Magnetic resonance imaging biomarkers for chronic kidney disease: a position paper from the European Cooperation in Science and Technology Action PARENCHIMA

T1 Relaxation Time for the Prediction of Renal Transplant Dysfunction

Quantitative magnetic resonance imaging (MRI) is emerging as a non-invasive tool to measure tissue scarring in renal allografts. However, whether prolonged T1 relaxation time results in lower transplant survival rates is unknown. This retrospective cohort study analyzed the capability to predict renal allograft dysfunction based on median T1 time. Forty-six transplant recipients with non-contrast 1.5T MRI and allograft biopsy were included. The primary endpoint was the eGFR slope over 24 months. T1 relaxation time correlated significantly with eGFR levels at all follow-up stages. Patients with T1 relaxation time above the median (T1 high) had a consistent decline in kidney function as compared to the patient group below the median (T1 low): overall eGFR slope: 11.3 vs. 1.4 mL/min/1.73 m2 over 24 months, p = 0.016. Graft survival rates at 24 months were 52% in the T1 high vs. 87% in the T1 low group, p = 0.0015. ROC analysis discovered a positive predictive value of 52% and a negative predictive value of 91% for graft loss. T1 mapping identified patients with a persistent decline of allograft function and an increased risk of allograft loss. MRI could significantly influence monitoring strategies in transplant surveillance, offering a safe, non-invasive alternative to traditional diagnostic methods.

Magnetic resonance diffusion tensor imaging is superior to arterial spin labeling in detecting renal allograft fibrosis

Background

Although both magnetic resonance (MR) diffusion tensor imaging (DTI) and arterial spin labeling (ASL) have been demonstrated to be useful for the assessment of renal allograft fibrosis, their diagnostic value for renal allograft fibrosis is rarely compared. In this study, we collected a relatively large sample size to compare the value of DTI and ASL in the assessment of renal transplantation (RT) fibrosis.

Methods

This study included 141 kidney transplant recipients who underwent DTI, ASL, and biopsy. The renal allograft fibrosis was divided into ci0, ci1, ci2, and ci3 fibrosis groups according to the biopsy results. The apparent diffusion coefficient (ADC), fractional anisotropy (FA), and renal blood flow (RBF) were calculated. One-way analysis of variance (ANOVA) was used to compare the differences of functional magnetic resonance imaging (MRI) parameters between different fibrosis subgroups. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate diagnostic performance.

Results

The medullary FA values in ci2 (0.27±0.04, P<0.001) and ci3 (0.21±0.03, P<0.001) groups were significantly lower than those in ci0 group (0.31±0.05). The medullary FA value in ci3 group (0.21±0.03) was significantly lower than that in ci1 group (0.30±0.07, P<0.001) and ci2 group (0.27±0.04, P<0.01). The AUC of DTI was found to be higher than that of ASL in accurately identifying renal allograft fibrosis, and the result was statistically significant in differentiating ci0-2 group and ci3 group (ci0 vs. ci1-3, 0.725 vs. 0.712, P>0.05; ci0-1 vs. ci2-3, 0.787 vs. 0.735, P>0.05; ci0-2 vs. ci3, 0.945 vs. 0.802, P<0.05).

Conclusions

DTI has a higher diagnostic value than ASL in noninvasive identification of the degree of renal allograft fibrosis.

Repeatability, Reproducibility, and Observer Variability of Cortical T1 Mapping for Renal Tissue Characterization

BACKGROUND

The global rise in kidney diseases underscores the need for reliable, noninvasive imaging biomarkers. Among these, renal cortical T1 has shown promise but further technical validation is still required.

PURPOSE

To evaluate the repeatability, reproducibility, and observer variability of kidney cortical T1 mapping in human volunteers without known renal disease.

STUDY TYPE

Prospective.

SUBJECTS

Three cohorts without renal disease: 1) 25 volunteers (median age 38 [interquartile range, IQR: 28-42] years, female N = 11) for scan-rescan assessments on GE 1.5 T and Siemens 1.5 T; 2) 29 volunteers (median age 29 [IQR: 24-40] years, female N = 15) for scan-rescan assessments on Siemens 3 T; and 3) 16 volunteers (median age 34 [IQR: 31-42] years, female N = 8) for cross-scanner reproducibility.

FIELD STRENGTH/SEQUENCES

1.5 T and 3 T, a modified Look-Locker imaging (MOLLI) sequence with a balanced steady-state free precession (bSSFP) readout.

ASSESSMENT

Kidney cortical T1 data was acquired on GE 1.5 T scanner, Siemens 1.5 T and 3 T scanners. Within-scanner repeatability and inter/intra-observer variability: GE 1.5 T and Siemens 1.5 T, and cross-scanner manufacturer reproducibility: Siemens 1.5 T-GE 1.5 T.

STATISTICAL TESTS

Bland Altman analysis, coefficient of variation (CoV), intra-class coefficient (ICC), and repeatability coefficient (RC).

RESULTS

Renal cortical T1 mapping showed high repeatability and reliability across scanner field strengths and manufacturers (repeatability: CoV 1.9%-2.8%, ICC 0.79-0.88, pooled RC 73 msec; reproducibility: CoV 3.0%, ICC 0.75, RC 90 msec). The method also showed robust observer variability (CoV 0.6%-1.4%, ICC 0.93-0.98, RC 22-48 msec).

DATA CONCLUSION

Kidney cortical T1 mapping is a highly repeatable and reproducible method across MRI manufacturers, field strengths, and observer conditions.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Potential MRI Biomarkers for Predicting Kidney Function and Histological Damage in Transplanted Deceased Donor Kidney Recipients

Background/Objectives: Kidney transplantation (kTx) is the preferred treatment for end-stage kidney disease. Limited evaluation of structural changes in transplanted kidneys hinders the timely prediction of disease progression and the implementation of treatment modifications. Protocol biopsies provide valuable insights but are invasive and carry risks of biopsy-related complications. This study investigates whether multiparametric magnetic resonance imaging (MRI), including T1 and T2 mapping and diffusion-weighted imaging (DWI), can predict kidney function and the progression of interstitial fibrosis and tubular atrophy (IF/TA) in the early post-transplant period. Methods: A prospective study was conducted at The Hospital of Lithuanian University of Health Sciences Kauno Klinikos from May 2022 to March 2024. Thirty-four patients receiving kidney transplants from deceased donors underwent baseline biopsies and post-transplant MRI scans. Follow-up assessments included kidney function evaluation, biopsies, and MRI scans at three months post-transplant. Results: Significant correlations were observed between MRI parameters and kidney function: T1 and apparent diffusion coefficient (ADC) corticomedullary differentiation (CMD) correlated with eGFR at discharge (r = -0.338, p = 0.05; r = 0.392, p = 0.022, respectively). Linear and logistic regression models demonstrated that post-transplant T1 and ADC CMD values significantly predicted kidney function at discharge. Furthermore, T1 CMD values measured 10-15 days post-transplant predicted IF/TA progression at three months post-kTx, with an area under the curve of 0.802 (95% CI: 0.616-0.987, p = 0.001) and an optimal cut-off value of -149.71 ms. The sensitivity and specificity were 0.818 and 0.273, respectively (Youden's index = 0.545). T2 mapping was not predictive. Conclusions: This study highlights the potential immediate clinical utility of MRI-derived biomarkers, particularly ADC and T1 CMD, in centers equipped with advanced imaging capabilities as tools for assessing kidney function in the early post-transplant period. With an AUROC of 0.802, T1 CMD demonstrates strong discriminatory power for predicting IF/TA progression early in the post-transplant period.

Concentric-object and equiangular-object methods to perform standardized regional analysis in renal mpMRI

OBJECTIVE

Renal multiparametric magnetic resonance imaging (mpMRI) sequences, including T1-T2 mapping, Blood oxygenation level-dependent (BOLD), Renal blood flow (RBF), and Apparent Diffusion Coefficient (ADC) from diffusion-weighted imaging (DWI), provide insights into kidney function. However, consensus on selecting regions of interest (ROIs) is lacking. This study aims to describe and compare the Concentric Objects (CO) and Equiangular Objects (EO) methods for standardized ROI selection and assess their efficacy in capturing regional variations in renal MRI parameters.

MATERIALS AND METHODS

Twelve healthy volunteers underwent mpMRI renal scans. ROIs were selected manually and by applying the CO and EO algorithms to each mpMRI sequence. The methods were tested across various subregion configurations. Regional differences in renal MRI parameters were evaluated.

RESULTS

CO and EO methods demonstrated statistically significant differences in mpMRI parameters across renal regions. ASL-RBF, BOLD-MRI, and T2-map results indicated substantial variations from the lower to upper kidney areas.

DISCUSSION

This study implemented CO and EO algorithms in renal mpMRI, showing their potential for evaluating cortico-medullary and cranio-caudal profiles. The findings validate the CO method for BOLD and ADC measurements and presented ASL-RBF and T1-T2 map profiles. The EO method's utility needs further validation with renal patients.

Multiparametric MRI: can we assess renal function differently?

