Myosteatosis and aortic calcium score on abdominal CT as prognostic markers in non-dialysis chronic kidney disease patients.

We aimed to examine the relationship between abdominal computed tomography (CT)-based body composition data and both renal function decline and all-cause mortality in patients with non-dialysis chronic kidney disease (CKD). This retrospective study comprised non-dialysis CKD patients who underwent consecutive unenhanced abdominal CT between January 2010 and December 2011. CT-based body composition was measured using semiautomated method that included visceral fat, subcutaneous fat, skeletal muscle area and density, and abdominal aortic calcium score (AAS). Sarcopenia and myosteatosis were defined by decreased skeletal muscle index (SMI) and decreased skeletal muscle density, respectively, each with specific cutoffs. Risk factors for CKD progression and survival were identified using logistic regression and Cox proportional hazard regression models. Survival between groups based on myosteatosis and AAS was compared using the Kaplan-Meier curve. 149 patients (median age: 70 years) were included; 79 (53.0%) patients had sarcopenia and 112 (75.2%) had myosteatosis. The median AAS was 560.9 (interquartile range: 55.7-1478.3)/m2. The prognostic factors for CKD progression were myosteatosis [odds ratio (OR) = 4.31, p = 0.013] and high AAS (OR = 1.03, p = 0.001). Skeletal muscle density [hazard ratio (HR) = 0.93, p = 0.004] or myosteatosis (HR = 4.87, p = 0.032) and high AAS (HR = 1.02, p = 0.001) were independent factors for poor survival outcomes. The presence of myosteatosis and the high burden of aortic calcium were significant factors for CKD progression and survival in patients with non-dialysis CKD.

Chronic kidney disease and its association with cerebral small vessel disease in the general older hypertensive population.

BACKGROUND: Cerebral small vessel disease can be identified using magnetic resonance imaging, and includes white matter hyperintensities, lacunar infarcts, cerebral microbleeds, and brain atrophy. Cerebral small vessel disease and chronic kidney disease share many risk factors, including hypertension. This study aims to explore an association between chronic kidney disease and cerebral small vessel disease, and also to explore the role of hypertension in this relationship. METHODS: With a cross sectional study design, data from 390 older adults was retrieved from the general population study Good Aging in Skåne. Chronic kidney disease was defined as glomerular filtration rate < 60 ml/min/1,73m2. Associations between chronic kidney disease and magnetic resonance imaging markers of cerebral small vessel disease were explored using logistic regression models adjusted for age and sex. In a secondary analysis, the same calculations were performed with the study sample stratified based on hypertension status. RESULTS: In the whole group, adjusted for age and sex, chronic kidney disease was not associated with any markers of cerebral small vessel disease. After stratification by hypertension status and adjusted for age and sex, we observed that chronic kidney disease was associated with cerebral microbleeds (OR 1.93, CI 1.04-3.59, p-value 0.037), as well as with cortical atrophy (OR 2.45, CI 1.34-4.48, p-value 0.004) only in the hypertensive group. In the non-hypertensive group, no associations were observed. CONCLUSIONS: In this exploratory cross-sectional study, we observed that chronic kidney disease was associated with markers of cerebral small vessel disease only in the hypertensive subgroup of a general population of older adults. This might indicate that hypertension is an important link between chronic kidney disease and cerebral small vessel disease. Further studies investigating the relationship between CKD, CSVD, and hypertension are warranted.

Association of renal elasticity evaluated by real-time shear wave elastography with renal fibrosis in patients with chronic kidney disease.

OBJECTIVE: Renal fibrosis is a final common pathological hallmark in the progression of chronic kidney disease (CKD). Non-invasive evaluation of renal fibrosis by mapping renal stiffness obtained by shear wave elastography (SWE) may facilitate the clinical therapeutic regimen for CKD patients. METHODS: A cohort of 162 patients diagnosed with CKD, who underwent renal biopsy, was prospectively and consecutively recruited between April 2019 and December 2021. The assessment of renal cortex stiffness was performed using SWE imaging. The patients were classified into different groups based on pathological renal fibrosis (mild group: n = 74; moderate-to-severe group: n = 88). Binary logistic regression model and generalized additive model were conducted to investigate the association of renal elasticity with renal fibrosis. RESULTS: Compared with the mildly impaired group, the moderate-to-severe group showed a significant decline in renal elasticity (P < .001). In the fully adjusted model, each 10 kPa drop in renal elasticity was associated with a 3.5-fold increment in the risk of moderate-to-severe renal fibrosis (fully adjusted odds ratio, 4.54; 95% CI, 2.41-8.57). Particularly, participants in the lowest elasticity group (≤29.92 kPa) had a 20-fold increased chance of moderate-to-severe renal fibrosis than those in the group with highest elasticity (≥37.93 kPa). An inverse linear association was observed between renal elasticity increment and moderate-to-severe renal fibrosis risk. CONCLUSION: There is a negative linear association between increased renal elasticity and moderate-to-severe renal fibrosis risk among CKD patients. Patients with diminished renal stiffness have a higher risk of moderate-to-severe renal fibrosis. ADVANCES IN KNOWLEDGE: CKD patients with reduced renal stiffness have a higher likelihood of moderate-to-severe renal fibrosis.

