Original Investigation| Volume 30, ISSUE 6, P1047-1055, June 2023

Download started.


Brain Micro-Structural and Functional Alterations for Cognitive Function Prediction in the End-Stage Renal Disease Patients Undergoing Maintenance Hemodialysis

      Rationale and Objectives

      The goal of this study was to investigate the relationship between altered brain micro-structure and function, and cognitive function in patients with end-stage renal disease (ESRD) undergoing maintenance hemodialysis. Specially, diffusion kurtosis imaging (DKI), the resting-state functional connectivity (FC) algorithm, and the least squares support vector regression machine (LSSVRM) were utilized to conduct our study.

      Materials and Methods

      A total of 50 patients and 36 matched healthy controls were prospectively enrolled in our study. All subjects completed the Montreal cognitive assessment scale (MoCA) test. DKI and resting-state functional magnetic resonance imaging were measured. Relationship between DKI parameters, FC, and MoCA scores was evaluated. LSSVRM combined with the whale optimization algorithm (WOA) was used to predict cognitive function scores.


      In ESRD patients, altered DKI metrics were identified in 12 brain regions. Furthermore, we observed changes in FC values based on regions of interest (ROIs) in nine brain regions, involved in default mode network (DMN), frontoparietal network (FPN), and the limbic system. Significant correlations among DKI values, FC values, and MoCA scores were found. To some extent, altered FC showed significant correlations with changed DKI parameters. Furthermore, optimized prediction models were applied to more accurately predict the cognitive function associated with ESRD patients.


      Micro-structural and functional brain changes were found in ESRD patients, which may account for the onset of cognitive impairment in affected patients. These quantitative parameters combined with our optimized prediction model may be helpful to establish more reliable imaging markers to detect and monitor cognitive impairment associated with ESRD.