We are lacking tools to evaluate renal performance. In this review, we presented the current knowledge and potential future applications in nephrology of new magnetic resonance imaging (MRI) techniques, focusing on diffusion-weighted (DWI) MRI, blood oxygen level-dependent (BOLD) MRI, and magnetic resonance relaxometry (T1 and T2 mapping). These sequences are sensitive to early changes in biological processes such as perfusion, oxygenation, edema, or fibrosis without requiring contrast medium injection and avoids irradiation and nephrotoxicity. Combining these different sequences into the so-called "multiparametric MRI" enables noninvasive, repeated exploration of renal performance on each kidney separately. DWI MRI, which evaluates the movement of water molecules, is a promising tool for noninvasive assessment of interstitial fibrosis and the cortical restricted diffusion has a prognostic value for the deterioration of renal function in diabetic nephropathy. BOLD MRI is sensitive to changes in renal tissue oxygenation based on the paramagnetic properties of deoxyhemoglobin and is of particular interest in the setting of renal artery stenosis to assess tissue oxygenation in the post-stenotic kidney. This sequence can be used for predicting degradation of renal function in chronic kidney diseases (CKD) and might be useful in preclinical studies to assess nephroprotective and nephrotoxic effects of drugs in development. T1 and T2 relaxation times change with tissue water content and might help assessing renal fibrosis. A corticomedullary dedifferentiation in T1 has been observed in CKD and negatively correlates with glomerular filtration rate. Data on the significance of T2 values in renal imaging is more limited. Multiparametric MRI has the potential to provide a better understanding of renal physiology and pathophysiology, a better characterization of renal lesions, an earlier and more sensitive detection of renal disease, and an aid to personalized patient-centered therapeutic decision-making. Further data and clinical trials are needed to allow its routine application in clinical practice.

An arterial spin labeling-based radiomics signature and machine learning for the prediction and detection of various stages of kidney damage due to diabetes

OBJECTIVE

The aim of this study was to assess the predictive capabilities of a radiomics signature obtained from arterial spin labeling (ASL) imaging in forecasting and detecting stages of kidney damage in patients with diabetes mellitus (DM), as well as to analyze the correlation between texture feature parameters and biological clinical indicators. Additionally, this study seeks to identify the imaging risk factors associated with early renal injury in diabetic patients, with the ultimate goal of offering novel insights for predicting and diagnosing early renal injury and its progression in patients with DM.

MATERIALS AND METHODS

In total, 42 healthy volunteers (Group A); 68 individuals with diabetes (Group B) who exhibited microalbuminuria, defined by a urinary albumin-to-creatinine ratio (ACR)< 30 mg/g and an estimated glomerular filtration rate (eGFR) within the range of 60-120 mL/min/1.73m²; and 53 patients with diabetic nephropathy (Group C) were included in the study. ASL using magnetic resonance imaging (MRI) at 3.0T was conducted. The radiologist manually delineated regions of interest (ROIs) on the ASL maps of both the right and left kidney cortex. Texture features from the ROIs were extracted utilizing MaZda software. Feature selection was performed utilizing a range of methods, such as the Fisher coefficient, mutual information (MI), probability of classification error, and average correlation coefficient (POE + ACC). A radiomics model was developed to detect early diabetic renal injury, extract imaging risk factors associated with early diabetic renal injury, and examine the relationship between significant texture feature parameters and biological clinical indicators. Patients with DM and kidney injury were followed prospectively. The study utilized seven machine learning algorithms to develop a detective radiomics model and a comprehensive predictive model for assessing the progression of kidney damage in patients with DM. The diagnostic efficacy of the models in detecting variations in diabetic kidney damage over time was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Empower (R) was used to establish a correlation between clinical biological indicators and texture feature metrics. Statistical analysis was conducted using R, Python, MedCalc 15.8, and GraphPad Prism 8.

RESULTS

A total of 367 texture features were extracted from the ROIs in the kidneys and refined based on selection criteria using MaZda software across groups A, B, and C. The renal blood flow (RBF) values of the renal cortex in groups A, B, and C exhibited a decreasing trend, with values of 256.458 ± 54.256 mL/100g/min, 213.846 ± 52.109 mL/100g/min, and 170.204 ± 34.992 mL/100g/min, respectively. There was a positive correlation between kidney RBF and eGFR (r = 0.439, P<0.001). The negative correlation between RBF and various clinical parameters including urinary albumin-to-creatinine ratio (UACR), body mass index (BMI), diastolic blood pressure (DBP), blood urea nitrogen (BUN), and serum creatinine (SCr) was investigated. Through the use of a least absolute shrinkage and selection operator (LASSO) regression model, the study identified the eight most significant texture features and biological indicators, namely GeoY, GeoRf, GeoRff, GeoRh, GeoW8, GeoW12, S (0, 4) Entropy, and S (5, -5) Entropy. Spearman correlation analysis revealed associations between imaging markers in early diabetic patients with kidney damage and factors such as age, systolic blood pressure (SBP), Alanine Transaminase (ALT), Aspartate Amino Transferase (AST) albumin, uric acid (UA), microalbuminuria (UMA), UACR, 24h urinary protein, fasting blood glucose (FBG), two hours postprandial blood glucose (P2BG), and HbA1c. The study utilized ASL imaging as a detection model to identify renal injury in patients with DM across different stages, achieving a sensitivity of 85.1%, specificity of 65.5%, and an AUC of 0.865. Additionally, a comprehensive prediction model combining imaging labels and biological indicators, with the naive Bayes machine learning algorithm as the best model, demonstrated an AUC of 0.734, accuracy of 0.74, and precision of 0.43.

CONCLUSION

ASL imaging sequences demonstrated the ability to accurately detect alterations in kidney function and blood flow in patients with DM. Strong associations were observed between renal blood flow values in ASL imaging and established clinical biomarkers. These values show promise in detecting early microstructural changes in the kidneys of diabetic patients. Utilizing image markers in conjunction with clinical indicators was effective in identifying early renal dysfunction and its progression in individuals with DM. Furthermore, the integration of imaging texture feature parameters with clinical biomarkers holds significant potential for predicting early renal damage and its progression in patients with diabetes.

Application of functional magnetic resonance imaging to evaluate renal structure and function in type 2 cardiorenal syndrome

BACKGROUND

There is a lack of diagnostic non-invasive imaging technology for assessing the early structural and functional changes of the kidney in type 2 cardiorenal (CRS) patients. This study aims to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for clinical application in type 2 CRS patients, to provide imaging markers for the assessment of kidney damage.

METHODS

This is a retrospective observational clinical study conducted in Nanjing, China. The clinical characteristics, including age, gender, medical history, laboratory results, and ultrasound and magnetic resonance imaging results were collected from the electronic medical record. Thirty-one patients with type 2 CRS, 20 patients with chronic heart failure (HF) and 20 healthy controls were enrolled and divided into type 2 CRS, HF and control groups. All the participants underwent magnetic resonance imaging (MRI) scanning. The apparent diffusion coefficient (ADC) value and IVIM-DWI parameters including true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were obtained. The correlation between estimated glomerular filtration rate (eGFR), renal size and imaging parameters was evaluated by Spearman correlation analysis.

RESULTS

ADC and D of the renal cortex in patients with type 2 CRS were lower than those in the healthy control group. ADC and f in the HF group were lower than those in the control group. D was positively correlated with the length (r = 0.3752, P = 0.0013) and transverse diameter (r = 0.3258, P = 0.0056) of the kidney. ADC (r = 0.2964, P = 0.0121) and D (r = 0.3051, P = 0.0097) were positively correlated with eGFR. Renal cortical ADC and D values could distinguish type 2 CRS patients from the healthy controls with area under the curve (AUC) of 0.723 and 0.706, respectively.

CONCLUSION

The ADC and D values were not only correlated with renal function, but also had lower levels in type 2 CRS. The IVIM-DWI parameter D was also related to kidney size, but further research is needed to determine whether it can be used as a novel imaging marker for type 2 CRS.

Diagnostic and Prognostic Potential of Multiparametric Renal MRI in Kidney Transplant Patients

BACKGROUND

Multiparametric MRI provides assessment of functional and structural parameters in kidney allografts. It offers a non-invasive alternative to the current reference standard of kidney biopsy.

PURPOSE

To evaluate the diagnostic and prognostic utility of MRI parameters in the assessment of allograft function in the first 3-months post-transplantation.

STUDY TYPE

Prospective.

SUBJECTS

32 transplant recipients (54 ± 17 years, 20 females), divided into two groups according to estimated glomerular filtration rate (eGFR) at 3-months post-transplantation: inferior graft function (IGF; eGFR<45 mL/min/1.73 m2, n = 10) and superior graft function (SGF; eGFR ≥ 45 mL/min/1.73 m2, n = 22). Further categorization was based on the need for hemodialysis (C1) and decrease in s-creatinine (C2) at 1-week post-transplantation: delayed-graft-function (DGF: n = 4 C1, n = 10 C2) and early graft-function (EGF: n = 28 C1, n = 22 C2).

FIELD STRENGTH/SEQUENCE

3-T, pseudo-continuous arterial spin labeling, T1-mapping, and diffusion-weighted imaging.

