Basic principles and new advances in kidney imaging

A European Renal Association (ERA) synopsis for nephrology practice of the 2023 European Society of Hypertension (ESH) Guidelines for the Management of Arterial Hypertension

In June 2023, the European Society of Hypertension (ESH) presented and published the new 2023 ESH Guidelines for the Management of Arterial Hypertension, a document that was endorsed by the European Renal Association (ERA). Following the evolution of evidence in recent years, several novel recommendations relevant to the management of hypertension in patients with chronic kidney disease (CKD) appeared in these Guidelines. These include recommendations for target office blood pressure (BP) <130/80 mmHg in most and against target office BP <120/70 mmHg in all patients with CKD; recommendations for use of spironolactone or chlorthalidone for patients with resistant hypertension with estimated glomerular filtration rate (eGFR) higher or lower than 30 mL/min/1.73 m2, respectively; use of a sodium-glucose cotransporter 2 inhibitor for patients with CKD and estimated eGFR ≥20 mL/min/1.73 m2; use of finerenone for patients with CKD, type 2 diabetes mellitus, albuminuria, eGFR ≥25 mL/min/1.73 m2 and serum potassium <5.0 mmol/L; and revascularization in patients with atherosclerotic renovascular disease and secondary hypertension or high-risk phenotypes if stenosis ≥70% is present. The present report is a synopsis of sections of the ESH Guidelines that are relevant to the daily clinical practice of nephrologists, prepared by experts from ESH and ERA. The sections summarized are those referring to the role of CKD in hypertension staging and cardiovascular risk stratification, the evaluation of hypertension-mediated kidney damage and the overall management of hypertension in patients with CKD.

Evaluation of split renal dysfunction using radiomics based on magnetic resonance diffusion-weighted imaging

BACKGROUND

Accurate and noninvasive assessment of split renal dysfunction is crucial, while there is lack of corresponding method clinically.

PURPOSE

To investigate the feasibility of using diffusion-weighted imaging (DWI)-based radiomics models to evaluate split renal dysfunction.

METHODS

We enrolled patients with impaired and normal renal function undergoing renal DWI examination. Glomerular filtration rate (GFR, mL/min) was measured using 99mTc-DTPA scintigraphy, which is reference standard of GFR measurement. The kidneys were classified into normal (GFR ≥40), mildly impaired (20≤ GFR < 40), moderately impaired (10≤ GFR < 20), and severely impaired (GFR < 10) renal function groups. Optimized subsets of radiomics features were selected from renal DWI images and radiomics scores (Rad-score) calculated to discriminate groups with different renal function. The radiomics model (Rad-score based) was developed in a training cohort and validated in a test cohort. Evaluations were conducted on the discrimination, calibration, and clinical application of the method.

RESULTS

The final analysis included 330 kidneys. Logistic regression was used to develop three radiomics models, model A, B, and C, which were used to distinguish normal from impaired, mild from moderate, and moderate from severe renal function, respectively. The area under the curve of the three models were 0.822, 0.704, and 0.887 in the training cohort and 0.843, 0.717, and 0.897 in the test cohort, respectively, indicating efficient discrimination performance.

CONCLUSIONS

DWI-based radiomics models have potential for evaluating split renal dysfunction and discriminating between normal and impaired renal function groups and their subgroups.

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification

Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore, this approach holds significant potential in supporting MRI data-driven preclinical investigations into the intricate mechanisms underlying renal pathophysiology. The integration of deep learning algorithms is crucial in achieving rapid and precise segmentation of the kidney from temporally resolved parametric MRI, facilitating the use of kidney size as a meaningful (pre)clinical biomarker for renal disease. To explore this potential, we employed dynamic parametric T2 mapping of the kidney in rats in conjunction with a custom-tailored deep dilated U-Net (DDU-Net) architecture. The architecture was trained, validated, and tested on manually segmented ground truth kidney data, with benchmarking against an analytical segmentation model and a self-configuring no new U-Net. Subsequently, we applied our approach to in vivo longitudinal MRI data, incorporating interventions that emulate clinically relevant scenarios in rats. Our approach achieved high performance metrics, including a Dice coefficient of 0.98, coefficient of determination of 0.92, and a mean absolute percentage error of 1.1% compared with ground truth. The DDU-Net enabled automated and accurate quantification of acute changes in kidney size, such as aortic occlusion (-8% ± 1%), venous occlusion (5% ± 1%), furosemide administration (2% ± 1%), hypoxemia (-2% ± 1%), and contrast agent-induced acute kidney injury (11% ± 1%). This approach can potentially be instrumental for the development of dynamic parametric MRI-based tools for kidney disorders, offering unparalleled insights into renal pathophysiology.

