J Neurosci. 2019; 129: 209-216https://doi.org/10.1080/00207454.2018.1521401
        • Yu J
        • Lam C L M
        • Lee TMC.
        White matter microstructural abnormalities in amnestic mild cognitive impairment: A meta-analysis of whole-brain and ROI-based studies [J].
        Neurosci Biobehav Rev. 2017; 83: 405-416https://doi.org/10.1016/j.neubiorev.2017.10.026
        • Allen J W
        • Yazdani M
        • Kang J
        • et al.
        Patients with Mild Cognitive Impairment may be Stratified by Advanced Diffusion Metrics and Neurocognitive Testing [J].
        J Neuroimaging. 2019; 29: 79-84https://doi.org/10.1111/jon.12588
        • Stahl R
        • Dietrich O
        • Teipel S J
        • et al.
        White matter damage in Alzheimer disease and mild cognitive impairment: assessment with diffusion-tensor MR imaging and parallel imaging techniques [J].
        Radiology. 2007; 243: 483-492https://doi.org/10.1148/radiol.2432051714
        • Liu Y
        • Liu D
        • Liu M
        • et al.
        The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study[J].
        Neurol Sci. 2023; 44: 171-180https://doi.org/10.1007/s10072-022-06408-x
        • Jensen J H
        • Helpern J A
        • Ramani A
        • et al.
        Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging [J].
        Magn Reson Med. 2005; 53: 1432-1440https://doi.org/10.1002/mrm.20508
        • Liu D
        • Li K
        • Ma X
        • et al.
        Correlations between the Microstructural Changes of the Medial Temporal Cortex and Mild Cognitive Impairment in patients with Cerebral Small Vascular Disease (cSVD): aDiffusion Kurtosis Imaging Study [J].
        Front Neurol. 2019; 10https://doi.org/10.3389/fneur.2019.01378
        • Liu H
        • Liu D
        • Li K
        • et al.
        Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease [J].
        Neurol Res. 2021; 43: 659-667https://doi.org/10.1080/01616412.2021.1910903
        • Song GP
        • Yao TT
        • Wang D
        Differentiating between Alzheimer's disease, amnestic mild cognitive impairment, and normal aging via diffusion kurtosis imaging [J].
        Neural Regen Res. 2019; 14: 2141-2146https://doi.org/10.4103/1673-5374.262594
        • Albert MS
        • DeKosky S T
        • Dickson D
        • et al.
        The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease [J].
        Alzheimers Dement. 2011; 7: 270-279https://doi.org/10.1016/j.jalz.2011.03.008
        • Falangola M F
        • Jensen J H
        • Tabesh A
        • et al.
        Non-Gaussian diffusion MRI assessment of brain microstructure in mild cognitive impairment and Alzheimer's disease [J].
        Magn Reson Imaging. 2013; 31: 840-846https://doi.org/10.1016/j.mri.2013.02.008
        • Sexton CE
        • Kalu UG
        • Filippini N
        • et al.
        A meta-analysis of diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease [J].
        Neurobiol Aging. 2011; 32: 2322,e5-18https://doi.org/10.1016/j.neurobiolaging.2010.05.019
        • Klingberg T.
        Development of a superior frontal-intraparietal network for visuo-spatial working memory [J].
        Neuropsychologia. 2006; 44: 2171-2177https://doi.org/10.1016/j.neuropsychologia.2005.11.019
        • Wen Q
        • Mustafi S M
        • Li J
        • et al.
        White matter alterations in early-stage Alzheimer's disease: A tract-specific study [J].
        Alzheimers Dement (Amst). 2019; 11: 576-587https://doi.org/10.1016/j.dadm.2019.06.003
        • Alexander A L
        • Hasan K
        • Kindlmann G
        • et al.
        A geometric analysis of diffusion tensor measurements of the human brain [J].
        Magn Reson Med. 2000; 44: 283-291https://doi.org/10.1002/1522-2594(200008)44:2<283::aid-mrm16>3.0.co;2-v
        • Blockx I
        • De Groof G
        • Verhoye M
        • et al.
        Microstructural changes observed with DKI in a transgenic Huntington rat model: evidence for abnormal neurodevelopment [J].
