Multiparametric Quantitative Ultrasound Imaging in Assessment of Chronic Kidney Disease

Value of radiomics-based two-dimensional ultrasound for diagnosing early diabetic nephropathy

Despite efforts to diagnose diabetic nephropathy (DN) using biochemical data or ultrasound imaging separately, a significant gap exists regarding the development of integrated models combining both modalities for enhanced early DN diagnosis. Therefore, we aimed to assess the ability of machine learning models containing two-dimensional ultrasound imaging and biochemical data to diagnose early DN in patients with type 2 diabetes mellitus (T2DM). This retrospective study included 219 patients, divided into a training or test group at an 8:2 ratio. Features were selected using minimum redundancy maximum relevance and random forest-recursive feature elimination. The predictive performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) for sensitivity, specificity, Matthews Correlation Coefficient, F1 score, and accuracy. K-nearest neighbor, support vector machine, and logistic regression models could diagnose early DN, with AUC values of 0.94, 0.85, and 0.85 in the training cohort and 0.91, 0.84, and 0.84 in the test cohort, respectively. Early DN diagnosing using two-dimensional ultrasound-based radiomics models can potentially revolutionize T2DM patient care by enabling proactive interventions, ultimately improving patient outcomes. Our integrated approach showcases the power of artificial intelligence in medical imaging, enhancing early disease detection strategies with far-reaching applications across medical disciplines.

Shear Wave Elastography for Assessment of Biopsy-Proven Renal Fibrosis: A Systematic Review and Meta-analysis

The purpose of this meta-analysis was to evaluate the diagnostic performance of shear wave elastography (SWE) for the staging of renal fibrosis in patients with chronic kidney disease (CKD). Classification of CKD into mild, moderate and severe fibrosis was based on renal biopsy pathology (glomerulosclerosis, tubulointerstitial injury and vascular sclerosis). The Cochrane Library, Medline, PubMed, Web of Science, EMBASE and CNKI databases were searched from January 1, 2009, to April 20, 2022. Pooled sensitivity, specificity, diagnostic odds ratio and area under the receiver operating characteristic curve (AUROC) were calculated using random effects models. A total of 1394 patients from 14 studies were included in the final analysis. For mild, moderate and severe renal fibrosis, SWE had a sensitivity of 0.79 (95% confidence interval [CI]: 0.67-0.88), 0.73 (95% CI: 0.65-0.80) and 0.87 (95% CI: 0.71-0.95); a specificity of 0.82 (95% CI: 0.75-0.87), 72% (95% CI: 0.67-0.77) and 0.83 (95% CI: 0.80-0.86); an AUROC of 0.87 (95% CI: 0.84-0.90), 0.78 (95% CI: 0.75-0.82) and 0.86 (95% CI: 0.82-0.88); and a diagnostic odds ratio of 17 (95% CI: 7-43), 7 (95% CI: 4-12) and 34 (95% CI: 13-88), respectively. Meta-regressions revealed that the publication date, system used and number of valid measurements of SWE were the main causes of heterogeneity. SWE is a good technique for diagnosing mild and severe renal fibrosis, as well as a fair technique for diagnosing moderate fibrosis.

Ultrasound shear wave elastography for the evaluation of renal pathological changes in adult patients

OBJECTIVE

Many studies have conflicting findings in using shear wave elastography (SWE) to assess renal fibrosis. This study reviews the use of SWE to evaluate pathological changes in native kidneys and renal allografts. It also tries to elucidate the confounding factors and care taken to ensure the results are consistent and reliable.

METHODS

The review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Literature search was conducted in Pubmed, Web of Science and Scopus database up to 23 October 2021. To evaluate risk and bias applicability, the Cochrane risk-of bias tool and GRADE was used. The review was registered under PROSPERO CRD42021265303.

RESULTS

A total of 2921 articles were identified. 104 full texts were examined and 26 studies included in systematic review. 11 studies performed on native kidneys and 15 studies on transplanted kidney. A wide range of impact factors was found that affect the accuracy of SWE of renal fibrosis in adult patients.