Automatic identification of hypertension and assessment of its secondary effects using artificial intelligence: A systematic review (2013-2023)

Artificial Intelligence (AI) techniques are increasingly used in computer-aided diagnostic tools in medicine. These techniques can also help to identify Hypertension (HTN) in its early stage, as it is a global health issue. Automated HTN detection uses socio-demographic, clinical data, and physiological signals. Additionally, signs of secondary HTN can also be identified using various imaging modalities. This systematic review examines related work on automated HTN detection. We identify datasets, techniques, and classifiers used to develop AI models from clinical data, physiological signals, and fused data (a combination of both). Image-based models for assessing secondary HTN are also reviewed. The majority of the studies have primarily utilized single-modality approaches, such as biological signals (e.g., electrocardiography, photoplethysmography), and medical imaging (e.g., magnetic resonance angiography, ultrasound). Surprisingly, only a small portion of the studies (22 out of 122) utilized a multi-modal fusion approach combining data from different sources. Even fewer investigated integrating clinical data, physiological signals, and medical imaging to understand the intricate relationships between these factors. Future research directions are discussed that could build better healthcare systems for early HTN detection through more integrated modeling of multi-modal data sources.

Contrast Agent-Free 3D Renal Ultrafast Doppler Imaging Reveals Vascular Dysfunction in Acute and Diabetic Kidney Diseases

To combat the irreversible decline in renal function associated with kidney disease, it is essential to establish non-invasive biomarkers for assessing renal microcirculation. However, the limited resolution and/or vascular sensitivity of existing diagnostic imaging techniques hinders the visualization of complex cortical vessels. Here, a 3D renal ultrafast Doppler (UFD) imaging system that uses a high ultrasound frequency (18 MHz) and ultrahigh frame rate (1 KHz per slice) to scan the entire volume of a rat's kidney in vivo is demonstrated. The system, which can visualize the full 3D renal vascular branching pyramid at a resolution of 167 µm without any contrast agent, is used to chronically and noninvasively monitor kidneys with acute kidney injury (AKI, 3 days) and diabetic kidney disease (DKD, 8 weeks). Multiparametric UFD analyses (e.g., vessel volume occupancy (VVO), fractional moving blood volume (FMBV), vessel number density (VND), and vessel tortuosity (VT)) describe rapid vascular rarefaction from AKI and long-term vascular degeneration from DKD, while the renal pathogeneses are validated by in vitro blood serum testing and stained histopathology. This work demonstrates the potential of 3D renal UFD to offer valuable insights into assessing kidney perfusion levels for future research in diabetes and kidney transplantation.

Effective deep learning classification for kidney stone using axial computed tomography (CT) images

INTRODUCTION

Stone formation in the kidneys is a common disease, and the high rate of recurrence and morbidity of the disease worries all patients with kidney stones. There are many imaging options for diagnosing and managing kidney stone disease, and CT imaging is the preferred method.

OBJECTIVES

Radiologists need to manually analyse large numbers of CT slices to diagnose kidney stones, and this process is laborious and time-consuming. This study used deep automated learning (DL) algorithms to analyse kidney stones. The primary purpose of this study is to classify kidney stones accurately from CT scans using deep learning algorithms.

METHODS

The Inception-V3 model was selected as a reference in this study. Pre-trained with other CNN architectures were applied to a recorded dataset of abdominal CT scans of patients with kidney stones labelled by a radiologist. The minibatch size has been modified to 7, and the initial learning rate was 0.0085.

RESULTS

The performance of the eight models has been analysed with 8209 CT images recorded at the hospital for the first time. The training and test phases were processed with limited authentic recorded CT images. The outcome result of the test shows that the Inception-V3 model has a test accuracy of 98.52 % using CT images in detecting kidney stones.

CONCLUSIONS

The observation is that the Inception-V3 model is successful in detecting kidney stones of small size. The performance of the Inception-V3 Model is at a high level and can be used for clinical applications. The research helps the radiologist identify kidney stones with less computational cost and disregards the need for many experts for such applications.

