Introduction:
Chronic kidney disease (CKD) is recognized as a major worldwide health problem. For all CKD, intra-renal fibrosis is a final common pathway that can be correlated with disease severity. Tissue stiffness can be measured non-invasively using shear wave elastography. This study evaluates the use of Young’s modulus derived by SWE as a biomarker that can distinguish normal from diseased kidneys. Also, Young’s modulus was correlated with estimated glomerular filtration rate (eGFR).
Methods:
The study comprised 60 chronic kidney disease (CKD) patients and 30 control subjects during the period between march 2023 and march 2024 in the department of radiology , CARE hospitals, Nampally. Conventional ultrasound was performed to measure the average kidney volume, parenchymal thickness and cortical thickness. SWE imaging was performed to measure average renal parenchymal stiffness. Diagnostic performance of SWE and conventional ultrasound were correlated with serum creatinine, urea levels and eGFR.
Results:
In our study, which has 60 cases and 30 controls, we found that the mean elastography value was significantly higher in cases (mean = -5.41 kPa) compared to controls (mean = -3.5 kPa). No significant difference in mean cortical thickness between cases and controls which could be due to exclusion of study population with cortical thickness less than 10mm. There is a significant difference between mean average kidney volume of cases and controls.No significant correlation between age and Elastography values in either cases (r = 0.024) or controls (r = 0.180). A mild positive correlation between BMI and Elastography values in cases (r = 0.428), but no significant correlation in controls (r = -0.058). No substantial relationship between cortical thickness and Elastography values in either cases (r = 0.025) or controls (r = -0.070). A mild negative correlation between eGFR and Elastography values in cases (r = -0.303). A statistically significant mild positive correlation between S creatinine and Elastography values in cases (r = 0.263). No significant relationship between cortical thickness and eGFR (ρ = 0.012), indicating a very weak or negligible positive correlation. A statistically significant moderate positive correlation between volume of kidney and eGFR (ρ = 0.479), suggesting a notable positive association between the two variables. Cortical thickness and Elastography values: no correlation in category 1 (ρ = 0.063), category 2 (ρ = 0.004), or category 3 (ρ = 0.028). eGFR and Elastography values: no correlation in category 1 (ρ = -0.090), mild positive correlation in category 2 (ρ = 0.318), and mild negative correlation in category 3 (ρ = -0.309). S.creatinine and Elastography values: moderate positive correlation in category 1 (ρ = 0.626), no correlation in category 2 (ρ = -0.054), and no correlation in category 3 (ρ = -0.140). Volume of kidney and eGFR: no correlation in category 1 (ρ = 0.090) or category 3 (ρ = 0.007), but mild positive correlation in category 2 (ρ = 0.445). Cortical thickness and eGFR: moderate negative correlation in category 1 (ρ = -0.572), mild positive correlation in category 2 (ρ = 0.425), and no correlation in category 3 (ρ = -0.072). Our analysis of average elastography values across different categories revealed a progressive increase in mean elastography values from category 1 to category 3. However, the Mann-Whitney U test showed no significant statistical difference between category 1 and category 2 (p > 0.05). Notably, We did not perform additional statistical analysis to investigate potential differences in elastography values between category 2 and category 3. The Mann Whitney U test was employed to compare Elastography values between category 1 and category 2 cases, yielding a non-significant difference (p = 0.384) in these values.
Conclusions:
SWE was superior to renal volume and cortical thickness in detecting CKD. A value of 4.32 kPa or less showed good accuracy in determining whether a kidney was diseased or not.
I have no potential conflict of interest to disclose.
I did not use generative AI and AI-assisted technologies in the writing process.