CONCLUSIONS

Compared to point SWE, two-dimensional SWE with elastogram could enable better selection of the region of interest in kidneys, leading to reproducible results. Tracking waves were attenuated as the depth from skin to region of interest increased, therefore, SWE is not recommended for overweight or obese patients. Variable transducer forces might also affect SWE reproducibility, thus, training of operators to ensure consistent operator-dependent transducer forces may be helpful.

ADVANCES IN KNOWLEDGE

This review provides a holistic insight on the efficiency of using SWE in evaluating pathological changes in native and transplanted kidneys, thereby contributing to the knowledge of its utilisation in clinical practice.

Arterial spin labeling and diffusion-weighted MR imaging: quantitative assessment of renal pathological injury in chronic kidney disease

PURPOSE

The aim of the study was to investigate the performance of arterial spin labeling (ASL), diffusion-weighted imaging (DWI), and clinical biomarkers in assessing renal pathological injury in CKD.

MATERIALS AND METHODS

Forty-five biopsy-proven CKD patients and 17 healthy volunteers underwent DWI and ASL examinations. Renal cortical blood flow (RBF) and apparent diffusion coefficient (ADC) values were acquired. Correlations between RBF, ADC, serum creatinine (SCr), estimated glomerular filtration rate (eGFR), and pathological scores were assessed. The diagnostic efficacy of SCr, eGFR, RBF, and ADC in assessing renal pathological injury was assessed by ROC curve analysis.

RESULTS

The cortical RBF, ADC, SCr, and eGFR were significantly correlated with the renal histology score (all p < 0.01). The AUC values of SCr, eGFR, RBF, and ADC were 0.705 (95% confidence interval (CI): 0.536-0.827), 0.718 (0.552-0.839), 0.823 (0.658-0.916), and 0.624 (0.451-0.786), respectively, in discriminating the minimal-mild renal pathological injury group (N = 30) from the control group (N = 17). The diagnostic ability of ASL was significantly higher than that of DWI (p = 0.049) and slightly but not significantly higher than that of eGFR and SCr (p = 0.151 and p = 0.129, respectively). When compared with that of eGFR, the sensitivity of ASL in detecting early renal injury increased from 50 to 70% (p = 0.014). However, in differentiating between the minimal-mild and moderate-severe renal injury groups (N = 15), there was no significant difference in diagnostic ability among the four parameters (all p > 0.05).

CONCLUSION

ASL is practicable for noninvasive evaluation of renal pathology, especially for predicting early renal pathological injury in CKD patients.

Assessment of Parotid Gland Tumors by Means of Quantitative Multiparametric Ultrasound (mpUS)

OBJECTIVE

The preoperative diagnostical differentiation of parotid gland tumor (PGT) is not always simple due to several different entities. B-mode-ultrasound (US) remains the imaging modality of choice, while histopathology serves as the gold standard for finalizing the diagnosis. We aimed to evaluate the use of multiparametric US (mpUS) in the assessment of PGT.

METHODS

We included 97 PGTs from 96 patients. A standardized mpUS protocol using B-mode-US, shear-wave elastography (SWE), and standardized contrast-enhanced ultrasound (CEUS) was performed prior to surgical intervention. SWE was assessed by real-time measurement conducting a minimum of five measurements, while quantitative CEUS parameters were assessed with a post-processing perfusion software.

RESULTS

SWE allowed differentiation between benign PGT (Warthin's Tumor (WT) paired with lymph nodes (LN) and pleomorphic adenoma (PA)), and WT and LN were softer compared to PA. WT showed lower velocities than squamous cell carcinoma (SCC): the most common malignant PGT. CEUS parameters showed significant group differences between WT and PA, WT and malignant lesions, WT and SCC, WT paired with LN versus PA, and WT paired with LN versus SCC.

CONCLUSION

MpUS seems to be beneficial in the assessment of PGT characterization, with benign PGT appearing to be softer in SWE than tumors with malignant tendencies. The quantitative CEUS parameter shows higher perfusion in WT than in PA, and malignant PGTs are less vascularized than WTs.