ASSESSMENT

Multiparametric MRI was evaluated at 1-week in all patients and 3-months after transplantation in 28 patients. Renal blood flow (RBF), diffusion coefficients (ADC, ΔADC, D, ∆ D, D*, flowing fraction f), T1 and ∆ T1 were calculated in cortex and medulla. The diagnostic and prognostic value of these parameters, obtained at 3-months and 1-week post-transplantation, respectively, was evaluated in the cortex to discriminate between DGF and EGF, and between SGF and IGF.

STATISTICAL TESTS

Logistic regression, receiver-operating-characteristics, area-under-the-curve (AUC), confidence intervals (CIs), analysis-of-variance, t-test, Wilcoxon-Mann-Whitney test, Fisher's exact test, Pearson's correlation. P-value<0.05 was considered significant.

RESULTS

DGF patients exhibited significantly lower cortical RBF and f and higher D*. The diagnostic value of MRI for detecting DGF was excellent (AUC = 100%). Significant differences between patients with IGF and SGF were found in RBF, ∆T1, and ∆D. Multiparametric MRI showed higher diagnostic (AUC = 95.32%; CI: 88%-100%) and prognostic (AUC = 97.47%, CI: 92%-100%) values for detecting IGF than eGFR (AUC = 89.50%, CI: 79%-100%).

DATA CONCLUSION

Multiparametric MRI may show high diagnostic and prognostic value in transplanted patients, yielding better results compared to eGFR measurements.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

The impact of population ageing on the burden of chronic kidney disease

The burden of chronic kidney disease (CKD) and its risk factors are projected to rise in parallel with the rapidly ageing global population. By 2050, the prevalence of CKD category G3-G5 may exceed 10% in some regions, resulting in substantial health and economic burdens that will disproportionately affect lower-income countries. The extent to which the CKD epidemic can be mitigated depends largely on the uptake of prevention efforts to address modifiable risk factors, the implementation of cost-effective screening programmes for early detection of CKD in high-risk individuals and widespread access and affordability of new-generation kidney-protective drugs to prevent the development and delay the progression of CKD. Older patients require a multidisciplinary integrated approach to manage their multimorbidity, polypharmacy, high rates of adverse outcomes, mental health, fatigue and other age-related symptoms. In those who progress to kidney failure, comprehensive conservative management should be offered as a viable option during the shared decision-making process to collaboratively determine a treatment approach that respects the values and wishes of the patient. Interventions that maintain or improve quality of life, including pain management and palliative care services when appropriate, should also be made available.

Quantification of Multi-Compartment Flow with Spectral Diffusion MRI

Purpose

Estimation of multi-compartment intravoxel 'flow' in fD in ml/100g/min with multi-b-value diffusion weighted imaging and a multi-Gaussian model in the kidneys.

Theory and Methods

A multi-Gaussian model of intravoxel flow using water transport time to quantify f D (ml/100g/min) is presented and simulated. Multi-compartment anisotropic DWI signal is simulated with Rician noise and SNR=50 and analyzed with a rigid bi-exponential, a rigid tri-exponential and diffusion spectrum imaging model of intravoxel incoherent motion (spectral diffusion) to study extraction of multi-compartment flow. The regularization parameter for spectral diffusion is varied to study the impact on the resulting spectrum and computation speed. The application is demonstrated in a two-center study of 54 kidney allografts with 9 b-value advanced DWI that were split by function (CKD-EPI 2021 eGFR<45ml/min/1.73m2) and fibrosis (Banff 2017 interstitial fibrosis and tubular atrophy score 0-6) to demonstrate multi-compartment flow of various kidney pathologies.

Results

Simulation of anisotropic multi-compartment flow from spectral diffusion demonstrated strong correlation to truth for both three-compartment anisotropic diffusion ( y = 1.08 x + 0.1 , R 2 = 0.71 ) and two-compartment anisotropic diffusion ( y = 0.91 + 0.6 , R 2 = 0.74 ), outperforming rigid models in cases of variable compartment number. Use of a fixed regularization parameter set to λ = 0.1 increased computation up to 208-fold and agreed with voxel-wise cross-validated regularization (concordance correlation coefficient=0.99). Spectral diffusion of renal allografts showed decreasing trend of tubular and vascular flow with higher levels of fibrosis, and significant increase in tissue parenchyma flow (f-stat=3.86, p=0.02). Tubular f D was significantly decreased in allografts with impaired function (eGFR<45ml/min/1.73m2)(Mann-Whitney U t-stat=-2.14, p=0.04).

Conclusions

Quantitative multi-compartment intravoxel 'flow' can be estimated in ml/100g/min with f D from multi-Gaussian diffusion with water transport time, even with moderate anisotropy such as in kidneys. The use of spectral diffusion with a multi-Gaussian model and a fixed regularization parameter is particularly promising in organs such as the kidney with variable numbers of physiologic compartments.

Quantitative non-contrast perfusion MRI in the body using arterial spin labeling

Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging (MRI) method that enables the assessment and the quantification of perfusion without the need for an exogenous contrast agent. ASL was originally developed in the early 1990s to measure cerebral blood flow. The utility of ASL has since then broadened to encompass various organ systems, offering insights into physiological and pathological states. In this review article, we present a synopsis of ASL for quantitative non-contrast perfusion MRI, as a contribution to the special issue titled "Quantitative MRI-how to make it work in the body?" The article begins with an introduction to ASL principles, followed by different labeling strategies, such as pulsed, continuous, pseudo-continuous, and velocity-selective approaches, and their role in perfusion quantification. We proceed to address the technical challenges associated with ASL in the body and outline some of the innovative approaches devised to surmount these issues. Subsequently, we summarize potential clinical applications, challenges, and state-of-the-art ASL methods to quantify perfusion in some of the highly perfused organs in the thorax (lungs), abdomen (kidneys, liver, pancreas), and pelvis (placenta) of the human body. The article concludes by discussing future directions for successful translation of quantitative ASL in body imaging.

MRI of kidney size matters

OBJECTIVE

To highlight progress and opportunities of measuring kidney size with MRI, and to inspire research into resolving the remaining methodological gaps and unanswered questions relating to kidney size assessment.

MATERIALS AND METHODS

This work is not a comprehensive review of the literature but highlights valuable recent developments of MRI of kidney size.

RESULTS

The links between renal (patho)physiology and kidney size are outlined. Common methodological approaches for MRI of kidney size are reviewed. Techniques tailored for renal segmentation and quantification of kidney size are discussed. Frontier applications of kidney size monitoring in preclinical models and human studies are reviewed. Future directions of MRI of kidney size are explored.

CONCLUSION

MRI of kidney size matters. It will facilitate a growing range of (pre)clinical applications, and provide a springboard for new insights into renal (patho)physiology. As kidney size can be easily obtained from already established renal MRI protocols without the need for additional scans, this measurement should always accompany diagnostic MRI exams. Reconciling global kidney size changes with alterations in the size of specific renal layers is an important topic for further research. Acute kidney size measurements alone cannot distinguish between changes induced by alterations in the blood or the tubular volume fractions-this distinction requires further research into cartography of the renal blood and the tubular volumes.

Diffusion tensor MRI is sensitive to fibrotic injury in a mouse model of oxalate-induced chronic kidney disease

Chronic kidney disease (CKD) is characterized by inflammation and fibrosis in the kidney. Renal biopsies and estimated glomerular filtration rate (eGFR) remain the standard of care, but these endpoints have limitations in detecting the stage, progression, and spatial distribution of fibrotic pathology in the kidney. MRI diffusion tensor imaging (DTI) has emerged as a promising noninvasive technology to evaluate renal fibrosis in vivo both in clinical and preclinical studies. However, these imaging studies have not systematically identified fibrosis particularly deeper in the kidney where biopsy sampling is limited, or completed an extensive analysis of whole organ histology, blood biomarkers, and gene expression to evaluate the relative strengths and weaknesses of MRI for evaluating renal fibrosis. In this study, we performed DTI in the sodium oxalate mouse model of CKD. The DTI parameters fractional anisotropy, apparent diffusion coefficient, and axial diffusivity were compared between the control and oxalate groups with region of interest (ROI) analysis to determine changes in the cortex and medulla. In addition, voxel-based analysis (VBA) was implemented to systematically identify local regions of injury over the whole kidney. DTI parameters were found to be significantly different in the medulla by both ROI analysis and VBA, which also spatially matched with collagen III immunohistochemistry (IHC). The DTI parameters in this medullary region exhibited moderate to strong correlations with histology, blood biomarkers, hydroxyproline, and gene expression. Our results thus highlight the sensitivity of DTI to the heterogeneity of renal fibrosis and importance of whole kidney noninvasive imaging.NEW & NOTEWORTHY Chronic kidney disease (CKD) can be characterized by inflammation and fibrosis of the kidney. Although standard of care methods have been limited in scope, safety, and spatial distribution, MRI diffusion tensor imaging (DTI) has emerged as a promising noninvasive technology to evaluate renal fibrosis in vivo. In this study, we performed DTI in an oxalate mouse model of CKD to systematically identify local kidney injury. DTI parameters strongly correlated with histology, blood biomarkers, hydroxyproline, and gene expression.

Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI

A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73 m2, CKD stage G4-5); 172 with moderate renal dysfunction (30 ≤ eGFR < 60 mL/min/1.73 m2, CKD stage G3a/b); and 76 with mild renal dysfunction (eGFR ≥ 60 mL/min/1.73 m2, CKD stage G1-2) participated in this study. The model was applied to the right, left, and both kidneys, as well as to each imaging method (T1-weighted IP/OP/WO images). The best performance was obtained when using bilateral kidneys and IP images, with an accuracy of 0.862 ± 0.036. The overall accuracy was better for the bilateral kidney models than for the unilateral kidney models. Our deep learning approach using kidney MRI can be applied to classify patients with CKD based on the severity of kidney disease.

Assessment of pharmacologically induced changes in canine kidney function by multiparametric magnetic resonance imaging and contrast enhanced ultrasound

Introduction

Dynamic contrast-enhanced (DCE) MRI and arterial spin labeling (ASL) MRI enable non-invasive measurement of renal blood flow (RBF), whereas blood oxygenation level-dependent (BOLD) MRI enables non-invasive measurement of the apparent relaxation rate (R2*), an indicator of oxygenation. This study was conducted to evaluate the potential role of these MRI modalities in assessing RBF and oxygenation in dogs. The correlation between contrast-enhanced ultrasound (CEUS) and the MRI modalities was examined and also the ability of the MRI modalities to detect pharmacologically induced changes.

Methods

RBF, using CEUS, ASL- and DCE-MRI, as well as renal oxygenation, using BOLD-MRI of eight adult beagles were assessed at two time-points, 2–3 weeks apart. During each time point, the anesthetized dogs received either a control (0.9% sodium chloride) or a dopamine treatment. For each time point, measurements were carried out over 2 days. An MRI scan at 3 T was performed on day one, followed by CEUS on day two.

Results

Using the model-free model with caudal placement of the arterial input function (AIF) region of interest (ROI) in the aorta, the DCE results showed a significant correlation with ASL measured RBF and detected significant changes in blood flow during dopamine infusion. Additionally, R2* negatively correlated with ASL measured RBF at the cortex and medulla, as well as with medullary wash-in rate (WiR) and peak intensity (PI). ASL measured RBF, in its turn, showed a positive correlation with cortical WiR, PI, area under the curve (AUC) and fall time (FT), and with medullary WiR and PI, but a negative correlation with medullary rise time (RT). During dopamine infusion, BOLD-MRI observed a significant decrease in R2* at the medulla and entire kidney, while ASL-MRI demonstrated a significant increase in RBF at the cortex, medulla and the entire kidney.

Conclusion

ASL- and BOLD-MRI can measure pharmacologically induced changes in renal blood flow and renal oxygenation in dogs and might allow detection of changes that cannot be observed with CEUS. However, further research is needed to confirm the potential of ASL- and BOLD-MRI in dogs and to clarify which analysis method is most suitable for DCE-MRI in dogs.

Noninvasive Assessment of Diabetic Kidney Disease With MRI: Hype or Hope?

Owing to the increasing prevalence of diabetic mellitus, diabetic kidney disease (DKD) is presently the leading cause of chronic kidney disease and end-stage renal disease worldwide. Early identification and disease interception is of paramount clinical importance for DKD management. However, current diagnostic, disease monitoring and prognostic tools are not satisfactory, due to their low sensitivity, low specificity, or invasiveness. Magnetic resonance imaging (MRI) is noninvasive and offers a host of contrast mechanisms that are sensitive to pathophysiological changes and risk factors associated with DKD. MRI tissue characterization involves structural and functional information including renal morphology (kidney volume (TKV) and parenchyma thickness using T1- or T2-weighted MRI), renal microstructure (diffusion weighted imaging, DWI), renal tissue oxygenation (blood oxygenation level dependent MRI, BOLD), renal hemodynamics (arterial spin labeling and phase contrast MRI), fibrosis (DWI) and abdominal or perirenal fat fraction (Dixon MRI). Recent (pre)clinical studies demonstrated the feasibility and potential value of DKD evaluation with MRI. Recognizing this opportunity, this review outlines key concepts and current trends in renal MRI technology for furthering our understanding of the mechanisms underlying DKD and for supplementing clinical decision-making in DKD. Progress in preclinical MRI of DKD is surveyed, and challenges for clinical translation of renal MRI are discussed. Future directions of DKD assessment and renal tissue characterization with (multi)parametric MRI are explored. Opportunities for discovery and clinical break-through are discussed including biological validation of the MRI findings, large-scale population studies, standardization of DKD protocols, the synergistic connection with data science to advance comprehensive texture analysis, and the development of smart and automatic data analysis and data visualization tools to further the concepts of virtual biopsy and personalized DKD precision medicine. We hope that this review will convey this vision and inspire the reader to become pioneers in noninvasive assessment and management of DKD with MRI. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

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.

From inflammation to renal fibrosis: A one-way road in autoimmunity?

Renal fibrosis is now recognized as a main determinant of renal pathology to include chronic kidney disease. Deposition of pathological matrix in the walls of glomerular capillaries, the interstitial space, and around arterioles predicts and contributes to the functional demise of the nephron and its surrounding vasculature. The recent identification of the major cell populations of fibroblast precursors in the kidney interstitium such as pericytes and tissue-resident mesenchymal stem cells, or bone-marrow-derived macrophages, and in the glomerulus such as podocytes, parietal epithelial and mesangial cells, has enabled the study of the fibrogenic process thought the lens of involved immunological pathways. Besides, a growing body of evidence is supporting the role of the lymphatic system in modulating the immunological response potentially leading to inflammation and ultimately renal damage. These notions have moved our understanding of renal fibrosis to be recognized as a clinical entity and new main player in autoimmunity, impacting directly the management of patients.

Multimodality Imaging in Metabolic Syndrome: State-of-the-Art Review

Metabolic syndrome comprises a set of risk factors that include abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, low high-density lipoprotein levels, and high blood pressure, at least three of which must be fulfilled for diagnosis. Metabolic syndrome has been linked to an increased risk of cardiovascular disease and type 2 diabetes mellitus. Multimodality imaging plays an important role in metabolic syndrome, including diagnosis, risk stratification, and assessment of complications. CT and MRI are the primary tools for quantification of excess fat, including subcutaneous and visceral adipose tissue, as well as fat around organs, which are associated with increased cardiovascular risk. PET has been shown to detect signs of insulin resistance and may detect ectopic sites of brown fat. Cardiovascular disease is an important complication of metabolic syndrome, resulting in subclinical or symptomatic coronary artery disease, alterations in cardiac structure and function with potential progression to heart failure, and systemic vascular disease. CT angiography provides comprehensive evaluation of the coronary and systemic arteries, while cardiac MRI assesses cardiac structure, function, myocardial ischemia, and infarction. Liver damage results from a spectrum of nonalcoholic fatty liver disease ranging from steatosis to fibrosis and possible cirrhosis. US, CT, and MRI are useful in assessing steatosis and can be performed to detect and grade hepatic fibrosis, particularly using elastography techniques. Metabolic syndrome also has deleterious effects on the pancreas, kidney, gastrointestinal tract, and ovaries, including increased risk for several malignancies. Metabolic syndrome is associated with cerebral infarcts, best evaluated with MRI, and has been linked with cognitive decline. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Pickhardt in this issue.

Magnetic resonance elastography resolving all gross anatomical segments of the kidney during controlled hydration

Introduction: Magnetic resonance elastography (MRE) is a non-invasive method to quantify biomechanical properties of human tissues. It has potential in diagnosis and monitoring of kidney disease, if established in clinical practice. The interplay of flow and volume changes in renal vessels, tubule, urinary collection system and interstitium is complex, but physiological ranges of in vivo viscoelastic properties during fasting and hydration have never been investigated in all gross anatomical segments simultaneously. Method: Ten healthy volunteers underwent two imaging sessions, one following a 12-hour fasting period and the second after a drinking challenge of >10 mL per kg body weight (60-75 min before the second examination). High-resolution renal MRE was performed using a novel driver with rotating eccentric mass placed at the posterior-lateral wall to couple waves (50 Hz) to the kidney. The biomechanical parameters, shear wave speed (cs in m/s), storage modulus (Gd in kPa), loss modulus (Gl in kPa), phase angle ( Υ = 2 π atan G l G d ) and attenuation (α in 1/mm) were derived. Accurate separation of gross anatomical segments was applied in post-processing (whole kidney, cortex, medulla, sinus, vessel). Results: High-quality shear waves coupled into all gross anatomical segments of the kidney (mean shear wave displacement: 163 ± 47 μm, mean contamination of second upper harmonics <23%, curl/divergence: 4.3 ± 0.8). Regardless of the hydration state, median Gd of the cortex and medulla (0.68 ± 0.11 kPa) was significantly higher than that of the sinus and vessels (0.48 ± 0.06 kPa), and consistently, significant differences were found in cs, Υ , and Gl (all p < 0.001). The viscoelastic parameters of cortex and medulla were not significantly different. After hydration sinus exhibited a small but significant reduction in median Gd by -0.02 ± 0.04 kPa (p = 0.01), and, consequently, the cortico-sinusoidal-difference in Gd increased by 0.04 ± 0.07 kPa (p = 0.05). Only upon hydration, the attenuation in vessels became lower (0.084 ± 0.013 1/mm) and differed significantly from the whole kidney (0.095 ± 0.007 1/mm, p = 0.01). Conclusion: High-resolution renal MRE with an innovative driver and well-defined 3D segmentation can resolve all renal segments, especially when including the sinus in the analysis. Even after a prolonged hydration period the approach is sensitive to small hydration-related changes in the sinus and in the cortico-sinusoidal-difference.

