4.6 Article

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

期刊

ACADEMIC RADIOLOGY
卷 30, 期 6, 页码 1047-1055

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.acra.2022.06.019

关键词

End-stage renal disease; diffusion kurtosis imaging; resting-state functional magnetic resonance imaging; predict

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The study aimed to investigate the relationship between altered brain micro-structure and function, and cognitive function in patients with end-stage renal disease (ESRD). DKI, resting-state functional connectivity (FC) algorithm, and LSSVRM were utilized. Results showed altered DKI metrics in 12 brain regions and changes in FC values in nine regions related to DMN, FPN, and the limbic system. There were significant correlations among DKI values, FC values, and MoCA scores. Optimized prediction models were used to predict cognitive function in ESRD patients. Micro-structural and functional brain changes in ESRD patients may contribute to cognitive impairment onset. These parameters and prediction models can help establish reliable imaging markers for detecting and monitoring cognitive impairment in ESRD.
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. Results: 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 signifi-cant correlations with changed DKI parameters. Furthermore, optimized prediction models were applied to more accurately predict the cognitive function associated with ESRD patients. Conclusion: 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: End-stage renal disease; diffusion kurtosis imaging; resting-state functional magnetic resonance imaging; predict. (c) 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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