Assessing brain microstructural changes in chronic kidney disease: a diffusion imaging study using multiple models
To explore the effectiveness of diffusion quantitative parameters derived from advanced diffusion models in detecting brain microstructural changes in patients with chronic kidney disease (CKD). The study comprised 44 CKD patients (eGFR<59 mL/min/1.73 m ) and 35 age-and sex-matched healthy contro...
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Published in | Frontiers in neurology Vol. 15; p. 1387021 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
01.05.2024
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Subjects | |
Online Access | Get full text |
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Summary: | To explore the effectiveness of diffusion quantitative parameters derived from advanced diffusion models in detecting brain microstructural changes in patients with chronic kidney disease (CKD).
The study comprised 44 CKD patients (eGFR<59 mL/min/1.73 m
) and 35 age-and sex-matched healthy controls. All patients underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging. Reconstructed to obtain diffusion MRI models, including diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI, were processed to obtain multi-parameter maps. The Tract-Based Spatial Statistics (TBSS) analysis was utilized for detecting microstructural differences and Pearson correlation analysis assessed the relationship between renal metabolism markers and diffusion parameters in the brain regions of CKD patients. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic performance of diffusion models, with AUC comparisons made using DeLong's method.
Significant differences were noted in DTI, NODDI, and MAP-MRI parameters between CKD patients and controls (
< 0.05). DTI indicated a decrease in Fractional Anisotropy(FA) and an increase in Mean and Radial Diffusivity (MD and RD) in CKD patients. NODDI indicated decreased Intracellular and increased Extracellular Volume Fractions (ICVF and ECVF). MAP-MRI identified extensive microstructural changes, with elevated Mean Squared Displacement (MSD) and Q-space Inverse Variance (QIV) values, and reduced Non-Gaussianity (NG), Axial Non-Gaussianity (NGAx), Radial Non-Gaussianity (NGRad), Return-to-Origin Probability (RTOP), Return-to-Axis Probability (RTAP), and Return-to-Plane Probability (RTPP). There was a moderate correlation between serum uric acid (SUA) and diffusion parameters in six brain regions (
< 0.05). ROC analysis showed the AUC values of DTI_FA ranged from 0.70 to 0.793. MAP_NGAx in the Retrolenticular part of the internal capsule R reported a high AUC value of 0.843 (
< 0.05), which was not significantly different from other diffusion parameters (
> 0.05).
The advanced diffusion models (DTI, NODDI, and MAP-MRI) are promising for detecting brain microstructural changes in CKD patients, offering significant insights into CKD-affected brain areas. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Evren Özarslan, Linköping University, Sweden Peng Wang, Inner Mongolia Medical University, China Reviewed by: Shi Diwei, Tsinghua University, China Edited by: Govind Nair, National Institutes of Health (NIH), United States These authors have contributed equally to this work and share first authorship |
ISSN: | 1664-2295 1664-2295 |
DOI: | 10.3389/fneur.2024.1387021 |