TNF-α and IL-1β Promote Renal Podocyte Injury in T2DM Rats by Decreasing Glomerular VEGF/eNOS Expression Levels and Altering Hemodynamic Parameters

PURPOSE

Diabetic nephropathy (DN) is a serious microvascular complication in those with type 2 diabetes mellitus (T2DM). Evidence confirms that serum tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in the T2DM stage are proposed as prognostic markers for DN development, but it is unclear how they affect renal podocyte-associated nephrin and WT-1 expression. In the presence of podocyte injury, glomerular vascular endothelial growth factor (VEGF), endothelial nitric oxide synthase (eNOS) and hemodynamic parameters are dysregulated. The current research aimed to clarify the relationship of TNF-α and IL-1β with podocyte injury by altering VEGF/eNOS expression and hemodynamic parameters.

METHODS

A high-fat diet/streptozotocin-induced DN rat model was established. Serum TNF-α and IL-1β levels were tracked in the pre-T2DM, T2DM and DN stages. In the DN stage, the mRNA and protein expression levels of renal TNF-α, IL-1β, VEGF, eNOS, nephrin and WT-1 were studied. Renal hemodynamic parameters, including peak systolic velocity, end-diastolic flow velocity and mean velocity were measured with a color Doppler ultrasound technique.

RESULTS

Compared to those in the normal control (CTL) group, serum TNF-α and IL-1β levels increased significantly in the pre-T2DM stage (obesity, insulin resistance and hyperlipidemia), T2DM stage (hyperglycemia) and DN stage (abnormal renal functions) (all: P < 0.05) in the DN group. Serum TNF-α and IL-1β levels in the T2DM stage were significantly higher than those in the pre-T2DM stage (two: P < 0.05). Compared to the CTL group, renal nephrin, WT-1, TNF-α, IL-1β, eNOS and VEGF expression and hemodynamic parameters in the DN stage all showed significant differences separately (all: P < 0.05).

CONCLUSION

Increased serum and renal TNF-α and IL-1β levels played important roles in reducing renal nephrin and WT-1 expression levels, which may be related to the fact that the former affected renal VEGF/eNOS expression and blood flow parameters in the DN rats.

Chronic Kidney Disease and Its Clinical Correlates in a Rural Community in Southwestern Nigeria

Chronic kidney disease (CKD) is a burgeoning problem globally, and more than a billion adults were affected as of 2016, with 1.2 million people dying from renal failure in 2017. To arrest the seemingly relentless progression of CKD to renal failure, there is a need to detect CKD early in the community. A community-based study was carried out to look at the prevalence and risk factors of CKD. Anthropometric and other clinical variables were measured. Blood samples were taken for determining creatinine, uric acid, urea, and lipids. CKD was defined as an estimated glomerular filtration rate of ≤60 mL/min/1.73 m2. Electrocardiograms and renal ultrasound scans were performed. In total, 201 people were recruited. Those with CKD had a male:female ratio of 1:3.9 and were older. The prevalence of autosomal-dominant polycystic kidney disease and CKD was 531.9 persons/100,000 population and 46.3%, respectively. Systolic blood pressure, pulse pressure, total cholesterol, triglycerides, high-density lipoprotein (HDL), uric acid, QTc interval, and electrocardiographic left ventricular hypertrophy were higher in those with CKD. Age, female sex, and HDL were independently associated with CKD. There was a steep rise in CKD at the community level. Increased awareness of CKD and prompt interventions are therefore imperative.

Renal Protective Effects of Inonotus obliquus on High-Fat Diet/Streptozotocin-Induced Diabetic Kidney Disease Rats: Biochemical, Color Doppler Ultrasound and Histopathological Evidence