A Comparison Between Two Different Definitions of Contrast-Associated Acute Kidney Injury for Long-Term Mortality in Patients with Chronic Kidney Disease Undergoing Coronary Angiography.

Background: Contrast-associated acute kidney injury (CA-AKI) is a prevalent complication following coronary angiography (CAG). However, there is ongoing controversy surrounding its precise definition. Although previous studies have demonstrated the successful application of appropriate definitions in managing high-risk CA-AKI patients, there remains limited research on the association between different definitions and prognosis specifically in patients with chronic kidney disease (CKD). Methods: A total of 4197 CKD patients undergoing coronary angiography (CAG) were included in this study. Two definitions of contrast-associated acute kidney injury (CA-AKI) were used: CA-AKIA, which was defined as an increase of ≥0.5 mg/dL or >25% in serum creatinine (SCr) from baseline within 72 hours after CAG, and CA-AKIB, which was defined as an increase of ≥0.3 mg/dL or >50% in SCr from baseline within 48 hours after CAG. Cox regression analysis was employed to assess the association between these two definitions and long-term mortality. Additionally, population attributable risks (PARs) were calculated to evaluate the impact of CA-AKI definitions on long-term prognosis. Results: During the median follow-up period of 4.70 (2.50-7.78) years, the overall long-term mortality was 23.6%, and the long-term mortality in patients with CA-AKI according to both CA-AKIA and CA-AKIB criteria were 33.5% and 33.8%, respectively. We found that CA-AKIA (HR: 1.45, 95% CI: 1.23-1.70, p<0.001) and CA-AKIB (HR: 1.44, 95% CI: 1.23-1.69, p<0.001) were associated with long-term mortality. The PARs were the highest for CA-AKIA (5.87%), followed by CA-AKIB (5.70%). Conclusion: Contrast-associated acute kidney injury (CA-AKI) is a frequently observed complication in CKD patients undergoing coronary angiography (CAG), and both definitions of CA-AKI are significantly correlated with a poor long-term prognosis. Consequently, in the clinical management of CKD patients, it is crucial to prioritize CA-AKI, irrespective of the specific CA-AKI definition used.

Muscle ultrasound to diagnose sarcopenia in chronic kidney disease: a systematic review and bayesian bivariate meta-analysis.

OBJECTIVE: The aim of this systematic review was to assess the diagnostic test accuracy of muscle ultrasound for sarcopenia among chronic kidney disease (CKD) populations. BACKGROUND: Sarcopenia has become a worldwide health issue, especially for CKD patients. Conventional techniques of muscle mass assessment often prove limited, thus prompts increasing interest in ultrasound suitability. METHODS: We searched the Cochrane Library, PubMed and Embase for literature published up to June 2023. Ultrasound diagnosis of sarcopenia in CKD patients was included. Two independent investigators used the Quality Assessment Tool for Diagnosis Accuracy Studies (QUADAS-2) to assess the quality. We extracted valuable information from eligible studies. Using a Bayesian bivariate model, we pooled sensitivity and specificity values and summary receiver operating characteristic (SROC) curves. RESULTS: Five articles, involving 428 participants at various stages of CKD were included. Three studies diagnosed by the cross-sectional area (CSA) of the rectus femoris, while two others by muscle thickness (MT) and shear wave elastography (SWE) from the same muscle, separately. Overall, CSA or SWE had a pooled sensitivity of 0.95 (95% CrI, 0.80, 1.00), and the specificity was 0.73 (95% CrI, 0.55, 0.88) for diagnosing sarcopenia in CKD patients. CONCLUSIONS: Ultrasound measurements of CSA and SWE were more sensitive for diagnosing sarcopenia in the CKD population than in the general population. Ultrasound assessment from a single peripheral skeletal muscle site may serve as a rapid screening tool for identifying sarcopenic individuals within the CKD population, if a specific cut-off value could be determined.

