Comparison of Shear Wave Elastography and Conventional Ultrasound in Assessing Kidney Function as Measured Using 51Cr-ethylenediaminetetraacetic Acid and 99Tc-Dimercaptosuccinic Acid

Pharmacodynamic Evaluation and Mechanism of Ginseng Polysaccharide against Nephrotoxicity Induced by Hexavalent Chromium

Hexavalent chromium is a common pollutant in the environment. Long-term exposure to hexavalent chromium can cause damage to multiple organs. The kidney is one of the main organs that metabolizes heavy metal toxicity, and the accumulation of Cr (VI) in the body can lead to serious damage to kidney function. Studies have shown that ginseng polysaccharides have the function of preventing cisplatin-induced endoplasmic reticulum stress, inflammatory response, and apoptosis in renal cells, but their efficacy and mechanisms against hexavalent chromium-induced nephrotoxicity need to be explored. The aim of this study was to explore the efficacy and mechanism of ginseng polysaccharide against hexavalent chromium-induced nephrotoxicity. The results of pharmacodynamic experiments showed that ginseng polysaccharide could significantly reduce the kidney index, urea nitrogen (BUN), and serum creatinine (Cre) values of K2Cr2O7-treated mice. The results of mechanistic experiments showed that ginseng polysaccharides could alleviate oxidative stress, apoptosis, and biofilm damage in renal tissues caused by Cr (VI). Lipidomic correlation analysis showed that ginseng polysaccharides could protect the organism by regulating the expression of differential lipids. This study opens new avenues for the development of alternative strategies for the prevention of kidney injury caused by hexavalent chromium.

Diagnostic utility of two-dimensional shear wave elastography in nephropathic dogs and its correlation with renal contrast-enhanced ultrasound in course of acute kidney injury

Aims of our study were to evaluate the feasibility and diagnostic value of two-dimensional shear wave elastography in dogs with acute kidney injury, chronic kidney disease, and acute on chronic kidney disease, its correlation with renal functional (creatinine, urea), and prognostic parameters (serum calcium-phosphorus product, urinary output), and with contrast-enhanced ultrasound (qualitative and quantitative evaluation). The study was prospective. A group of healthy (Group A) and a group of nephropathic dogs (Group B) were included. Shear wave elastography was performed on the left kidney of the subjects of both groups; contrast-enhanced ultrasound was performed only in dogs with acute kidney injury and acute on chronic kidney disease. Sixty-four dogs were included (Group A, n=24; Group B, n=40). The renal stiffness values were significantly higher in Group B than Group A; optimal cut-off stiffness values for detection of renal pathology were: ≥1.51 m/sec (area under the curve, 0.84; 95% confidence interval 0.74-0.94) and ≥6.75 kPa (area under the curve, 0.84; 95% confidence interval 0.73-0.94). For contrast-enhanced ultrasound, a significant positive correlation was found between renal stiffness, area under the curve, and wash-out area under the curve values of cortex quantitative analysis. No correlations were found between renal stiffness and renal functional and prognostic parameters. Shear wave elastography showed diagnostic utility to detect renal abnormalities in dogs with acute kidney injury, chronic kidney disease and acute on chronic kidney disease, however, it could not differentiate between these different nephropathies.

Ultrasound elastography in chronic kidney disease: a systematic review and meta-analysis

Ultrasound elastography (USE) is a noninvasive technique for assessing tissue elasticity, and its application in nephrology has aroused growing interest in recent years. The purpose of this article is to systematically review the clinical application of USE in patients with chronic kidney disease (CKD), including native and transplanted kidneys, and quantitatively investigate differences in elasticity values between healthy individuals and CKD patients. Furthermore, we provide a qualitative analysis of the studies included, discussing the potential interplay between renal stiffness, estimated glomerular filtration rate, and fibrosis. In January 2022, a systematic search was carried out on the MEDLINE (PubMed) database, concerning studies on the application of USE in patients with CKD, including patients with transplanted kidneys. The results of the included studies were extracted by two independent researchers and presented mainly through a formal narrative summary. A meta-analysis of nine study parts from six studies was performed. A total of 647 studies were screened for eligibility and, after applying the exclusion and inclusion criteria, 69 studies were included, for a total of 6728 patients. The studies proved very heterogeneous in terms of design and results. The shear wave velocity difference of - 0.82 m/s (95% CI: - 1.72-0.07) between CKD patients and controls was not significant. This result agrees with the qualitative evaluation of included studies that found controversial results for the relationship between renal stiffness and glomerular filtration rate. On the contrary, a clear relationship seems to emerge between USE values and the degree of fibrosis. At present, due to the heterogeneity of results and technical challenges, large-scale application in the monitoring of CKD patients remains controversial.

Shear wave elastography and Doppler ultrasound in kidney transplant recipients

Objective

To evaluate the association between shear wave elastography parameters and arterial resistance in kidney transplant recipients.

Materials and Methods

This was a prospective cross-sectional study involving consecutive adult kidney transplant recipients. All patients underwent color Doppler to evaluate the resistive index (RI) and ultrasound shear wave elastography for the quantification of renal allograft stiffness.

Results

We evaluated 55 patients, of whom 9 (16.4%) had an RI defined as abnormal (≥ 0.79) and 46 (83.6%) had an RI defined as normal (< 0.79). The mean age was higher in the abnormal RI group than in the normal RI group (68.0 ± 8.6 years vs. 42.6 ± 14.1 years; p < 0.001), as was the mean shear wave velocity (2.6 ± 0.4 m/s vs. 2.2 ± 0.4 m/s; p = 0.013). Multivariate analysis identified two independent predictors of arterial resistance: age (OR = 1.169; 95% CI: 1.056 to 1.294; p = 0.003) and shear wave velocity (OR = 17.1; 95% CI: 1.137 to 257.83; p = 0.040).