Chronic kidney disease in children: an update

Chronic kidney disease (CKD) is a major healthcare issue worldwide. However, the prevalence of pediatric CKD has never been systematically assessed and consistent information is lacking in this population. The current definition of CKD is based on glomerular filtration rate (GFR) and the extent of albuminuria. Given the physiological age-related modification of GFR in the first years of life, the definition of CKD is challenging per se in the pediatric population, resulting in high risk of underdiagnosis in this population, treatment delays and untailored clinical management. The advent and spreading of massive-parallel sequencing technology has prompted a profound revision of the epidemiology and the causes of CKD in children, supporting the hypothesis that CKD is much more frequent than currently reported in children and adolescents. This acquired knowledge will eventually converge in the identification of the molecular pathways and cellular response to damage, with new specific therapeutic targets to control disease progression and clinical features of children with CKD. In this review, we will focus on recent innovations in the field of pediatric CKD and in particular those where advances in knowledge have become available in the last years, with the aim of providing a new perspective on CKD in children and adolescents.

Direct mapping of kidney function by DCE-MRI urography using a tetrazinanone organic radical contrast agent

Chronic kidney disease (CKD) and acute kidney injury (AKI) are ongoing global health burdens. Glomerular filtration rate (GFR) is the gold standard measure of kidney function, with clinical estimates providing a global assessment of kidney health without spatial information of kidney- or region-specific dysfunction. The addition of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to the anatomical imaging already performed would yield a 'one-stop-shop' for renal assessment in cases of suspected AKI and CKD. Towards urography by DCE-MRI, we evaluated a class of nitrogen-centered organic radicals known as verdazyls, which are extremely stable even in highly reducing environments. A glucose-modified verdazyl, glucoverdazyl, provided contrast limited to kidney and bladder, affording functional kidney evaluation in mouse models of unilateral ureteral obstruction (UUO) and folic acid-induced nephropathy (FAN). Imaging outcomes correlated with histology and hematology assessing kidney dysfunction, and glucoverdazyl clearance rates were found to be a reliable surrogate measure of GFR.

Current progress in artificial intelligence-assisted medical image analysis for chronic kidney disease: A literature review

Chronic kidney disease (CKD) causes irreversible damage to kidney structure and function. Arising from various etiologies, risk factors for CKD include hypertension and diabetes. With a progressively increasing global prevalence, CKD is an important public health problem worldwide. Medical imaging has become an important diagnostic tool for CKD through the non-invasive identification of macroscopic renal structural abnormalities. Artificial intelligence (AI)-assisted medical imaging techniques aid clinicians in the analysis of characteristics that cannot be easily discriminated by the naked eye, providing valuable information for the identification and management of CKD. Recent studies have demonstrated the effectiveness of AI-assisted medical image analysis as a clinical support tool using radiomics- and deep learning-based AI algorithms for improving the early detection, pathological assessment, and prognostic evaluation of various forms of CKD, including autosomal dominant polycystic kidney disease. Herein, we provide an overview of the potential roles of AI-assisted medical image analysis for the diagnosis and management of CKD.

Renal hemodynamic changes in patients with type 2 diabetes and their clinical impact

The dysfunction of the internal mechanics within the kidney's filtering units, known as glomeruli, has been linked to the emergence and progression of diabetic kidney disease (DKD). To better understand this crucial aspect of kidney function and the pathology of DKD, a variety of methods are employed in research, from the introduction of external compounds, such as inulin, iohexol, iothalamate and p-aminohippurate, to cutting-edge imaging techniques and computational analysis. Given the significance of intraglomerular hemodynamic dysfunction in the pathogenesis and treatment of DKD, it is essential to thoroughly examine the available data on this topic. Accordingly, the aim of this review is to provide a comprehensive appraisal of the role of intraglomerular hemodynamic dysfunction in the development of DKD and the effects of current therapies used to mitigate DKD. Through this analysis, we can gain a deeper understanding of the complex pathogenesis of DKD and potentially discover new avenues for tailored therapeutic management of patients with DKD.

Anomalous kinetics of galactose-deficient IgA incurring nephropathy revealed by cross-scale optical imaging