Evaluation of renal function in chronic kidney disease using histogram analysis based on multiple diffusion models.

OBJECTIVES: To compare the diagnostic value of histogram features of multiple diffusion metrics in predicting early renal impairment in chronic kidney disease (CKD). METHODS: A total of 77 patients with CKD (mild group, estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2) and 30 healthy controls (HCs) were enrolled. Diffusion-weighted imaging was performed by using single-shot echo planar sequence with 13 b values (0, 20, 50, 80, 100, 150, 200, 500, 800, 1000, 1500, 2000, and 2500 s/mm2). Diffusion models including mono-exponential (Mono), intravoxel incoherent motion (IVIM), stretched-exponential (SEM), and kurtosis (DKI) were calculated, and their histogram features were analysed. All diffusion models for predicting early renal impairment in CKD were established using logistic regression analysis, and diagnostic efficiency was compared among the models. RESULTS: All diffusion models had high differential diagnosis efficiency between the mild group and HCs. The areas under the curve (AUCs) of Mono, IVIM, SEM, DKI, and the combined diffusion model for predicting early renal impairment in CKD were 0.829, 0.809, 0.760, 0.825, and 0.861, respectively. There were no significant differences in AUCs except SEM and combined model, SEM, and DKI model. There were significant correlations between eGFR/serum creatinine and some of histogram features. CONCLUSIONS: Histogram analysis based on multiple diffusion metrics was practicable for the non-invasive assessment of early renal impairment in CKD. ADVANCES IN KNOWLEDGE: Advanced diffusion models provided microstructural information. Histogram analysis further reflected histological characteristics and heterogeneity. Histogram analysis based on multiple diffusion models could provide an accurate and non-invasive method to evaluate the early renal damage of CKD.

Comparison of the effects of peritoneal dialysis and hemodialysis on spontaneous brain activity in CKD patients: an rs-fMRI study.

OBJECTIVE: To compare the effects of peritoneal dialysis and hemodialysis on spontaneous brain activity in patients with end-stage renal disease. METHODS: A total of 52 dialysis patients with end-stage renal disease, including 25 patients with chronic kidney disease undergoing hemodialysis (HD-CKD) and 27 patients with chronic kidney disease undergoing peritoneal dialysis (PD-CKD), and 49 healthy controls (normal control) were included. All participants underwent neuropsychological testing (Mini-Mental State Examination and Montreal cognitive assessment) and resting-state functional magnetic resonance imaging. Fractional amplitude of low frequency fluctuations and Regional Homogeneity algorithms were employed to evaluate spontaneous brain activity. Statistical analysis was performed to discern differences between the groups. RESULTS: When compared with the normal control group, the PD-CKD group exhibited significant alterations in fractional amplitude of low frequency fluctuations in various cerebellum regions and other brain areas, while the HD-CKD group showed decreased fractional amplitude of low frequency fluctuations in the bilateral pericalcarine cortex. The Regional Homogeneity values in the PD-CKD group were notably different than those in the normal control group, particularly in regions such as the bilateral caudate nucleus and the right putamen. CONCLUSION: Both peritoneal dialysis and hemodialysis modalities impact brain activity, but manifest differently in end-stage renal disease patients. Understanding these differences is crucial for optimizing patient care.

Longitudinal changes in renal volumes evaluated by automated three-dimensional volumetric computed tomography of the whole kidney: The association with the renal function and disease progression.