        Neuroimage. 2012; 59: 957-967https://doi.org/10.1016/j.neuroimage.2011.08.062
        • Yuan L
        • Sun M
        • Chen Y
        • et al.
        Non-Gaussian diffusion alterations on diffusion kurtosis imaging in patients with early Alzheimer's disease [J].
        Neurosci Lett. 2016; 616: 11-18https://doi.org/10.1016/j.neulet.2016.01.021
        • Yang A W
        • Jensen J H
        • Hu C C
        • et al.
        Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging [J].
        J Magn Reson Imaging. 2013; 37: 365-371https://doi.org/10.1002/jmri.23840
        • Julka D
        • Gill K D
        Involvement of altered cytoskeletal protein phosphorylation in aluminum-induced CNS dysfunction [J].
        J Biochem Toxicol. 1996; 11: 227-233https://doi.org/10.1002/(sici)1522-7146(1996)11:5<227::Aid-jbt3>3.0.Co;2-m
        • Van Petten C.
        Relationship between hippocampal volume and memory ability in healthy individuals across the lifespan: review and meta-analysis [J].
        Neuropsychologia. 2004; 42: 1394-1413https://doi.org/10.1016/j.neuropsychologia.2004.04.006
        • Magisetty O
        • Dowlathabad M R
        • Raichurkar K P
        • et al.
        First magenetic resonance imaging studies on aluminium maltolate-treated aged New Zealand rabbits:an Alzheimer's animal mode [J].
        Psychogeriatrics. 2016; 16: 263-267https://doi.org/10.1111/psyg.12158
        • Poulter S
        • Lee S A
        • Dachtler J
        • et al.
        Vector trace cells in the subiculum of the hippocampal formation [J].
        Nat Neurosci. 2021; 24: 266-275https://doi.org/10.1038/s41593-020-00761-w
        • Wang L.
        Entry and Deposit of Aluminum in the Brain [J].
        Adv Exp Med Biol. 2018; 1091: 39-51https://doi.org/10.1007/978-981-13-1370-7_3
        • Hao W
        • Hao C
        • Wu C
        • et al.
        Aluminum impairs cognitive function by activating DDX3X-NLRP3-mediated pyroptosis signaling pathway [J].
        Food and Chemical Toxicol. 2021; 157112591https://doi.org/10.1016/j.fct.2021.112591
        • Giorgianni C M
        • D'Arrigo G
        • Brecciaroli R
        • et al.
        Neurocognitive effects in welders exposed to aluminium [J].
        Toxicol Ind Health. 2014; 30: 347-356https://doi.org/10.1177/0748233712456062
        • Polizzi S
        • Pira E
        • Ferrara M
        • et al.
        Neurotoxic effects of aluminium among foundry workers and Alzheimer's disease [J].
        Neurotoxicology. 2002; 23: 761-774https://doi.org/10.1016/s0161-813x(02)00097-9
        • Riihimäki V
        • Aitio A.
        Occupational exposure to aluminum and its biomonitoring in perspective [J].
        Crit Rev Toxicol. 2012; 42: 827-853https://doi.org/10.3109/10408444.2012.725027
        • Meyer-Baron M
        • Schäper M
        • Knapp G
        • et al.
        Occupational aluminum exposure: evidence in support of its neurobehavioral impact [J].
        Neurotoxicology. 2007; 28: 1068-1078https://doi.org/10.1016/j.neuro.2007.07.001
        • Zhang ZY
        • Jiang HR
        • Sun XR
        • et al.
        Monitoring mild cognitive impairment of workers exposed to occupational aluminium based on quantitative susceptibility mapping[J].
        Clin Radiol. 2022; 77: 840-847https://doi.org/10.1016/j.crad.2022.06.007
        • Xu SM
        • Pan BL
        • Gao D
        • et al.
        Blood glucose mediated the effects of cognitive function impairment related to aluminum exposure in Chinese aluminum smelting workers [J].
        Neurotoxicology. 2022; 91: 282-289https://doi.org/10.1016/j.neuro.2022.06.001
        • Xu SM
        • Zhang YW
        • Ju XF
        • et al.
        Cross-sectional study based on occupational aluminium exposure population[J].
        Environ Toxicol Pharmacol. 2021; 83103581https://doi.org/10.1016/j.etap.2020.103581