IgA nephropathy (IgAN) is the most common glomerulonephritis, characterized by the presence of predominant IgA deposits in the mesangium. Deposition of pathogenic IgA in kidney tissue is a fundamental initiating process that has not been fully studied. Here, we employed optical imaging to directly visualize kidney deposition of IgA with optimized spatial and temporal resolution in BALB/c nude mice. Real-time fluorescence imaging revealed that IgA isolated from patients with IgAN preferentially accumulated in the kidneys, compared with IgA purified from healthy individuals. There was no difference in the distribution of either IgA preparation by the liver. Photoacoustic computed tomography dynamically demonstrated and quantified the enhanced retention of pathological IgA in the kidney cortex. Photoacoustic microscopy tracked IgA deposition in the glomeruli with a resolution down to three microns in a mouse model. Notably, longitudinal fluorescent imaging revealed that galactose-deficient IgA (Gd-IgA), which was elevated in the circulation of patients with IgAN, persisted in the kidney for longer than two weeks, and stable deposition of Gd-IgA induced kidney impairment, including albuminuria and mesangial proliferation. Thus, our study highlights that the aberrant kidney depositional kinetics of Gd-IgA is involved in the pathogenesis of IgAN. Hence, cross-scale optical imaging has potential applications in assessing immune-mediated kidney diseases and uncovering underlying mechanisms of disease.

Monitoring kidney size to interpret MRI-based assessment of renal oxygenation in acute pathophysiological scenarios

AIM

Tissue hypoxia is an early key feature of acute kidney injury. Assessment of renal oxygenation using magnetic resonance imaging (MRI) markers T₂ and T₂ * enables insights into renal pathophysiology. This assessment can be confounded by changes in the blood and tubular volume fractions, occurring upon pathological insults. These changes are mirrored by changes in kidney size (KS). Here, we used dynamic MRI to monitor KS for physiological interpretation of T₂ * and T₂ changes in acute pathophysiological scenarios.

METHODS

KS was determined from T₂ *, T₂ mapping in rats. Six interventions that acutely alter renal tissue oxygenation were performed directly within the scanner, including interventions that change the blood and/or tubular volume. A biophysical model was used to estimate changes in O₂ saturation of hemoglobin from changes in T₂ * and KS.

RESULTS

Upon aortic occlusion KS decreased; this correlated with a decrease in T₂ *, T₂ . Upon renal vein occlusion KS increased; this negatively correlated with a decrease in T₂ *, T₂ . Upon simultaneous occlusion of both vessels KS remained unchanged; there was no correlation with decreased T₂ *, T₂ . Hypoxemia induced mild reductions in KS and T₂ *, T₂ . Administration of an X-ray contrast medium induced sustained KS increase, with an initial increase in T₂ *, T₂ followed by a decrease. Furosemide caused T₂ *, T₂ elevation and a minor increase in KS. Model calculations yielded physiologically plausible calibration ratios for T₂ *.

CONCLUSION

Monitoring KS allows physiological interpretation of acute renal oxygenation changes obtained by T₂ *, T₂ . KS monitoring should accompany MRI-oximetry, for new insights into renal pathophysiology and swift translation into human studies.

Parametric MRI Detects Aristolochic Acid Induced Acute Kidney Injury

Exposure to aristolochic acid (AA) is of increased concern due to carcinogenic and nephrotoxic effects, and incidence of aristolochic acid nephropathy (AAN) is increasing. This study characterizes renal alterations during the acute phase of AAN using parametric magnetic resonance imaging (MRI). An AAN and a control group of male Wistar rats received administration of aristolochic acid I (AAI) and polyethylene glycol (PEG), respectively, for six days. Both groups underwent MRI before and 2, 4 and 6 days after AAI or PEG administration. T₂ relaxation times and apparent diffusion coefficients (ADCs) were determined for four renal layers. Serum creatinine levels (sCr) and blood urea nitrogen (BUN) were measured. Tubular injury scores (TIS) were evaluated based on histologic findings. Increased T₂ values were detected since day 2 in the AAN group, but decreased ADCs and increased sCr levels and BUN were not detected until day 4. Significant linear correlations were observed between T₂ of the cortex and the outer stripe of outer medulla and TIS. Our results demonstrate that parametric MRI facilitates early detection of renal injury induced by AAI in a rat model. T₂ mapping may be a valuable tool for assessing kidney injury during the acute phase of AAN.

Unmet needs in clinical trials in CKD: questions we have not answered and answers we have not questioned

Many advances have been made in the field of nephrology over the last decade. These include an increasing focus on patient-centred involvement in trials, exploration of innovative trial designs and methodology, the growth of personalized medicine and, most importantly, novel therapeutic agents that are disease-modifying for large groups of patients with and without diabetes and chronic kidney disease. Despite this progress, many questions remain unanswered and we have not critically evaluated some of our assumptions, practices and guidelines despite emerging evidence to challenge current paradigms and discrepant patient-preferred outcomes. How best to implement best practices, diagnose various conditions, examine better diagnostic tools, treat laboratory values versus patients and understand prediction equations in the clinical context remain unanswered. As we enter a new era in nephrology, there are extraordinary opportunities to change the culture and care. Rigorous research paradigms enabling both the generation and the use of new information should be explored. We identify here some key areas of interest and suggest renewed efforts to describe and address these gaps so that we can develop, design and execute trials of importance to all.