PURPOSE: To clarify the changes in the total renal volume over time with changes of the renal function using automated 3D volumetric CT of the whole kidney and to evaluate the usefulness of the total renal volume CT measurement in predicting chronic kidney disease (CKD) grade progression. METHODS: A total of 961 patients who underwent abdominal CT at least twice (an interval of more than 4 years) were included. The automated 3D volumetric CT measurement of the whole kidney was performed at the initial and latest CT examination. Patients with CKD grade G2 at the time of the initial CT were divided into two groups: a progression group (CKD grade progressed to G3-G5) and a non-progression group. Changes in the renal volume over time were compared between the two groups. RESULTS: The volume of both kidneys measured on initial CT was positively correlated with eGFR (ρ = 0.490, p < 0.001). There was a significant difference in the initial volume of both kidneys among CKD grades (p < 0.001, G1:318.7 ± 60.5 ml, G2:275.5 ± 53.5 ml, G3:233.7 ± 46.9 ml, G4:183.2 ± 22.5 ml, G5:157.7 ± 77.4 ml). When comparing the progression and non-progression groups, the initial volume of both kidneys was significantly smaller in the progression group, compared with the non-progression group (252.0 ± 50.6 ml vs. 278.9 ± 53.7 ml). In addition, the annual reduction volume in both the right and left kidneys was significantly greater in the progression group than in the non-progression group (p < 0.001). CONCLUSION: The automated 3D volumetric CT measurement of the whole kidney has the potential to monitor changes in renal volume over time with changes of the renal function.

Deferral of Estimated Glomerular Filtration Rate Testing Before Contrast-Enhanced CT in Low-Risk Emergency Department Patients: Assessment of Safety and Impact on Throughput.

OBJECTIVE: To assess the safety and utility of deferring estimated glomerular filtration rate (eGFR) testing before contrast-enhanced CT (CECT) in low-risk emergency department (ED) patients. METHODS: A new question was added to CECT order screens, allowing ordering ED providers to defer eGFR testing in patients deemed low risk for contrast-induced acute kidney injury (AKI). Low risk was defined as no known chronic kidney disease (CKD) or risk factors for AKI or CKD. Patients on chronic dialysis were deemed low risk. The project included three phases: baseline, pilot (optional order question), and full implementation (required order question). Outcomes were operational throughput metrics of CECT order to protocol (O to P) and order to begin (O to B) times. As a balancing safety measure, the proportion of patients deemed to be "low risk" and subsequently found to have eGFR value less than 30 mL/min/1.73 m2 was reported. RESULTS: A total of 16,446 CECT studies were included from four EDs. In the pilot phase, provider engagement rates with the question were low (5%-14%). After full implementation, median O to P time improved from 23.93 min at baseline to 13.02 (P < .0001) and median O to B time improved from 80.34 min to 76.48 (P = .0002). In 0.3% (2 of 646) studies, CECT was completed in patients categorized as low risk by the ED provider with subsequently resulted eGFR <30 mL/min/1.73 m2. DISCUSSION: Upfront clinical risk assessment for AKI and CKD by ED providers can be used to safely defer eGFR testing and improve operational performance for patients requiring CECT.

Renal stiffness measured by shear wave elastography and its relationship with perirenal fat in patients with chronic kidney disease.

PURPOSE: This study aimed to utilize shear wave elastography (SWE) to assess changes in renal stiffness and its influencing factors in patients with chronic kidney disease (CKD) across different estimated glomerular filtration rate (eGFR) categories. It also sought to determine the correlation between perirenal fat (PF) and renal stiffness at various stages of CKD. METHODS: A total of 190 CKD patients and 50 healthy controls were evaluated. Clinical parameters, conventional renal ultrasound measurements, PF, and renal stiffness trends were assessed separately. Factors independently associated with renal stiffness and PF were further analyzed. RESULTS: Renal parenchymal stiffness was significantly higher in the Albumin-CKD G1-2 (ALB-CKD G1-2) and CKD G3 groups than in the control group (p < 0.05). The parenchymal stiffness of the CKD G3 group was higher than that of the ALB-CKD G1-2 group (p < 0.05). The independent factors of renal parenchymal stiffness varied at different stages of disease development, with eGFR and PF being significant factors in the CKD G3 group. PF was elevated in the ALB-CKD G1-2 and CKD G3 groups compared to the control group, and the independent factors of PF varied across different stages, although waist circumference remained a common factor. CONCLUSION: Using SWE to detect renal elastic moduli can effectively assess changes in renal stiffness in patients with CKD with varying eGFRs. PF is an independent factor of renal stiffness in patients with CKD G3, providing a foundation for early diagnosis and clinical treatment.

Diffusion-weighted, intravoxel incoherent motion, and diffusion kurtosis tensor MR imaging in chronic kidney diseases: Correlations with histology.

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.

Performance and Interpretation of Sonography in the Practice of Nephrology: Core Curriculum 2024.