Should we enlarge the indication for kidney biopsy in diabetics? The con part

Diabetes is the most common cause of chronic kidney disease (CKD), a condition found in 850 million persons and projected to become the fifth global cause of death by 2040. Research is needed that examines kidney tissue to characterize distinct phenotypes in patients with diabetes mellitus (DM) and CKD so as to identify non-invasive biomarker signatures and develop targeted therapeutic approaches. However, from a routine care point of view, kidney biopsy is likely overused in patients with CKD and DM, as most biopsy results are not expected to be associated with a therapeutic approach that differs from standard kidney protection with triple or quadruple therapy (renin-angiotensin system blockade, sodium-glucose cotransporter 2 inhibitors, nonsteroidal mineralocorticoid receptor antagonists and glucagon-like peptide-1 receptor agonists). Moreover, expanding the kidney biopsy criteria will increase the absolute number of complications from kidney biopsies, which may reach 27 000 to 108 000 deaths of persons that would derive little benefit from kidney biopsy if all people with DM and severe CKD were biopsied globally. Finally, limited resources should be optimally allocated. The cost of one kidney biopsy can fund 7000 semiquantitative urinary albumin:creatinine ratio assessments that could identify earlier stages of the disease and allow treatment that prevents progression to a stage at which kidney biopsy may be considered.

Renal MRI: From Nephron to NMR Signal

Renal diseases pose a significant socio-economic burden on healthcare systems. The development of better diagnostics and prognostics is well-recognized as a key strategy to resolve these challenges. Central to these developments are MRI biomarkers, due to their potential for monitoring of early pathophysiological changes, renal disease progression or treatment effects. The surge in renal MRI involves major cross-domain initiatives, large clinical studies, and educational programs. In parallel with these translational efforts, the need for greater (patho)physiological specificity remains, to enable engagement with clinical nephrologists and increase the associated health impact. The ISMRM 2022 Member Initiated Symposium (MIS) on renal MRI spotlighted this issue with the goal of inspiring more solutions from the ISMRM community. This work is a summary of the MIS presentations devoted to: 1) educating imaging scientists and clinicians on renal (patho)physiology and demands from clinical nephrologists, 2) elucidating the connection of MRI parameters with renal physiology, 3) presenting the current state of leading MR surrogates in assessing renal structure and functions as well as their next generation of innovation, and 4) describing the potential of these imaging markers for providing clinically meaningful renal characterization to guide or supplement clinical decision making. We hope to continue momentum of recent years and introduce new entrants to the development process, connecting (patho)physiology with (bio)physics, and conceiving new clinical applications. We envision this process to benefit from cross-disciplinary collaboration and analogous efforts in other body organs, but also to maximally leverage the unique opportunities of renal physiology. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Functional Magnetic Resonance Imaging to Monitor Disease Progression: A Prospective Study in Patients with Primary Membranoproliferative Glomerulonephritis

INTRODUCTION

Primary membranoproliferative glomerulonephritis (MPGN) is a rare kidney disease with poor prognosis and no specific therapies. The disease heterogeneity and the difficulty of performing repeated kidney biopsies pose big challenges. This study investigates the correlation between non-contrast enhanced magnetic resonance imaging (MRI) and histologic and clinical findings in patients with primary MPGN.

METHODS

Patients with primary MPGN underwent baseline and 1-year kidney MRI in addition to biopsy and laboratory testing as part of a prospective MRI subproject of a clinical trial (ClinicalTrials.gov identifier NCT03723512). Diffusion-weighted and phase-contrast MRI were used to investigate kidney diffusivity and perfusion. Peritubular interstitial volume and fibrosis were quantified on kidney biopsies.

RESULTS

Seven patients with primary MPGN (18[17-21] years, 43% females) were included. Kidney biopsies showed variable degree of global and segmental glomerular sclerosis ([5-30]% and [10-60]%), mild interstitial fibrosis (<10%), and increased peritubular interstitial volume ([19-40]%). MRI and laboratory parameters changed very differently from patient to patient over 1 year. Peritubular interstitial volume and glomerular sclerosis negatively associated with renal blood flow (RBF) (rho = -0.81 and -0.77), and positively with renal vascular resistance (RVR) (rho = 0.65 and 0.73). Urinary albumin to creatinine ratio (uACR) negatively associated with RBF and filtration fraction (FF) (rho = -0.86 and -0.6), while positively with RVR (rho = 0.88). uACR decrease was associated with kidney diffusivity increase (rho = -0.5). Measured glomerular filtration rate (GFR) positively associated with kidney diffusivity, RBF, and FF (rho = 0.87, 0.85, and 0.59), while negatively with RVR (rho = -0.89); GFR increase was associated with kidney diffusivity, RBF, and FF increase (rho = 0.77, 0.7, and 0.7) and RVR decrease (rho = -0.7).

CONCLUSION

The strong correlation found between MRI and histologic and clinical findings, despite the rather limited number of patients, highlights MRI potential to monitor disease progression in patients with rare kidney disease.

Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer

We explored the added value of a radiomic strategy based on quantitative transverse relaxation (T2) mapping and conventional magnetic resonance imaging (MRI) to evaluate the histologic grade of bladder cancer (BCa) preoperatively. Patients who were suspected of BCa underwent pelvic MRI (including T2 mapping and diffusion-weighted imaging (DWI) before any treatment. All patients with histological-proved urothelial BCa were included. We constructed different prediction models using the mean signal values and radiomic features from both T2 mapping and apparent diffusion coefficient (ADC) maps. The diagnostic performance of each model or parameter was assessed using receiver operating characteristic curves. In total, 92 patients were finally included (training cohort, n = 64; testing cohort, n = 28); among these, 71 had high-grade BCa. In the testing cohort, the T2-mapping radiomic model achieved the highest prediction performance (area under the curve (AUC), 0.87; 95% confidence interval (CI), 0.73-1.0) compared with the ADC radiomic model (AUC, 0.77; 95%CI, 0.56-0.97), and the joint radiomic model of 0.78 (95%CI, 0.61-0.96). Our results demonstrated that radiomic mapping could provide more information than direct evaluation of T2 and ADC values in differentiating histological grades of BCa. Additionally, among the radiomic models, the T2-mapping radiomic model outperformed the ADC and joint radiomic models.

Diffusion magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterisation in ADPKD

OBJECTIVES

Beyond total kidney and cyst volume (TCV), non-cystic tissue plays an important role in autosomal dominant polycystic kidney disease (ADPKD) progression. This study aims at presenting and preliminarily validating a diffusion MRI (DWI)-based TCV quantification method and providing evidence of DWI potential in characterising non-cystic tissue microstructure.

METHODS

T2-weighted MRI and DWI scans (b = 0, 15, 50, 100, 200, 350, 500, 700, 1000; 3 directions) were acquired from 35 ADPKD patients with CKD stage 1 to 3a and 15 healthy volunteers on a 1.5 T scanner. ADPKD classification was performed using the Mayo model. DWI scans were processed by mono- and segmented bi-exponential models. TCV was quantified on T2-weighted MRI by the reference semi-automatic method and automatically computed by thresholding the pure diffusivity (D) histogram. The agreement between reference and DWI-based TCV values and the differences in DWI-based parameters between healthy and ADPKD tissue components were assessed.

RESULTS

There was strong correlation between DWI-based and reference TCV (rho = 0.994, p < 0.001). Non-cystic ADPKD tissue had significantly higher D, and lower pseudo-diffusion and flowing fraction than healthy tissue (p < 0.001). Moreover, apparent diffusion coefficient and D values significantly differed by Mayo imaging class, both in the whole kidney (Wilcoxon p = 0.007 and p = 0.004) and non-cystic tissue (p = 0.024 and p = 0.007).

CONCLUSIONS

DWI shows potential in ADPKD to quantify TCV and characterise non-cystic kidney tissue microstructure, indicating the presence of microcysts and peritubular interstitial fibrosis. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion.

CLINICAL RELEVANCE STATEMENT

This study shows diffusion-weighted MRI (DWI) potential to quantify total cyst volume and characterise non-cystic kidney tissue microstructure in ADPKD. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion.

KEY POINTS

• Diffusion magnetic resonance imaging shows potential to quantify total cyst volume in ADPKD. • Diffusion magnetic resonance imaging might allow to non-invasively characterise non-cystic kidney tissue microstructure. • Diffusion magnetic resonance imaging-based biomarkers significantly differ by Mayo imaging class, suggesting their possible prognostic value.