Quantitative Analysis of Renal Perfusion in Rhabdomyolysis-Induced Acute Kidney Injury Using Contrast-Enhanced Ultrasound: An Experimental Study

The aim of this study was to evaluate renal perfusion changes in rats with acute kidney injury induced by rhabdomyolysis, using quantitative parameters obtained with contrast-enhanced ultrasound (CEUS). Sprague-Dawley (SD) rats were randomly divided into an experimental group (n = 40) and a control group (n = 20). Each group was further divided into four subgroups (0.5-, 6-, 24- and 72-h groups). Time-intensity curves and related quantitative parameters of the renal cortex and medulla were obtained by CEUS, and the contrast characteristics analyzed for different time points. In the experimental group, the CEUS quantitative parameters for the renal medulla of time to peak (TTP), descending time/2 (DT/2) and area under the curve (AUC) increased, whereas ascending slope (AS) and descending slope (DS) decreased. Similarly, renal cortical AS, DS and AUC in the experimental group differed significantly from those in the control group. With respect to the CEUS quantitative parameters for the renal cortex, AUC increased, and AS and DS decreased. These parameters differed significantly between the experimental and control groups. CEUS is sensitive to change in renal perfusion in rhabdomyolysis-induced acute kidney injury and, thus, has diagnostic value.

Current Use and Complementary Value of Combining in Vivo Imaging Modalities to Understand the Renoprotective Effects of Sodium-Glucose Cotransporter-2 Inhibitors at a Tissue Level

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) were initially developed to treat diabetes and have been shown to improve renal and cardiovascular outcomes in patients with- but also without diabetes. The mechanisms underlying these beneficial effects are incompletely understood, as is the response variability between- and within patients. Imaging modalities allow in vivo quantitative assessment of physiological, pathophysiological, and pharmacological processes at kidney tissue level and are therefore increasingly being used in nephrology. They provide unique insights into the renoprotective effects of SGLT2i and the variability in response and may thus contribute to improved treatment of the individual patient. In this mini-review, we highlight current work and opportunities of renal imaging modalities to assess renal oxygenation and hypoxia, fibrosis as well as interaction between SGLT2i and their transporters. Although every modality allows quantitative assessment of particular parameters of interest, we conclude that especially the complementary value of combining imaging modalities in a single clinical trial aids in an integrated understanding of the pharmacology of SGLT2i and their response variability.

High-performance renal imaging with a radiolabeled, non-excretable chimeric fusion protein

Ideal nuclear imaging tracers should exhibit high target uptake and low background signal. Traditional renal scintigraphy and SPECT scans examine kidney function via static or dynamic tracing of radioactive probes in the kidneys. The lack of tracer affinity to specific biological processes and high background uptake from urinary excretion have added many difficulties to precision renal diagnosis. In this issue of Theranostics, Jin and colleagues innovatively devised a recombinant probe for preferential kidney imaging through targeting of tubular neonatal Fc receptor and proximal tubular basement membrane for sustained tubular reabsorption and accumulation. This work has broad implications regarding how an in depth understanding of physiology and pathology may be of service for tracer development, renal diagnosis, and disease theranostics.

Novel Uses of Ultrasound to Assess Kidney Mechanical Properties

Ultrasound is a key imaging tool for evaluating the kidney. Over the last two decades, methods to measure the mechanical properties of soft tissues have been developed and used in clinical practice, although use in the kidney has not been as widespread as for other applications. The mechanical properties of the kidney are determined by the structure and composition of the renal parenchyma and perfusion characteristics. Because pathologic processes change these factors, the mechanical properties change and can be used for diagnostic purposes and for monitoring treatment or disease progression. Ultrasound-based elastography methods for evaluating the mechanical properties of the kidney use focused ultrasound beams to perturb the kidney and then high frame-rate ultrasound methods are used to measure the resulting motion. The motion is analyzed to estimate the mechanical properties. This review will describe the principles of these methods and discuss several seminal studies related to characterizing the kidney. Additionally, an overview of the clinical use of elastography methods in native and kidney allografts will be provided. Perspectives on future developments and uses of elastography technology along with other complementary ultrasound imaging modalities will be provided.