Ultrasonography is increasingly being performed by clinicians at the point of care, and nephrologists are no exception. This Core Curriculum illustrates how ultrasonography can be incorporated into clinical decision making across the spectrum of kidney disease to optimize the care nephrologists provide to patients. Sonography is valuable in outpatient and inpatient settings for the diagnosis and management of acute and chronic kidney disease, evaluation of cystic disease, urinary obstruction, pain, hematuria, proteinuria, assessment of volume status, and in providing guidance for kidney biopsy. As kidney disease advances, ultrasound is useful in the placement and maintenance of temporary and permanent access for dialysis. After kidney transplantation, ultrasonography is critical for evaluation of allograft dysfunction and for biopsies. Sonography skills expedite patient care and enhance the practice of nephrology and are relatively easily acquired with training. It is our hope that this curriculum will encourage nephrologists to learn and apply this valuable skill.

Kidney shape statistical analysis: associations with disease and anthropometric factors.

BACKGROUND: Organ measurements derived from magnetic resonance imaging (MRI) have the potential to enhance our understanding of the precise phenotypic variations underlying many clinical conditions. METHODS: We applied morphometric methods to study the kidneys by constructing surface meshes from kidney segmentations from abdominal MRI data in 38,868 participants in the UK Biobank. Using mesh-based analysis techniques based on statistical parametric maps (SPMs), we were able to detect variations in specific regions of the kidney and associate those with anthropometric traits as well as disease states including chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension. Statistical shape analysis (SSA) based on principal component analysis was also used within the disease population and the principal component scores were used to assess the risk of disease events. RESULTS: We show that CKD, T2D and hypertension were associated with kidney shape. Age was associated with kidney shape consistently across disease groups. Body mass index (BMI) and waist-to-hip ratio (WHR) were also associated with kidney shape for the participants with T2D. Using SSA, we were able to capture kidney shape variations, relative to size, angle, straightness, width, length, and thickness of the kidneys, within disease populations. We identified significant associations between both left and right kidney length and width and incidence of CKD (hazard ratio (HR): 0.74, 95% CI: 0.61-0.90, p < 0.05, in the left kidney; HR: 0.76, 95% CI: 0.63-0.92, p < 0.05, in the right kidney) and hypertension (HR: 1.16, 95% CI: 1.03-1.29, p < 0.05, in the left kidney; HR: 0.87, 95% CI: 0.79-0.96, p < 0.05, in the right kidney). CONCLUSIONS: The results suggest that shape-based analysis of the kidneys can augment studies aiming at the better categorisation of pathologies associated with chronic kidney conditions.

Electric impedance tomography enables portable and non-invasive approach to screen and monitor chronic kidney disease.

Chronic kidney disease (CKD) is an escalating global health concern, and non-invasive means for early CKD detection is eagerly awaited. Here, we explore the potential of using home-based frequency-difference electrical impedance tomography (fdEIT) to evaluate CKD based on bio-conductivity characteristics. We performed bio-conductivity measurement in vivo paired with standard estimated glomerular filtration rate (eGFR) measurements on a N=126 CKD patients by EIT and traditional blood and urine tests, respectively. We developed an EIT processing pipeline that extracts the kidney regions from EIT images. We further developed a regression model and a CKD classification scheme. Our results showed a significant correlation between EIT-features and eGFR, and the classification scheme shows sensitivity and specificity of 76.2% and 74.6% respectively considering stages 1 and 2 CKD versus stages 3, 4 and 5 CKD. These results suggest the feasibility of EIT to be used as a portable, self-administrated and home-based approach for CKD early diagnostic screening and longitudinal monitoring.Clinical Relevance-The results presented here demonstrates a cost-effective, home-based and self-administrative screening process on chronic kidney disease patients, thereby enhancing the quality and area of possible application of telemedicine. By achieving this, the process presented here can relieve the burden of public health system.

Examination of alternative eGFR definitions on the performance of deep learning models for detection of chronic kidney disease from fundus photographs.

Deep learning (DL) models have shown promise in detecting chronic kidney disease (CKD) from fundus photographs. However, previous studies have utilized a serum creatinine-only estimated glomerular rate (eGFR) equation to measure kidney function despite the development of more up-to-date methods. In this study, we developed two sets of DL models using fundus images from the UK Biobank to ascertain the effects of using a creatinine and cystatin-C eGFR equation over the baseline creatinine-only eGFR equation on fundus image-based DL CKD predictors. Our results show that a creatinine and cystatin-C eGFR significantly improved classification performance over the baseline creatinine-only eGFR when the models were evaluated conventionally. However, these differences were no longer significant when the models were assessed on clinical labels based on ICD10. Furthermore, we also observed variations in model performance and systemic condition incidence between our study and the ones conducted previously. We hypothesize that limitations in existing eGFR equations and the paucity of retinal features uniquely indicative of CKD may contribute to these inconsistencies. These findings emphasize the need for developing more transparent models to facilitate a better understanding of the mechanisms underpinning the ability of DL models to detect CKD from fundus images.