Diabetic kidney disease (DKD) is the current leading cause of end-stage renal disease. Inonotus obliquus (chaga), a medicinal fungus, has been used in treatment of diabetes. Here, we aim to identify the renal protective effects of chaga extracts on a DKD rat model which was induced by a high-fat diet and streptozotocin injection. During the total 17-weeks experiment, the biological parameters of serum and urine were examined, and the color Doppler ultrasound of renal artery, the periodic acid-Schiff staining, and electron microscopy of kidney tissue were performed. The compositions of chaga extracts were analyzed and the intervention effects of the extracts were also observed. Compared with the normal control group, the biochemical research showed that insulin resistance was developed, blood glucose and total cholesterol were elevated, urinary protein excretion and serum creatinine levels were significantly increased in the DKD model. The ultrasound examinations confirmed the deteriorated blood flow parameters of the left renal interlobar artery in the rat models. Finally, histopathological data supported renal injury on the thickened glomerular basement membrane and fusion of the foot processes. 8 weeks intervention of chaga improved the above changes significantly, and the 100 mg/kg/d chaga group experienced significant effects compared with the 50 mg/kg/d in some parameters. Our findings suggested that Doppler ultrasound examinations guided with biochemical indicators played important roles in evaluating the renal injury as an effective, noninvasive, and repeatable method in rats. Based on biochemical, ultrasound, and histopathological evidence, we confirmed that chaga had pharmacodynamic effects on diabetes-induced kidney injury and the aforementioned effects may be related to delaying the progression of DKD.

Ultrasound Based Radiomics Features of Chronic Kidney Disease

RATIONALE AND OBJECTIVES

Interstitial fibrosis, common to most chronic kidney diseases, can potentially affect the speckle patterns of kidney ultrasound (US). Here we use Radiomics features derived from US images to identify kidneys with chronic kidney disease.

MATERIALS AND METHODS

B-mode US without speckle reduction was performed on a cohort of CKD patients (n = 75) and healthy subjects (n = 27). Images of the patients with renal cysts, agenesis and calculi were excluded. After background subtraction, regions of interest were selected from each kidney. Four hundred and sixty-five Radiomics features including first and second-order gray level statistics were calculated on the selected regions. Second-order features were also calculated on wavelet transformed images. A random forest model was used to identify the most important features that can differentiate healthy and diseased kidneys. The ten most important features, based on the Gini index, were used to train a support vector machine. Synthetic minority oversampling technique was used to remove over fitting.

RESULTS

Wavelet transformed, Gray Level Run Length Matrix based Normalized Run Length Non-uniformity, WT (LH) (GRLN) was identified as the most significant feature in differentiating CKD and healthy kidneys (accuracy - 0.85, sensitivity - 1.0). The mean WT (LH) GRLN of healthy kidneys (0.40 ± 0.01) was significantly higher (p < 0.01) than that of the CKD kidneys (0.24 ± 0.01). According to the Gini Index, the differentiability of WT (LH) GRLN was highest when the long axis of the kidney was oriented perpendicular to the columns of the image matrix.

CONCLUSION

Radiomics features based on wavelet transformation are sensitive to directionality of US speckle patters and can be successfully used to differentiate CKD and healthy US kidney images.

Clinical predictive model for the 1-year remission probability of IgA vasculitis nephritis

PURPOSE

Early remission of Immunoglobulin A vasculitis nephritis (IgAVN) substantially affects its prognosis. In this work, a multivariate model to predict the 1-year remission probability of patients with IgAVN was developed on the basis of clinical laboratory data.

METHODS

Data of 187 patients with IgAVN confirmed by renal biopsy were retrospectively assessed. Least absolute shrinkage and selection operator regression analysis were conducted to establish a multivariate logistic regression model. A nomogram based on the multivariate logistic regression model was constructed for easy application in clinical practice. Concordance index, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and clinical impact curves (CIC) were used to evaluate the predictive accuracy and clinical value of this nomogram.

RESULTS

The predictive factors contained in the multivariate model included duration, gender, respiratory infection, arthritis, edema, estimated glomerular filtration rate, 24 h urine protein, uric acid, and renal ultrasound intensity. The area under the curves (AUC) of the nomogram in the training set and testing set were 0.814 and 0.822, respectively, indicating its good predictive ability. Moreover, the DCA curve and CIC revealed its clinical utility.

CONCLUSION

The developed multivariate predictive model combines the clinical and laboratory factors of patients with IgAVN and is useful in the individualized prediction of the 1-year remission probability aid for clinical decision-making during treatment and management of IgAVN.