Renal Perfusion, Oxygenation and Metabolism: The Role of Imaging

Thanks to technical advances in the field of medical imaging, it is now possible to study key features of renal anatomy and physiology, but so far poorly explored due to the inherent difficulties in studying both the metabolism and vasculature of the human kidney. In this narrative review, we provide an overview of recent research findings on renal perfusion, oxygenation, and substrate uptake. Most studies evaluating renal perfusion with positron emission tomography (PET) have been performed in healthy controls, and specific target populations like obese individuals or patients with renovascular disease and chronic kidney disease (CKD) have rarely been assessed. Functional magnetic resonance (fMRI) has also been used to study renal perfusion in CKD patients, and recent studies have addressed the kidney hemodynamic effects of therapeutic agents such as glucagon-like receptor agonists (GLP-1RA) and sodium-glucose co-transporter 2 inhibitors (SGLT2-i) in an attempt to characterise the mechanisms leading to their nephroprotective effects. The few available studies on renal substrate uptake are discussed. In the near future, these imaging modalities will hopefully become widely available with researchers more acquainted with them, gaining insights into the complex renal pathophysiology in acute and chronic diseases.

Abdominal Imaging in ADPKD: Beyond Total Kidney Volume

In the context of autosomal dominant polycystic kidney disease (ADPKD), measurement of the total kidney volume (TKV) is crucial. It acts as a marker for tracking disease progression, and evaluating the effectiveness of treatment strategies. The TKV has also been recognized as an enrichment biomarker and a possible surrogate endpoint in clinical trials. Several imaging modalities and methods are available to calculate the TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess the cyst burden, which can be crucial to assessing the disease state and helping to identify rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond these measurements, the quantification and characterization of non-cystic kidney tissue shows potential for stratifying ADPKD patients early on, monitoring disease progression, and possibly predicting renal function loss. A broad spectrum of radiological imaging techniques are available to characterize the kidney tissue, showing promise when it comes to non-invasively picking up the early signs of ADPKD progression. Radiomics have been used to extract textural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging biomarkers, focusing on the quantification methods, potential, and necessary steps toward a successful translation to clinical practice.

Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis

OBJECTIVES

To identify optimized MRI markers for evaluating chronic kidney disease (CKD) and renal interstitial fibrosis (IF).

MATERIALS AND METHODS

This prospective study included 43 patients with CKD and 20 controls. The CKD group was divided into mild and moderate-to-severe subgroups based on pathological results. Scanned sequences included T1 mapping, R2* mapping, intravoxel incoherent motion imaging, and diffusion-weighted imaging. One-way analyses of variance were used to compare MRI parameters among groups. Correlations of MRI parameters with estimated glomerular filtration rate (eGFR) and renal IF were analyzed using age as covariates. The support vector machine (SVM) model was used to evaluate the diagnostic efficacy of multiparametric MRI.

RESULTS

Compared to control values, renal cortical apparent diffusion coefficient (cADC), medullary ADC (mADC), cortical pure diffusion coefficient (cDt), medullary Dt (mDt), cortical shifted apparent diffusion coefficient (csADC), and medullary sADC (msADC) values gradually decreased in the mild and moderate-to-severe groups, while cortical T1 (cT1) and medullary T1 (mT1) values gradually increased. Values of cADC, mADC, cDt, mDt, cT1, mT1, csADC, and msADC were significantly associated with eGFR and IF (p < 0.001). The SVM model indicated that multiparametric MRI combining cT1 and csADC can distinguish patients with CKD from controls with high accuracy (0.84), sensitivity (0.70), and specificity (0.92) (AUC: 0.96). Multiparametric MRI combining cT1 and cADC exhibited high accuracy (0.91), sensitivity (0.95), and specificity (0.81) for evaluating IF severity (AUC: 0.96).

CONCLUSION

Multiparametric MRI combining T1 mapping and diffusion imaging may be of clinical utility in non-invasive assessment of CKD and IF.

CLINICAL RELEVANCE STATEMENT

This study shows that multiparametric MRI combining T1 mapping and diffusion imaging may be clinically useful in the non-invasive assessment of chronic kidney disease (CKD) and interstitial fibrosis; this could provide information for risk stratification, diagnosis, treatment, and prognosis.

KEY POINTS

• Optimized MRI markers for evaluating chronic kidney disease and renal interstitial fibrosis were investigated. • Renal cortex/medullary T1 values increased as interstitial fibrosis increased; cortical shifted apparent diffusion coefficient (csADC) correlated significantly with eGFR and interstitial fibrosis. • Support vector machine (SVM) combining cortical T1 (cT1) and csADC/cADC effectively identifies chronic kidney disease and accurately predicts renal interstitial fibrosis.

Magnetic Resonance Imaging in Clinical Trials of Diabetic Kidney Disease

Chronic kidney disease (CKD) associated with diabetes mellitus (DM) (known as diabetic kidney disease, DKD) is a serious and growing healthcare problem worldwide. In DM patients, DKD is generally diagnosed based on the presence of albuminuria and a reduced glomerular filtration rate. Diagnosis rarely includes an invasive kidney biopsy, although DKD has some characteristic histological features, and kidney fibrosis and nephron loss cause disease progression that eventually ends in kidney failure. Alternative sensitive and reliable non-invasive biomarkers are needed for DKD (and CKD in general) to improve timely diagnosis and aid disease monitoring without the need for a kidney biopsy. Such biomarkers may also serve as endpoints in clinical trials of new treatments. Non-invasive magnetic resonance imaging (MRI), particularly multiparametric MRI, may achieve these goals. In this article, we review emerging data on MRI techniques and their scientific, clinical, and economic value in DKD/CKD for diagnosis, assessment of disease pathogenesis and progression, and as potential biomarkers for clinical trial use that may also increase our understanding of the efficacy and mode(s) of action of potential DKD therapeutic interventions. We also consider how multi-site MRI studies are conducted and the challenges that should be addressed to increase wider application of MRI in DKD.

The value of functional magnetic resonance imaging in the evaluation of diabetic kidney disease: a systematic review and meta-analysis

Background

The diversity of clinical trajectories in diabetic kidney disease (DKD) has made blood and biochemical urine markers less precise, while renal puncture, the gold standard, is almost impossible in the assessment of diabetic kidney disease, and the value of functional magnetic resonance imaging in the evaluation of diabetic pathological alterations is increasingly recognized.

Methods

The literature on functional magnetic resonance imaging (fMRI) for the assessment of renal alterations in diabetic kidney disease was searched in PubMed, Web of Science, Cochrane Library, and Embase databases. The search time limit is from database creation to March 10, 2023. RevMan was used to perform a meta-analysis of the main parameters of fMRIs extracted from DKD patients and healthy volunteers (HV).

Results

24 publications (1550 subjects) were included in this study, using five functional MRIs with seven different parameters. The renal blood flow (RBF) values on Arterial spin labeling magnetic resonance imaging (ASL-MRI) was significantly lower in the DKD group than in the HV group. The [WMD=-99.03, 95% CI (-135.8,-62.27), P<0.00001]; Diffusion tensor imaging magnetic resonance imaging (DTI-MRI) showed that the fractional anisotropy (FA) values in the DKD group were significantly lower than that in HV group [WMD=-0.02, 95%CI (-0.03,-0.01), P<0.0001]. And there were no statistically significant differences in the relevant parameters in Blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) or Intro-voxel incoherent movement magnetic resonance imaging (IVIM-DWI).

Discussion

ASL and DWI can identify the differences between DKD and HV. DTI has a significant advantage in assessing renal cortical changes; IVIM has some value in determining early diabetic kidney disease from the cortex or medulla. We recommend combining multiple fMRI parameters to assess structural or functional changes in the kidney to make the assessment more comprehensive. We did not observe a significant risk of bias in the present study.

Systematic review registration

https://www.crd.york.ac.uk, identifier CRD42023409249.

Cardiac Phase and Flow Compensation Effects on REnal Flow and Microstructure AnisotroPy MRI in Healthy Human Kidney

BACKGROUND

Renal diffusion-weighted imaging (DWI) involves microstructure and microcirculation, quantified with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and hybrid models. A better understanding of their contrast may increase specificity.

PURPOSE

To measure modulation of DWI with cardiac phase and flow-compensated (FC) diffusion gradient waveforms.

STUDY TYPE

Prospective.

POPULATION

Six healthy volunteers (ages: 22-48 years, five females), water phantom.

FIELD STRENGTH/SEQUENCE

3-T, prototype DWI sequence with 2D echo-planar imaging, and bipolar (BP) or FC gradients. 2D Half-Fourier Single-shot Turbo-spin-Echo (HASTE). Multiple-phase 2D spoiled gradient-echo phase contrast (PC) MRI.