Retinal changes and cardiac biomarker assessment in relation to chronic kidney disease: a single centre study.

BACKGROUND: The prevalence of chronic kidney disease (CKD) is rising in Malaysia. Early detection is necessary to prevent disease progression, especially in terms of cardiovascular (CV) risk, the main cause of death in end-stage renal disease (ESRD). Retinal changes have proven to be a good predictor of CKD whereas cardiac biomarkers are useful in cardiovascular risk stratification. We aimed to demonstrate the correlation between retinal changes and cardiac biomarkers with CKD. METHODS: This single-centre cross-sectional study was conducted among patients with CKD stages 3, 4, and 5 (not on dialysis) from the Nephrology Clinic, Universiti Kebangsaan Malaysia Medical Centre. A total of 84 patients were recruited with an even distribution across all three stages. They underwent fundus photography where images were analysed for vessel calibre (central retinal venular equivalent (CRVE), central retinal arterial equivalent (CRAE), and tortuosity indices. Optical coherence tomography was used to measure macular volume. Blood samples were sent for laboratory measurement of high-sensitivity C-reactive protein (hs-CRP) and asymmetric dimethylarginine (ADMA). These parameters were analysed in relation to CKD. RESULTS: The mean age was 58.8 ± 11.7 years, with 52.4% male and 47.6% female patients. Among them, 64.3% were diabetics. Retinal vessel tortuosity (r = -0.220, p-value = 0.044) had a negative correlation with the estimated glomerular filtration rate (eGFR). CRVE showed a positive correlation with proteinuria (r = 0.342, p = 0.001) but negative correlation with eGFR (r = -0.236, p = 0.031). Hs-CRP positively correlated with proteinuria (r = 0.313, p = 0.04) and negatively correlated with eGFR (r = -0.370, p = 0.001). Diabetic patients had a higher CRVE compared to non-diabetic patients (p = 0.02). History of ischaemic heart disease was associated with a smaller macula volume (p = 0.038). Male gender (r2 = 0.066, p = 0.031) and HbA1c had a positive influence (r2 = 0.066, p = 0.047) on retinal vessel tortuosity. There was a positive influence of age (r2 = 0.183, p = 0.012) and hs-CRP (r2 = 0.183, p = 0.045) on CRVE. As for macula volume, it negatively correlated with diabetes (r2 = 0.015, p = 0.040) and positively correlated with smoking (r2 = 0.015, p = 0.012). CONCLUSION: Our study showed that eGFR value affects retinal vessel tortuosity, CRVE and hs-CRP. These parameters bear potential to be used as non-invasive tools in assessing CKD. However, only macula volume may be associated with CVD risk among the CKD population.

Diagnostic assessment of two-dimensional shear wave elastography in relation to dimethyl arginine levels in dogs with chronic kidney disease.

BACKGROUND: In veterinary medicine, previous studies regarding the diagnostic performance of shear wave elastography (SWE) in chronic kidney disease (CKD) are not consistent with each other. Moreover, there has been no study evaluating the relationship between symmetric dimethyl arginine (SDMA) concentration and renal shear wave velocity (SWV) using two-dimensional SWE (2D SWE) in dogs with CKD. OBJECTIVES: This study aimed to evaluate the diagnostic capability of 2D SWE in dogs with CKD and to assess the relationship between renal SWV and SDMA concentration. METHODS: Dogs with healthy kidneys and dogs with CKD underwent 2D SWE and SDMA assay. Renal stiffness was estimated as renal SWV in m/s. RESULTS: SDMA concentration had a weak positive correlation with the left (r = 0.338, p = 0.022) and right renal SWV (r = 0.337, p = 0.044). Renal SWV was not significantly different between healthy kidney and CKD groups in the left (p = 0.085) and right (p = 0.171) kidneys. CONCLUSIONS: 2D SWE may could not distinguish between dogs with healthy kidney and dogs with early stage of CKD, but it would be useful for assessing the serial change of renal function in dogs.