Evaluation of Renal Oxygenation and Hemodynamics in Patients with Chronic Kidney Disease by Blood Oxygenation Level-dependent Magnetic Resonance Imaging and Intrarenal Doppler Ultrasonography

INTRODUCTION

The basic pathophysiologic derangement of chronic kidney disease (CKD) begins with the loss of nephrons, leading to renal hemodynamic changes, eventually causing a reduced nephron count and renal hypoxia. The purpose of this study was to observe the renal oxygenation and renal hemodynamics of patients with CKD using blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) and intrarenal Doppler ultrasonography (IDU).

METHODS

The study enrolled 39 patients with stage 1-4 CKD and 19 healthy volunteers (HVs). Based on their estimated glomerular filtration rate (eGFR), CKD patients were divided into 2 subgroups: a mild renal impairment (MI) group and a moderate to severe renal impairment (MSI) group. We monitored the participants' mean cortical T2* (COT2*) and mean medullary T2* (MET2*) values on BOLD-MRI, and measured the peak systolic velocities (PSVs), end-diastolic velocities (EDVs), renal resistive index (RI), and kidney length by IDU. We also recorded clinical indicators such as age, sex, body mass index (BMI), 24-h urinary protein (24-h Upr), serum creatinine (sCr), blood urea nitrogen (BUN), and eGFR. BOLD-MRI, IDU measurements, and the clinical indicators were compared in CKD patients and HVs by the analysis of variance and Kruskal-Wallis H test. Spearman's correlation was used to assess the relationship between data from BOLD-MRI and IDU and clinical indicators.

RESULTS

The COT2* values were significantly higher than the MET2* values in the HV, MI, and MSI groups. COT2*, MET2*, EDV, PSV, and kidney length gradually decreased in the HV, MI, and MSI groups (all p < 0.05), whereas RI and 24-h Upr gradually increased (both p < 0.05). Spearman correlation analysis showed that COT2* and MET2* were significantly positively correlated with eGFR, PSV, EDV, and kidney length but were significantly negatively correlated with sCr, BUN, and 24-h Upr (all p < 0.05). There was no correlation observed between the COT2* and MET2* and the RI and BMI values.

CONCLUSIONS

Renal oxygenation and blood flow velocities were found declined as the CKD stage progressed. The BOLD-MRI and IDU techniques may have clinical value by measuring intrarenal oxygenation and renal blood perfusion to judge the severity of renal damage in patients with CKD.

Exploration of a Framework for the Identification of Chronic Kidney Disease Based on 2D Ultrasound Images: A Survey

BACKGROUND

Chronic kidney disease (CKD) is a fatal disease that ultimately results in kidney failure. The primary threat is the aetiology of CKD. Over the years, researchers have proposed various techniques and methods to detect and diagnose the disease. The conventional method of detecting CKD is the determination of the estimated glomerular filtration rate by measuring creatinine levels in blood or urine. Conventional methods for the detection and classification of CKD are tedious; therefore, several researchers have suggested various alternative methods. Recently, the research community has shown keen interest in developing methods for the early detection of this disease using imaging modalities such as ultrasound, magnetic resonance imaging, and computed tomography.

DISCUSSION

The study aimed to conduct a systematic review of various existing techniques for the detection and classification of different stages of CKD using 2D ultrasound imaging of the kidney. The review was confined to 2D ultrasound images alone, considering the feasibility of implementation even in underdeveloped countries because 2D ultrasound scans are more cost effective than other modalities. The techniques and experimentation in each work were thoroughly studied and discussed in this review.

CONCLUSION

This review displayed the cutting-age research, challenges, and possibilities of further research and development in the detection and classification of CKD.

Can distinction between the renal cortex and outer medulla on ultrasonography predict estimated glomerular filtration rate in canine chronic kidney diseases?

Background

Quantitative evaluation of renal cortical echogenicity (RCE) has been tried and developed in human and veterinary medicine.

Objectives

The objective of this study was to propose a method for evaluating RCE quantitatively and intuitively, and to determine associations between ultrasonographic renal structural distinction and estimated glomerular filtration rate (eGFR) in canine chronic kidney disease (CKD).