ASSESSMENT

BP and FC water signal decays were qualitatively compared. Renal arteries and velocities were visualized on PC-MRI. Systolic (peak velocity), diastolic (end stable velocity), and pre-systolic (before peak velocity) phases were identified. Following mutual information-based retrospective self-registration of DWI within each kidney, and Marchenko-Pastur Principal Component Analysis (MPPCA) denoising, combined IVIM-DTI analysis estimated mean diffusivity (MD), fractional anisotropy (FA), and eigenvalues (λi) from tissue diffusivity (Dt ), perfusion fraction (fp ), and pseudodiffusivity (Dp , Dp,axial , Dp,radial ), for each tissue (cortex/medulla, segmented on b0/FA respectively), phase, and waveform (BP, FC). Monte Carlo water diffusion simulations aided data interpretation.

STATISTICAL TESTS

Mixed model regression probed differences between tissue types and pulse sequences. Univariate general linear model analysis probed variations among cardiac phases. Spearman correlations were measured between diffusion metrics and renal artery velocities. Statistical significance level was set at P < 0.05.

RESULTS

Water BP and FC signal decays showed no differences. Significant pulse sequence dependence occurred for λ1 , λ3 , FA, Dp , fp , Dp,axial , Dp,radial in cortex and medulla, and medullary λ2 . Significant cortex/medulla differences occurred with BP for all metrics except MD (systole [P = 0.224]; diastole [P = 0.556]). Significant phase dependence occurred for Dp , Dp,axial , Dp,radial for BP and medullary λ1 , λ2 , λ3 , MD for FC. FA correlated significantly with velocity. Monte Carlo simulations indicated medullary measurements were consistent with a 34 μm tubule diameter.

DATA CONCLUSION

Cardiac gating and flow compensation modulate of measurements of renal diffusion.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY STAGE: 2.

QSM Throughout the Body

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.

Identifying disease progression in chronic kidney disease using proton magnetic resonance spectroscopy

Chronic kidney disease (CKD) affects approximately 10% of the world population, higher still in some developing countries, and can cause irreversible kidney damage eventually leading to kidney failure requiring dialysis or kidney transplantation. However, not all patients with CKD will progress to this stage, and it is difficult to distinguish between progressors and non-progressors at the time of diagnosis. Current clinical practice involves monitoring estimated glomerular filtration rate and proteinuria to assess CKD trajectory over time; however, there remains a need for novel, validated methods that differentiate CKD progressors and non-progressors. Nuclear magnetic resonance techniques, including magnetic resonance spectroscopy and magnetic resonance imaging, have the potential to improve our understanding of CKD progression. Herein, we review the application of magnetic resonance spectroscopy both in preclinical and clinical settings to improve the diagnosis and surveillance of patients with CKD.

Summary and overview of the first ISMRM workshop on magnetic resonance elastography, August 25-26, 2022, Berlin, Germany

An ISMRM workshop on MR elastography was held at Charité-Universitätsmedizin Berlin on August 25-26, 2022. As an exclusively in-person event, 65 participants from 9 countries attended the workshop despite COVID-19-related restrictions. The topics of the workshop covered cellular and microtissue mechanical interactions, the development of MR elastography driver technology, approaches to inverse problems, clinical applications, and integration of MR elastography into multiparametric MRI protocols. The workshop was a great success by promoting direct knowledge exchange as well as for strategizing future directions for MR elastography. In this symposium review, we briefly summarized all oral presentations as well as the concluding panel discussion.

Multiparametric renal magnetic resonance imaging: A reproducibility study in renal allografts with stable function

Monitoring renal allograft function after transplantation is key for the early detection of allograft impairment, which in turn can contribute to preventing the loss of the allograft. Multiparametric renal MRI (mpMRI) is a promising noninvasive technique to assess and characterize renal physiopathology; however, few studies have employed mpMRI in renal allografts with stable function (maintained function over a long time period). The purposes of the current study were to evaluate the reproducibility of mpMRI in transplant patients and to characterize normal values of the measured parameters, and to estimate the labeling efficiency of Pseudo-Continuous Arterial Spin Labeling (PCASL) in the infrarenal aorta using numerical simulations considering experimental measurements of aortic blood flow profiles. The subjects were 20 transplant patients with stable kidney function, maintained over 1 year. The MRI protocol consisted of PCASL, intravoxel incoherent motion, and T1 inversion recovery. Phase contrast was used to measure aortic blood flow. Renal blood flow (RBF), diffusion coefficient (D), pseudo-diffusion coefficient (D*), flowing fraction ( f ), and T1 maps were calculated and mean values were measured in the cortex and medulla. The labeling efficiency of PCASL was estimated from simulation of Bloch equations. Reproducibility was assessed with the within-subject coefficient of variation, intraclass correlation coefficient, and Bland-Altman analysis. Correlations were evaluated using the Pearson correlation coefficient. The significance level was p less than 0.05. Cortical reproducibility was very good for T1, D, and RBF, moderate for f , and low for D*, while medullary reproducibility was good for T1 and D. Significant correlations in the cortex between RBF and f (r = 0.66), RBF and eGFR (r = 0.64), and D* and eGFR (r = -0.57) were found. Normal values of the measured parameters employing the mpMRI protocol in kidney transplant patients with stable function were characterized and the results showed good reproducibility of the techniques.

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.

Novel strategies in nephrology: what to expect from the future?

Chronic kidney disease (CKD) will become the fifth global case of death by 2040. Its largest impact is on premature mortality but the number of persons with kidney failure requiring renal replacement therapy (RRT) is also increasing dramatically. Current RRT is suboptimal due to the shortage of kidney donors and dismal outcomes associated with both hemodialysis and peritoneal dialysis. Kidney care needs a revolution. In this review, we provide an update on emerging knowledge and technologies that will allow an earlier diagnosis of CKD, addressing the current so-called blind spot (e.g. imaging and biomarkers), and improve renal replacement therapies (wearable artificial kidneys, xenotransplantation, stem cell-derived therapies, bioengineered and bio-artificial kidneys).

Antifibrotic Agents for the Management of CKD: A Review

Kidney fibrosis is a hallmark of chronic kidney disease (CKD) and a potential therapeutic target. However, there are conceptual and practical challenges to directly targeting kidney fibrosis. Whether fibrosis is mainly a cause or a consequence of CKD progression has been disputed. It is unclear whether specifically targeting fibrosis is feasible in clinical practice because most drugs that decrease fibrosis in preclinical models target additional and often multiple pathogenic pathways (eg, renin-angiotensin-aldosterone system blockade). Moreover, tools to assess whole-kidney fibrosis in routine clinical practice are lacking. Pirfenidone, a drug used for idiopathic pulmonary fibrosis, is undergoing a phase 2 trial for kidney fibrosis. Other drugs in use or being tested for idiopathic pulmonary fibrosis (eg, nintedanib, PRM-151, epigallocatechin gallate) are also potential candidates to treat kidney fibrosis. Novel therapeutic approaches may include antagomirs (eg, lademirsen) or drugs targeting interleukin 11 or NKD2 (WNT signaling pathway inhibitor). Reversing the dysfunctional tubular cell metabolism that leads to kidney fibrosis offers additional therapeutic opportunities. However, any future drug targeting fibrosis of the kidneys should demonstrate added benefit to a standard of care that combines renin-angiotensin system with mineralocorticoid receptor (eg, finerenone) blockade or with sodium/glucose cotransporter 2 inhibitors.

Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches

BACKGROUND

 Until today, assessment of renal function has remained a challenge for modern medicine. In many cases, kidney diseases accompanied by a decrease in renal function remain undetected and unsolved, since neither laboratory tests nor imaging diagnostics provide adequate information on kidney status. In recent years, developments in the field of functional magnetic resonance imaging with application to abdominal organs have opened new possibilities combining anatomic imaging with multiparametric functional information. The multiparametric approach enables the measurement of perfusion, diffusion, oxygenation, and tissue characterization in one examination, thus providing more comprehensive insight into pathophysiological processes of diseases as well as effects of therapeutic interventions. However, application of multiparametric fMRI in the kidneys is still restricted mainly to research areas and transfer to the clinical routine is still outstanding. One of the major challenges is the lack of a standardized protocol for acquisition and postprocessing including efficient strategies for data analysis. This article provides an overview of the most common fMRI techniques with application to the kidney together with new approaches regarding data analysis with deep learning.

METHODS

 This article implies a selective literature review using the literature database PubMed in May 2021 supplemented by our own experiences in this field.

RESULTS AND CONCLUSION

 Functional multiparametric MRI is a promising technique for assessing renal function in a more comprehensive approach by combining multiple parameters such as perfusion, diffusion, and BOLD imaging. New approaches with the application of deep learning techniques could substantially contribute to overcoming the challenge of handling the quantity of data and developing more efficient data postprocessing and analysis protocols. Thus, it can be hoped that multiparametric fMRI protocols can be sufficiently optimized to be used for routine renal examination and to assist clinicians in the diagnostics, monitoring, and treatment of kidney diseases in the future.

KEY POINTS

  · Multiparametric fMRI is a technique performed without the use of radiation, contrast media, and invasive methods.. · Multiparametric fMRI provides more comprehensive insight into pathophysiological processes of kidney diseases by combining functional and structural parameters.. · For broader acceptance of fMRI biomarkers, there is a need for standardization of acquisition, postprocessing, and analysis protocols as well as more prospective studies.. · Deep learning techniques could significantly contribute to an optimization of data acquisition and the postprocessing and interpretation of larger quantities of data..

