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Noninvasive assessment of renal function and fibrosis in CKD patients using histogram analysis based on diffusion
Guanjie Yuan1, Weinuo Qu1, Shichao Li1
1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou District Wuhan 430030, Hubei, China.
Insights
Diffusion kurtosis imaging (DKI) histogram analysis shows promise for noninvasively assessing kidney function and fibrosis in chronic kidney disease (CKD) patients. Key parameters effectively differentiate disease severity and correlate with renal function and fibrosis scores.
Area of Science:
- Radiology
- Nephrology
- Medical Imaging
Background:
- Chronic kidney disease (CKD) poses a significant global health burden.
- Accurate assessment of renal function and fibrosis is crucial for CKD management.
- Noninvasive imaging biomarkers are needed to complement traditional diagnostic methods.
Purpose of the Study:
- To evaluate the utility of histogram analysis derived from diffusion kurtosis imaging (DKI) for assessing renal function and fibrosis in CKD.
- To determine the correlation between DKI histogram parameters and estimated glomerular filtration rate (eGFR) and fibrosis scores.
- To assess the diagnostic performance of DKI parameters in differentiating CKD severity.
Main Methods:
- Diffusion kurtosis imaging (DKI) was performed on 36 CKD patients prior to renal biopsy.
- Histogram parameters of diffusivity (D) and kurtosis (K) were extracted using FireVoxel.
- Statistical analyses compared histogram parameters between stable (eGFR ≥ 60) and impaired (eGFR < 60) eGFR groups, and correlated them with fibrosis scores.
Main Results:
- Significant differences in D and K histogram parameters were observed between stable and impaired eGFR groups in both cortex and medulla.
- Cortical Dmean showed the strongest correlation with eGFR (r=0.648) and the highest AUC (0.889) for differentiating renal function.
- Cortical K90th strongly correlated with fibrosis scores (r=0.575) and demonstrated the largest AUC (0.849) for fibrosis assessment, with improved performance when combined with 24-hour urinary protein.
Conclusions:
- Histogram analysis of DKI is a feasible noninvasive method for evaluating renal function in CKD patients.
- DKI-derived histogram parameters can effectively assess renal fibrosis severity in CKD.
- This technique offers a promising noninvasive approach for monitoring CKD progression and guiding treatment decisions.
Purpose:
To investigate the potential of histogram analysis based on diffusion kurtosis imaging (DKI) in evaluating renal function and fibrosis associated with chronic kidney disease (CKD).
Materials And Methods:
Thirty-six CKD patients were enrolled, and DKI was performed in all patients before the renal biopsy. The histogram parameters of diffusivity (D) and kurtosis (K) were obtained using FireVoxel. The histogram parameters between the stable [estimated glomerular filtration rate (eGFR) ≥ 60 ml/min/1.73 m2] and impaired (eGFR < 60 ml/min/1.73 m2) eGFR group were compared. Besides, patients were classified into mild, moderate, and severe fibrosis group using a semi-quantitative standard. The correlations of histogram parameters with eGFR and fibrosis scores were investigated and the diagnostic performances of histogram parameters in assessing renal dysfunction and fibrosis were analyzed. The added value of combination of most significant parameter with 24 h urinary protein (24 h-UPRO) in evaluating fibrosis was also explored.
Results:
Seven D histogram parameters in cortex (mean, median, 10th, 25th, 75th, 90th percentiles and entropy), two D histogram parameters in medulla (75th, 90th percentiles), seven K histogram parameters in cortex (mean, min, median, 10th, 25th, 75th, 90th percentiles) and three K histogram parameters in medulla (mean, median, 25th percentile) were significantly different between the two groups. The Dmean of cortex was the most relevant parameter to eGFR (r = 0.648, P < 0.001) and had the largest area under the curve (AUC) for differentiating the stable from impaired eGFR group [AUC = 0.889; 95% confidence interval (CI) 0.728-0.970]. The K90th of cortex presented the strongest correlation with fibrosis scores (r = 0.575, P < 0.001) and achieved the largest AUC for distinguishing the mild from moderate to severe fibrosis group (AUC = 0.849, 95% CI 0.706-0.993). Combining the K90th in cortex with 24 h-UPRO gained statistically higher AUC value (AUC = 0.880, 95% CI 0.763-0.996).
Conclusion:
Histogram analysis based on DKI is practicable for the noninvasive assessment of renal function and fibrosis in CKD patients.
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