Methods

Data were collected on 63 dogs, including 27 with normal kidney function and 36 CKD patients. Symmetric dimethylarginine and creatinine concentrations were measured for calculating eGFR. RCE was evaluated as 3 grades on ultrasonography images according to the distinction between the renal cortex and outer medulla. The RCE grade of each kidney was measured.

Results

There was a significant difference in eGFR between the group normal and CKD (p < 0.001). As mean of RCE grades (the mean values of each right and left kidney's RCE grade) increases, the proportion of group CKD among the patients in each grade increases (p < 0.001). Also, severity of RCE (classified as "high" if any right or left kidney evaluated as RCE grade 3, "low" otherwise) and eGFR is good indicator for predicting group CKD (p < 0.001).

Conclusions

The degree of distinction between the renal cortex and the outer medulla is closely related to renal function including eGFR and the RCE grade defined in this study can be used as a method of objectively evaluating RCE.

The Value of Contrast-Enhanced Ultrasound versus Doppler Ultrasound in Grading Renal Artery Stenosis

Objective

This study is aimed at exploring the accuracy of contrast-enhanced ultrasound (CEUS) in grading renal artery stenosis.

Methods

122 renal arteries with suspected renal artery stenosis were selected. DSA, DUS, and CEUS were performed for all patients with suspected renal artery stenosis in the research. DSA was selected as the gold standard. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of CEUS or Doppler ultrasound (DUS) in the diagnosis of renal artery stenosis were analyzed. The consistency between CEUS and digital subtraction angiography (DSA) was compared. The accuracy of DUS or CEUS in grading renal artery stenosis was assessed by the area under the receiver operating characteristic (ROC) curves and compared between groups.

Results

The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of CEUS in the diagnosis of renal artery stenosis were 88.9%, 87.8%, 88.5%, 93.5%, and 80.0%, respectively. There was no significant difference in grading renal artery stenosis between CEUS and DSA (X² = 0.643, P = 0.424). 77 of the 122 renal arteries were diagnosed with the stenosis rate more than 30% by CEUS. Compared with the results of DSA, the kappa value of CEUS was 0.749 (P < 0.05).

Conclusion

CEUS is accurate in grading renal artery stenosis, and it may represent the method of choice in diagnosing renal artery stenosis.

Ultrasound Shear Wave Elastography and Doppler Sonography to Assess the Effect of Hydration on Human Kidneys: A Preliminary Observation

To assess the feasibility of ultrasound imaging in depicting the changes in kidney size, hemodynamics and cortex viscoelasticity after hydration, we prospectively performed 2-D ultrasound shear wave elastography (SWE) and Doppler sonography of bilateral kidneys in 30 volunteers. Kidney length, cortex shear wave velocity (SWV), shear wave dispersion (SWD), interlobar artery peak systolic velocity (PSV), end-diastolic velocity (EDV) and resistive index (RI) were measured before and 60 min after with and without drinking water (1 L). The differences in kidney length, SWV, PSV, EDV and color pixel intensity before and after hydration were significant (p < 0.001), whereas these differences were not significant without hydration (p > 0.05). SWD and RI did not significantly differ with or without hydration. Inter- and intra-observer reliability in performing SWE and Doppler sonography was good. The use of Doppler sonography and ultrasound SWE to evaluate the effect of hydration on kidney size, hemodynamics and viscoelasticity seem to be feasible.

Supersonic Shear Wave Ultrasonography for Assessing Tissue Stiffness in Native Kidney

Recent years have brought shear wave elastography to the attention of nephrologists as a non-invasive method for detecting kidney fibrosis and, therefore, as a potential tool for reducing the need for kidney biopsy. Few studies are performed on native kidney. We aimed to compare cortical stiffness, assessed by measuring Young's modulus (YM, kPa) with SuperSonic Imaging technology, in patients with various degrees of chronic kidney disease (CKD) compared with healthy individuals. Cortical stiffness was measured by two operators, in different sessions, in 32 patients with CKD stages 3-5 and 20 healthy individuals. Comparison between mean YM values in CKD and those in controls and also between the different stages of CKD was our primary objective. The influence of other possible confounders on YM readings was also investigated and analyzed. Mean YM was significantly greater in CKD patients than in controls. Estimated YM was not able to differentiate the stages of CKD, except stage 5. Intra-subject variability was greater in CKD than in controls. Body mass index was the most important confounder in multiple analyses, in both the CKD and control groups. Our results highlight a positive correlation between increased cortical stiffness and presence of CKD. Further studies are needed to validate this method for implementation in daily clinical practice.