Development of a novel combined nomogram model integrating deep learning radiomics to diagnose IgA nephropathy clinically.

This study aimed to develop and validate a combined nomogram model based on superb microvascular imaging (SMI)-based deep learning (DL), radiomics characteristics, and clinical factors for noninvasive differentiation between immunoglobulin A nephropathy (IgAN) and non-IgAN.We prospectively enrolled patients with chronic kidney disease who underwent renal biopsy from May 2022 to December 2022 and performed an ultrasound and SMI the day before renal biopsy. The selected patients were randomly divided into training and testing cohorts in a 7:3 ratio. We extracted DL and radiometric features from the two-dimensional ultrasound and SMI images. A combined nomograph model was developed by combining the predictive probability of DL with clinical factors using multivariate logistic regression analysis. The proposed model's utility was evaluated using receiver operating characteristics, calibration, and decision curve analysis. In this study, 120 patients with primary glomerular disease were included, including 84 in the training and 36 in the test cohorts. In the testing cohort, the ROC of the radiomics model was 0.816 (95% CI:0.663-0.968), and the ROC of the DL model was 0.844 (95% CI:0.717-0.971). The nomogram model combined with independent clinical risk factors (IgA and hematuria) showed strong discrimination, with an ROC of 0.884 (95% CI:0.773-0.996) in the testing cohort. Decision curve analysis verified the clinical practicability of the combined nomogram. The combined nomogram model based on SMI can accurately and noninvasively distinguish IgAN from non-IgAN and help physicians make clearer patient treatment plans.

Application of Real-Time Sound Touch Elastography for Evaluating Chronic Kidney Disease of Transplanted Kidneys.

BACKGROUND: If chronic allograft nephropathy can be detected early and treated, the long-term survival rate of the transplanted kidney may be effectively improved. PURPOSE: To compare the application value of real-time sound touch elastography (STE), strain elastography, and color Doppler flow imaging in evaluating chronic kidney disease of transplanted kidneys. MATERIALS AND METHODS: A total of 101 patients with renal transplantation were divided into a normal group (serum creatinine <134 mol/L, 58 patients) and a chronic allograft nephropathy group after renal transplantation over 6 months (serum creatinine >134 mol/L, 43 patients). The maximum elastic modulus (Emax) was determined, and receiver operator characteristics were used to compare the diagnostic efficacy of STE ultrasound. RESULTS: Emean, Emax, B/A (the strain rate of the internal oblique muscle tissue/ the strain rate of the central renal cortex) of cortical standard strain ratio in strain elastography, and resistance index (RI) between normal and chronic allograft nephropathy groups have statistical significance (P < .05). Emax is superior to B/A and arcuate artery RI in the chronic cortex in the diagnosis of renal dysfunction, and the area under the receiver operator characteristics curve is 0.88. The estimated glomerular filtration rate was negatively correlated with renal cortex Emax, B/A, and arcuate artery RI, among which Emax was the strongest (r = - 0.713, P < .001). The renal cortical Emax cut-off was 30.95 kPa, the sensitivity was 92%, the specificity was 88%, and the accuracy was 88%. CONCLUSION: The STE technique to evaluate chronic renal dysfunction after renal transplantation is more sensitive than traditional strain-type elastography and hemodynamic parameters, with renal function decline, renal cortex Emax, renal cortical B/A, and arcuate artery RI gradually increased, and renal cortex Emax was particularly obvious.

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comprised 100 participants with renal dysfunction (RD; eGFR < 45 mL/min/1.73 m2) and 70 without (non-RD; eGFR ≥ 45 mL/min/1.73 m2). The model was applied to the right, left, and both kidneys; it was first evaluated on the non-RD group data and subsequently on the combined data of the RD and non-RD groups. For bilateral kidney segmentation of the non-RD group, the best performance was obtained when using IP image, with a Dice score of 0.902 ± 0.034, average surface distance of 1.46 ± 0.75 mm, and a difference of - 27 ± 21 mL between ground-truth and automatically computed volume. Slightly worse results were obtained for the combined data of the RD and non-RD groups and for unilateral kidney segmentation, particularly when segmenting the right kidney from the OP images. Our 3D CNN-assisted automatic segmentation tools can be utilized in future studies on total kidney volume measurements and various image analyses of a large number of patients with CKD.