CITATION FORMAT

· Zhang C, Schwartz M, Küstner T et al. Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1775-8633.

Non-contrast-enhanced magnetic resonance imaging can be used to assess renal cortical and medullary volumes—A validation study

Background

Magnetic resonance imaging (MRI) biomarkers can diagnose and prognosticate kidney disease. Renal volume validation studies are however scarce, and measurements are limited by use of contrast agent or advanced post-processing.

Purpose

To validate a widely available non-contrast-enhanced MRI method for quantification of renal cortical and medullary volumes in pigs; investigate observer variability of cortical and medullary volumes in humans; and present reference values for renal cortical and medullary volumes in adolescents.

Materials and Methods

Cortical and medullary volumes were quantified from transaxial in-vivo water-excited MR images in six pigs and 15 healthy adolescents (13–16years). Pig kidneys were excised, and renal cortex and medulla were separately quantified by the water displacement method. Both limits of agreement by the Bland-Altman method and reference ranges are presented as 2.5–97.5 percentiles.

Results

Agreement between MRI and ex-vivo quantification were -7 mL (-10–0 mL) for total parenchyma, -4 mL (-9–3 mL) for cortex, and -2 mL (-7–2 mL) for medulla. Intraobserver variability for pig and human kidneys were <5% for total parenchyma, cortex, and medulla. Interobserver variability for both pig and human kidneys were ≤4% for total parenchyma and cortex, and 6% and 12% for medulla. Reference ranges indexed for body surface area and sex were 54–103 mL/m2 (boys) and 56–103 mL/m2 (girls) for total parenchyma, 39–62 mL/m2 and 36–68 mL/m2 for cortex, and 16–45 mL/m2 and 17–42 mL/m2 for medulla.

Conclusion

The proposed widely available non-contrast-enhanced MRI method can quantify cortical and medullary renal volumes and can be directly implemented clinically.

Comparison of multiparametric magnetic resonance imaging sequences with laboratory parameters for prognosticating renal function in chronic kidney disease

Magnetic resonance imaging (MRI) is playing an increasingly important role in evaluating chronic kidney disease (CKD). It has the potential to be used not only for evaluation of physiological and pathological states, but also for prediction of disease course. Although different MRI sequences have been employed in renal disease, there are few studies that have compared the different sequences. We compared several multiparametric MRI sequences, and compared their results with the estimated glomerular filtration rate. Principal component analysis showed a similarity between T1 values and tissue perfusion (arterial spin labelling), and between fractional anisotropy (diffusion tensor imaging) and apparent diffusion coefficient values (diffusion-weighted imaging). In multiple regression analysis, only T2* values, derived from the blood oxygenation level-dependent (BOLD) MRI sequence, were associated with estimated glomerular filtration rate slope after adjusting for degree of proteinuria, a classic prognostic factor for CKD. In receiver operating characteristic curve analysis, T2* values were a good predictor of rapid deterioration, regardless of the degree of proteinuria. This suggests further study of the use of BOLD-derived T2* values in the workup of CKD, especially to predict the disease course.

Will advances in functional renal magnetic resonance imaging translate to the nephrology clinic?

Characterizing structural and tissue abnormalities of the kidney is fundamental to understanding kidney disease. Functional multi-parametric renal magnetic resonance imaging (MRI) is a noninvasive imaging strategy whereby several sequences are employed within a single session to quantify renal perfusion, tissue oxygenation, fibrosis, inflammation, and oedema without using ionizing radiation. In this review, we discuss evidence surrounding its use in several clinical settings including acute kidney injury, chronic kidney disease, hypertension, polycystic kidney disease and around renal transplantation. Kidney size on MRI is already a validated measure for making therapeutic decisions in the setting of polycystic kidney disease. Functional MRI sequences, T1 mapping and apparent diffusion coefficient, can non-invasively quantify interstitial fibrosis and so may have a near-future role in the nephrology clinic to stratify the risk of progressive chronic kidney disease or transplant dysfunction. Beyond this, multi-parametric MRI may be used diagnostically, for example differentiating inflammatory versus ischaemic causes of renal dysfunction, but this remains to be proven. Changes in MRI properties of kidney parenchyma may be useful surrogate markers to use as end points in clinical trials to assess if drugs prevent renal fibrosis or alter kidney perfusion. Large, multi-centre studies of functional renal MRI are ongoing which aim to provide definitive answers as to its role in the management of patients with renal dysfunction.

Evolving Medical Imaging Techniques for the Assessment of Delayed Graft Function: A Narrative Review

Purpose of review

Delayed graft function (DGF) is a significant complication that contributes to poorer graft function and shortened graft survival. In this review, we sought to evaluate the current and emerging role of medical imaging modalities in the assessment of DGF and how it may guide clinical management.

Sources of information

PubMed, Google Scholar, and ClinicalTrial.gov up until February 2021.

Methods

This narrative review first examined the pathophysiology of DGF and current clinical management. We then summarized relevant studies that utilized medical imaging to assess posttransplant renal complications, namely, DGF. We focused our attention on noninvasive, evolving imaging modalities with the greatest potential for clinical translation, including contrast-enhanced ultrasound (CEUS) and multiparametric magnetic resonance imaging (MRI).

Key findings

A kidney biopsy in the setting of DGF can be used to assess the degree of ischemic renal injury and to rule out acute rejection. Biopsies are accompanied by complications and may be limited by sampling bias. Early studies on CEUS and MRI have shown their potential to distinguish between the 2 most common causes of DGF (acute tubular necrosis and acute rejection), but they have generally included only small numbers of patients and have not kept pace with more recent technical advances of these imaging modalities. There remains unharnessed potential with CEUS and MRI, and more robust clinical studies are needed to better evaluate their role in the current era.

Limitations

The adaptation of emerging approaches for imaging DGF will depend on additional clinical trials to study the feasibility and diagnostic test characteristics of a given modality. This is limited by access to devices, technical competence, and the need for interdisciplinary collaborations to ensure that such studies are well designed to appropriately inform clinical decision-making.

Workflow for automatic renal perfusion quantification using ASL-MRI and machine learning

PURPOSE

Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post-processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). Machine learning has proven its value in medical image segmentation, including the kidneys. This study presents a fully automatic workflow for renal cortex perfusion quantification by including machine learning-based segmentation.

METHODS

Fully automatic workflow was achieved by construction of a cascade of 3 U-nets to replace manual segmentation in ASL quantification. All 1.5T ASL-MRI data, including M₀ , T₁ , and ASL label-control images, from 10 healthy volunteers was used for training (dataset 1). Trained cascade performance was validated on 4 additional volunteers (dataset 2). Manual segmentations were generated by 2 observers, yielding reference and second observer segmentations. To validate the intended use of the automatic segmentations, manual and automatic RBF values in mL/min/100 g were compared.

RESULTS

Good agreement was found between automatic and manual segmentations on dataset 1 (dice score = 0.78 ± 0.04), which was in line with inter-observer variability (dice score = 0.77 ± 0.02). Good agreement was confirmed on dataset 2 (dice score = 0.75 ± 0.03). Moreover, similar cortical RBF was obtained with automatic or manual segmentations, on average and at subject level; with 211 ± 31 mL/min/100 g and 208 ± 31 mL/min/100 g (P < .05), respectively, with narrow limits of agreement at -11 and 4.6 mL/min/100 g. RBF accuracy with automated segmentations was confirmed on dataset 2.

CONCLUSION

Our proposed method automates ASL quantification without compromising RBF accuracy. With quick processing and without observer dependence, renal ASL-MRI is more attractive for clinical application as well as for longitudinal and multi-center studies.

Diffusion tensor imaging for the study of early renal dysfunction in patients affected by bardet-biedl syndrome

Kidney structural abnormalities are common features of Bardet-Biedl syndrome (BBS) patients that lead to a progressive decline in renal function. Magnetic resonance diffusion tensor imaging (DTI) provides useful information on renal microstructures but it has not been applied to these patients. This study investigated using DTI to detect renal abnormalities in BBS patients with no overt renal dysfunction. Ten BBS subjects with estimated glomerular filtration rates over 60 ml/min/1.73m² and 14 individuals matched for age, gender, body mass index and renal function were subjected to high-field DTI. Fractional anisotropy (FA), and mean, radial and axial diffusivity were evaluated from renal cortex and medulla. Moreover, the corticomedullary differentiation of each DTI parameter was compared between groups. Only cortical FA statistically differed between BBS patients and controls (p = 0.033), but all the medullary DTI parameters discriminated between the two groups with lower FA (p < 0.001) and axial diffusivity (p = 0.021) and higher mean diffusivity (p = 0.043) and radial diffusivity (p < 0.001) in BBS patients compared with controls. Corticomedullary differentiation values were significantly reduced in BBS patients. Thus, DTI is a valuable tool for investigating microstructural alterations in renal disorders when kidney functionality is preserved.