Related Experiment Video
Updated: Jul 24, 2025

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Diffusion-weighted, intravoxel incoherent motion, and diffusion kurtosis tensor MR imaging in chronic kidney
Jie Zhu1, Aiqun Chen2, Jiayin Gao1
1Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
Objectives:
To probe the correlations of parameters derived from standard DWI and its extending models including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) with the pathological and functional alterations in CKD.
Material And Methods:
Seventy-nine CKD patients with renal biopsy and 10 volunteers were performed with DWI, IVIM, diffusion kurtosis tensor imaging (DKTI) scanning. Correlations between imaging results and the pathological damage [glomerulosclerosis index (GSI) and tubulointerstitial fibrosis index (TBI)], as well as eGFR, 24 h urinary protein and Scr) were evaluated.CKD patients were divided into 2 groups: group 1: both GSI and TBI scores <2 points (61 cases); group 2: both GSI and TBI scores ≥2 points (18 cases).
Results:
There were significant difference in cortical and medullary MD, and cortical D among 3 groups and between group 1 and 2. Cortical and medullary MD, cortical D, and medullary FA were negatively correlated with GSI score (r = -0.322 to -0.386, P < 0.05). Cortical and medullary MD and D, medullary FA were also negatively correlated with TBI score (r = -0.257 to -0.395, P < 0.05). These parameters were all correlated with eGFR and Scr. Cortical MD and D showed the highest AUC of 0.790 and 0.745 in discriminating mild and moderate-severe glomerulosclerosis and tubular interstitial fibrosis, respectively.
Conclusions:
The corrected diffusion-related indices, including cortical and medullary D and MD, as well as medullary FA were superior to ADC, perfusion-related and kurtosis indices for evaluating the severity of renal pathology and function in CKD patients.
Insights
Advanced diffusion MRI techniques, including diffusion kurtosis tensor imaging (DKTI), can effectively assess chronic kidney disease (CKD) severity. Key diffusion parameters correlate with kidney damage and function, outperforming standard metrics.
Area of Science:
- Radiology and Imaging
- Nephrology
- Biomedical Engineering
Background:
- Chronic kidney disease (CKD) involves progressive renal pathological and functional decline.
- Standard imaging lacks sensitivity in quantifying CKD severity.
- Advanced diffusion MRI models offer potential for non-invasive assessment.
Purpose of the Study:
- To evaluate correlations between diffusion MRI parameters (DWI, IVIM, DTI, DKI) and CKD pathology/function.
- To compare the efficacy of different diffusion models in assessing renal damage.
Main Methods:
- Diffusion MRI including DWI, IVIM, and DKTI performed on 79 CKD patients and 10 controls.
- Correlations analyzed between imaging parameters and renal biopsy scores (GSI, TBI), eGFR, and urinary protein.
- Patients stratified into groups based on GSI and TBI scores.
Main Results:
- Cortical and medullary diffusion parameters (D, MD) and medullary FA showed significant differences across CKD severity groups.
- These parameters negatively correlated with GSI and TBI scores, indicating increased damage with lower diffusion values.
- Cortical MD and D demonstrated high AUC for discriminating CKD severity.
Conclusions:
- Corrected diffusion indices (cortical/medullary D and MD, medullary FA) are superior to ADC, perfusion, and kurtosis indices for evaluating CKD.
- Diffusion MRI provides a sensitive, non-invasive tool for assessing renal pathology and function in CKD.
Related Concept Videos
Imaging Studies I: Kidney, Ureter, and Bladder Studies
Magnetic Resonance Imaging
Imaging Studies IV: Magnetic Resonance Imaging
Acute Kidney Injury IV: Diagnostic Studies and Prevention
Imaging Studies VII: Vascular Imaging
Chronic Kidney Disease I: Introduction