      Key Words


      ESRD (end-stage renal disease), HC (healthy controls), rs-fMRI (resting-state functional magnetic resonance imaging), BOLD (blood-oxygen-level-dependent), DKI (diffusion kurtosis imaging), DTI (diffusion tensor imaging), FC (functional connectivity), LSSVRM (least squares support vector regression machine), WOA (whale optimization algorithm), CI (cognitive impairment), MK (mean kurtosis), AK (axial kurtosis), RK (radial kurtosis), KA (kurtosis anisotropy), MoCA (Montreal cognitive assessment scale), DMN (default mode network), FPN (frontoparietal network), CKD (chronic kidney disease)
      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 to Academic Radiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Kalantar-Zadeh K
        • Jafar TH
        • Nitsch D
        • et al.
        Chronic kidney disease.
        Lancet. 2021; 398: 786-802
        • van Zwieten A
        • Wong G
        • Ruospo M
        • et al.
        Prevalence and patterns of cognitive impairment in adult hemodialysis patients: the COGNITIVE-HD study.
        Nephrol Dial Transpl. 2018; 33: 1197-1206
        • Basser PJ
        • Mattiello J
        • LeBihan D
        MR diffusion tensor spectroscopy and imaging.
        Biophys J. 1994; 66: 259-267
        • Mu J
        • Chen T
        • Li P
        • et al.
        Altered white matter microstructure mediates the relationship between hemoglobin levels and cognitive control deficits in end-stage renal disease patients.
        Hum Brain Mapp. 2018; 39: 4766-4775
        • Jensen JH
        • Helpern JA
        • Ramani A
        • et al.
        Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging.
        Magn Reson Med. 2005; 53: 1432-1440
        • Veraart J
        • Poot DH
        • Van Hecke W
        • et al.
        More accurate estimation of diffusion tensor parameters using diffusion Kurtosis imaging.
        Magn Reson Med. 2011; 65: 138-145
        • Li C
        • Lan C
        • Zhang X
        • et al.
        Evaluation of diffusional kurtosis imaging in sub-acute ischemic stroke: comparison with rehabilitation treatment effect.
        Cell Transplant. 2019; 28: 1053-1061
        • Yin J
        • Sun H
        • Wang Z
        • et al.
        Diffusion kurtosis imaging of acute infarction: comparison with routine diffusion and follow-up MR imaging.
        Radiology. 2018; 287: 651-657
        • Ito K
        • Ohtsuka C
        • Yoshioka K
        • et al.
        Differential diagnosis of Parkinsonism by a combined use of diffusion kurtosis imaging and quantitative susceptibility mapping.
        Neuroradiology. 2017; 59: 759-769
        • Kamagata K
        • Tomiyama H
        • Motoi Y
        • et al.
        Diffusional kurtosis imaging of cingulate fibers in Parkinson disease: comparison with conventional diffusion tensor imaging.
        Magn Reson Imaging. 2013; 31: 1501-1506
        • Lu P
        • Yuan T
        • Liu X
        • et al.
        Role of diffusional kurtosis imaging in differentiating neuromyelitis optica–related and multiple sclerosis–related acute optic neuritis.
        J Comput Assist Tomo. 2020; 44: 47-52
        • McKenna F
        • Babb J
        • Miles L
        • et al.
        Reduced microstructural lateralization in males with chronic schizophrenia: a diffusional kurtosis imaging study.
        Cereb Cortex. 2020; 30: 2281-2294
        • Liu Y
        • Zhang GM
        • Peng X
        • et al.
        Diffusion kurtosis imaging as an imaging biomarker for predicting prognosis in chronic kidney disease patients.
        Nephrol Dial Transplant. 2021; published online ahead of print, 2021 Jul 24
        • Hui ES
        • Cheung MM
        • Qi L
        • et al.
        Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis.
        Neuroimage. 2008; 42: 122-134
        • Barkhof F
        • Haller S
        • Rombouts SA
        Resting-state functional MR imaging: a new window to the brain.
        Radiology. 2014; 272: 29-49
        • Tomasi D
        • Wang GJ
        • Volkow ND
        Energetic cost of brain functional connectivity.
        Proc Natl Acad Sci. 2013; 110: 13642-13647
        • Wu F
        • Tu Z
        • Sun J
        • et al.
        Abnormal functional and structural connectivity of amygdala-prefrontal circuit in first-episode adolescent depression: a combined fMRI and DTI study.
        Front Psychiatry. 2020; 10: 983
        • Wang Y
        • Sun K
        • Liu Z
        • et al.
        Classification of unmedicated bipolar disorder using whole-brain functional activity and connectivity: a radiomics analysis.
        Cereb Cortex. 2020; 30: 1117-1128
        • Fiorenzato E
        • Strafella AP
        • Kim J
        • et al.
        Dynamic functional connectivity changes associated with dementia in Parkinson's disease.
        Brain. 2019; 142: 2860-2872
        • Qureshi MNI
        • Ryu S
        • Song J
        • et al.
        Evaluation of functional decline in Alzheimer's dementia using 3D deep learning and group ICA for rs-fMRI measurements.
        Front Aging Neurosci. 2019; 11: 8
        • Passamonti L
        • Tsvetanov KA
        • Jones PS
        • et al.
        Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance.
        J Neurosci. 2019; 39: 7218-7226
        • Chen HJ
        • Wang YF
        • Qi R
        • et al.
        Altered amygdala resting-state functional connectivity in maintenance hemodialysis end-stage renal disease patients with depressive mood.
        Mol Neurobiol. 2017; 54: 2223-2233
        • Hu R
        • Gao L
        • Chen P
        • et al.
        How do you feel now? The salience network functional connectivity in end-stage renal disease.
        Front Neurosci-Switz. 2020; 14533910
        • Gong N
        • Wong C
        • Chan C
        • et al.
        Correlations between microstructural alterations and severity of cognitive deficiency in Alzheimer's disease and mild cognitive impairment: a diffusional kurtosis imaging study.
        Magn Reson Imaging. 2013; 31: 688-694
        • Steven AJ
        • Zhuo J
        • Melhem ER
        Diffusion kurtosis imaging: an emerging technique for evaluating the microstructural environment of the brain.
        Am J Roentgenol. 2014; 202: W26
        • Zhang G
        • Zhang Y
        • Zhang C
        • et al.
        Diffusion kurtosis imaging of Substantia Nigra is a sensitive method for early diagnosis and disease evaluation in Parkinson's disease.
        Parkinson's Dis. 2015; 2015: 1-5
        • Chou MC
        • Ko CH
        • Chang JM
        • et al.
        Disruptions of brain structural network in end-stage renal disease patients with long-term hemodialysis and normal-appearing brain tissues.
        J Neuroradiol. 2019; 46: 256-262
        • Raichle ME
        The brain's default mode network.
        Annu Rev Neurosci. 2015; 38: 433-447
        • Lu H
        • Gu Z
        • Xing W
        • et al.
        Alterations of default mode functional connectivity in individuals with end-stage renal disease and mild cognitive impairment.
        BMC Nephrol. 2019; 20: 246
        • Cavanna AE
        • Trimble MR
        The precuneus: a review of its functional anatomy and behavioural correlates.
        Brain. 2006; 129: 564-583
        • Vertes RP
        • Linley SB
        • Hoover WB
        Limbic circuitry of the midline thalamus.
        Neurosci Biobehav Rev. 2015; 54: 89-107
        • Behfar Q
        • Behfar SK
        • von Reutern B
        • et al.
        Graph theory analysis reveals resting-state compensatory mechanisms in healthy aging and prodromal Alzheimer's disease.
        Front Aging Neurosci. 2020; 12576627
        • Shi Y
        • Tong C
        • Zhang M
        • et al.
        Altered functional connectivity density in the brains of hemodialysis end-stage renal disease patients: an in vivo resting-state functional MRI study.
        PLoS One. 2019; 14e227123
        • Niendam TA
        • Laird AR
        • Ray KL
        • et al.
        Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions.
        Cognit Affect Behav Neurosci. 2012; 12: 241-268
        • Vincent JL
        • Kahn I
        • Snyder AZ
        • et al.
        Evidence for a frontoparietal control system revealed by intrinsic functional connectivity.
        J Neurophysiol. 2008; 100: 3328-3342
        • Ma Q
        • Tang Y
        • Wang F
        • et al.
        Transdiagnostic dysfunctions in brain modules across patients with schizophrenia, bipolar disorder, and major depressive disorder: a connectome-based study.
        Schizophrenia Bull. 2020; 46: 699-712
        • Zhang Y
        • Xi Z
        • Zheng J
        • et al.
        GWLS: a novel model for predicting cognitive function scores in patients with end-stage renal disease.
        Front Aging Neurosci. 2022; 14: 83433
        • Hui ES
        • Cheung MM
        • Qi L
        • et al.
        Advanced MR diffusion characterization of neural tissue using directional diffusion kurtosis analysis.
        Annu Int Conf IEEE Eng Med Biol Soc. 2008; 2008: 3941-3944