Correlation of Point Shear Wave Velocity and Kidney Function in Chronic Kidney Disease

OBJECTIVES

Point shear wave elastography is a quantitative ultrasound-based imaging method used in the assessment of renal disease. Among point shear wave elastographic options, 2 techniques have been studied considerably: Virtual Touch quantification (VTQ; Siemens AG, Erlangen, Germany) and ElastPQ (EPQ; Philips Healthcare, Bothell, WA). Both rely on the tissue response to an acoustic beam generated by the ultrasound transducer. The data on renal VTQ are more extensive, whereas EPQ has been used less thus far in the assessment of the kidneys. This study aimed to evaluate the performance of EPQ in the kidney and compare it with VTQ.

METHODS

We studied 124 participants using EPQ: 22 with no renal disease and 102 with chronic kidney disease (CKD). Ninety-one were studied with both the EPQ and VTQ methods. We obtained 5 valid measurements in each kidney, expressed in meters per second.

RESULTS

The mean kidney stiffness measurements ± SD obtained with EPQ in the healthy control group were as follows: right kidney, 1.23 ± 0.33 m/s; and left kidney, 1.26 ± 0.32 m/s (P = .6). In the patients with CKD (all stages), the mean kidney stiffness measurements obtained were significantly lower: right kidney, 1.09 ± 0.39 m/s; and left kidney, 1.04 ± 0.38 m/s (P = .4). We observed that, similar to VTQ, EPQ values decreased with CKD progression, based on analysis of variance results using different CKD stages. From a receiver operating characteristic curve analysis, the cutoff value for an estimated glomerular filtration rate of less than 45 mL/min was 1.24 m/s, and the value for an estimated glomerular filtration rate of less than 30 mL/min was 1.07 m/s.

CONCLUSIONS

When using EPQ, the kidney shear wave velocity is decreased in patients with CKD, an observation similar to that obtained by using the VTQ method.

A Dynamic Graph Cuts Method with Integrated Multiple Feature Maps for Segmenting Kidneys in 2D Ultrasound Images

RATIONALE AND OBJECTIVES

Automatic segmentation of kidneys in ultrasound (US) images remains a challenging task because of high speckle noise, low contrast, and large appearance variations of kidneys in US images. Because texture features may improve the US image segmentation performance, we propose a novel graph cuts method to segment kidney in US images by integrating image intensity information and texture feature maps.

MATERIALS AND METHODS

We develop a new graph cuts-based method to segment kidney US images by integrating original image intensity information and texture feature maps extracted using Gabor filters. To handle large appearance variation within kidney images and improve computational efficiency, we build a graph of image pixels close to kidney boundary instead of building a graph of the whole image. To make the kidney segmentation robust to weak boundaries, we adopt localized regional information to measure similarity between image pixels for computing edge weights to build the graph of image pixels. The localized graph is dynamically updated and the graph cuts-based segmentation iteratively progresses until convergence. Our method has been evaluated based on kidney US images of 85 subjects. The imaging data of 20 randomly selected subjects were used as training data to tune parameters of the image segmentation method, and the remaining data were used as testing data for validation.

RESULTS

Experiment results demonstrated that the proposed method obtained promising segmentation results for bilateral kidneys (average Dice index = 0.9446, average mean distance = 2.2551, average specificity = 0.9971, average accuracy = 0.9919), better than other methods under comparison (P < .05, paired Wilcoxon rank sum tests).

CONCLUSIONS

The proposed method achieved promising performance for segmenting kidneys in two-dimensional US images, better than segmentation methods built on any single channel of image information. This method will facilitate extraction of kidney characteristics that may predict important clinical outcomes such as progression of chronic kidney disease.