Conclusion

We observed an association between rigidity in the cortex of the transplanted kidney, as evaluated by shear wave elastography, and arterial resistance, as evaluated by color Doppler, in kidney transplant recipients.

Elastography ultrasound with machine learning improves the diagnostic performance of traditional ultrasound in predicting kidney fibrosis

BACKGROUND

Noninvasively predicting kidney tubulointerstitial fibrosis is important because it's closely correlated with the development and prognosis of chronic kidney disease (CKD). Most studies of shear wave elastography (SWE) in CKD were limited to non-linear statistical dependencies and didn't fully consider variables' interactions. Therefore, support vector machine (SVM) of machine learning was used to assess the prediction value of SWE and traditional ultrasound techniques in kidney fibrosis.

METHODS

We consecutively recruited 117 CKD patients with kidney biopsy. SWE, B-mode, color Doppler flow imaging ultrasound and hematological exams were performed on the day of kidney biopsy. Kidney tubulointerstitial fibrosis was graded by semi-quantification of Masson staining. The diagnostic performances were accessed by ROC analysis.

RESULTS

Tubulointerstitial fibrosis area was significantly correlated with eGFR among CKD patients (R = 0.450, P < 0.001). AUC of SWE, combined with B-mode and blood flow ultrasound by SVM, was 0.8303 (sensitivity, 77.19%; specificity, 71.67%) for diagnosing tubulointerstitial fibrosis (>10%), higher than either traditional ultrasound, or SWE (AUC, 0.6735 [sensitivity, 67.74%; specificity, 65.45%]; 0.5391 [sensitivity, 55.56%; specificity, 53.33%] respectively. Delong test, p < 0.05); For diagnosing different grades of tubulointerstitial fibrosis, SWE combined with traditional ultrasound by SVM, had AUCs of 0.6429 for mild tubulointerstitial fibrosis (11%-25%), and 0.9431 for moderate to severe tubulointerstitial fibrosis (>50%), higher than other methods (Delong test, p < 0.05).

CONCLUSION

SWE with SVM modeling could improve the diagnostic performance of traditional kidney ultrasound in predicting different kidney tubulointerstitial fibrosis grades among CKD patients.

Shear Wave Elastography: A Review on the Confounding Factors and Their Potential Mitigation in Detecting Chronic Kidney Disease

Early detection of chronic kidney disease is important to prevent progression of irreversible kidney damage, reducing the need for renal transplantation. Shear wave elastography is ideal as a quantitative imaging modality to detect chronic kidney disease because of its non-invasive nature, low cost and portability, making it highly accessible. However, the complexity of the kidney architecture and its tissue properties give rise to various confounding factors that affect the reliability of shear wave elastography in detecting chronic kidney disease, thus limiting its application to clinical trials. The objective of this review is to highlight the confounding factors presented by the complex properties of the kidney, in addition to outlining potential mitigation strategies, along with the prospect of increasing the versatility and reliability of shear wave elastography in detecting chronic kidney disease.

Advances of Contrast-Enhanced Ultrasonography and Elastography in Kidney Transplantation: From Microscopic to Microcosmic

Kidney transplantation is the best choice for patients with end-stage renal disease. To date, allograft biopsy remains the gold standard for revealing pathologic changes and predicting long-term outcomes. However, the invasive nature of transplant biopsy greatly limits its application. Ultrasound has been a first-line examination for evaluating kidney allografts for a long time. Advances in ultrasound in recent years, especially the growing number of studies in elastography and contrast-enhanced ultrasonography (CEUS), have shed new light on its application in kidney transplantation. Elastography, including strain elastography and shear wave elastography, is used mainly to assess allograft stiffness and, thus, predict renal fibrosis. CEUS has been used extensively in evaluating blood microperfusion, assessing acute kidney injury and detecting different complications after transplantation. Requiring the use of microbubbles also makes CEUS a novel method of gene transfer and drug delivery, enabling promising targeted diagnosis and therapy. In this review, we summarize the advances of elastography and CEUS in kidney transplantation and evaluate their potential efficiency in becoming a better complement to or even substitute for transplant biopsy in the future.

Recent advances in medical image processing for the evaluation of chronic kidney disease

Assessment of renal function and structure accurately remains essential in the diagnosis and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic Resonance Imaging (MRI), Ultrasound Elastography (UE), Computed Tomography (CT) and scintigraphy (PET, SPECT) offers the opportunity to non-invasively retrieve structural, functional and molecular information that could detect changes in renal tissue properties and functionality. Currently, the ability of artificial intelligence to turn conventional medical imaging into a full-automated diagnostic tool is widely investigated. In addition to the qualitative analysis performed on renal medical imaging, texture analysis was integrated with machine learning techniques as a quantification of renal tissue heterogeneity, providing a promising complementary tool in renal function decline prediction. Interestingly, deep learning holds the ability to be a novel approach of renal function diagnosis. This paper proposes a survey that covers both qualitative and quantitative analysis applied to novel medical imaging techniques to monitor the decline of renal function. First, we summarize the use of different medical imaging modalities to monitor CKD and then, we show the ability of Artificial Intelligence (AI) to guide renal function evaluation from segmentation to disease prediction, discussing how texture analysis and machine learning techniques have emerged in recent clinical researches in order to improve renal dysfunction monitoring and prediction. The paper gives a summary about the role of AI in renal segmentation.