New Magnetic Resonance Imaging Index for Renal Fibrosis Assessment: A Comparison between Diffusion-Weighted Imaging and T1 Mapping with Histological Validation

Characterization of kidneys in patients with systemic sclerosis by multi-parametric magnetic resonance quantitative imaging

PURPOSE

To determine the usefulness of multiparametric magnetic resonance (MR) quantitative imaging in characterizing the kidneys in systemic sclerosis (SSc) patients.

MATERIAL AND METHODS

Forty-six SSc patients (47.9 ± 12.8 years, 40 females) and 22 age- and sex- matched healthy volunteers (46.1 ± 13.8 years, 20 females) were recruited and underwent renal MR imaging by acquiring blood oxygen level dependent and saturated multi-delay renal arterial spin labeling (SAMURAI) sequences. The T2* value, T1 value, renal blood flow (RBF), arterial bolus arrival time (aBAT), and tissue bolus arrival time (tBAT) of renal cortex were measured and compared among diffuse cutaneous SSc (dcSSc) and limited cutaneous SSc (lcSSc) groups and healthy controls using One-way ANOVA and analyzed by logistic regression.

RESULTS

Compared to healthy volunteers, SSc patients with normal estimated glomerular filtration rate (n = 40) had significantly lower T2* value (P = 0.026) in the left renal cortex, longer T1 value (right: P = 0.015; left: P = 0.023), lower RBF (right: P < 0.001; left: P < 0.001), and shorter tBAT (right: P < 0.001; left: P = 0.005) in both right and left renal cortex after adjusting for demographics. The dcSSc patients (n = 23) had significantly lower RBF in both right (226.7 ± 65.2 mL/100 g/min vs. 278.2 ± 73.5 mL/100 g/min, P = 0.022) and left (194.5 ± 71.5 mL/100 g/min vs. 252.7 ± 84.4 mL/100 g/min, P = 0.020) renal cortex compared to the lcSSc patients (n = 23) after adjusting for demographics, but the significance of the difference was attenuated after further adjusting for modified Rodnan skin score and digital ulcers.

CONCLUSION

Multi-parametric MR quantitative imaging, particularly multi-delay ASL perfusion imaging, is a useful technique for characterizing the kidneys and classification of SSc patients.

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.

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.

Native T1-mapping as a predictor of progressive renal function decline in chronic kidney disease patients

BACKGROUND

To investigate the potential of Native T1-mapping in predicting the prognosis of patients with chronic kidney disease (CKD).

METHODS

We enrolled 119 CKD patients as the study subjects and included 20 healthy volunteers as the control group, with follow-up extending until October 2022. Out of these patients, 63 underwent kidney biopsy measurements, and these patients were categorized into high (25-50%), low (< 25%), and no renal interstitial fibrosis (IF) (0%) groups. The study's endpoint event was the initiation of renal replacement therapy, kidney transplantation, or an increase of over 30% in serum creatinine levels. Cox regression analysis determined factors influencing unfavorable kidney outcomes. We employed Kaplan-Meier analysis to contrast kidney survival rates between the high and low T1 groups. Additionally, receiver-operating characteristic (ROC) curve analysis assessed the predictive accuracy of Native T1-mapping for kidney endpoint events.

RESULTS

T1 values across varying fibrosis degree groups showed statistical significance (F = 4.772, P < 0.05). Multivariate Cox regression pinpointed 24-h urine protein, cystatin C(CysC), hemoglobin(Hb), and T1 as factors tied to the emergence of kidney endpoint events. Kaplan-Meier survival analysis revealed a markedly higher likelihood of kidney endpoint events in the high T1 group compared to the low T1 value group (P < 0.001). The ROC curves for variables (CysC, T1, Hb) tied to kidney endpoint events demonstrated area under the curves(AUCs) of 0.83 (95%CI: 0.75-0.91) for CysC, 0.77 (95%CI: 0.68-0.86) for T1, and 0.73 (95%CI: 0.63-0.83) for Hb. Combining these variables elevated the AUC to 0.88 (95%CI: 0.81-0.94).

CONCLUSION

Native T1-mapping holds promise in facilitating more precise and earlier detection of CKD patients most at risk for end-stage renal disease.

Contemporary and Emerging MRI Strategies for Assessing Kidney Allograft Complications: Arterial Stenosis and Parenchymal Injury, From the AJR Special Series on Imaging of Fibrosis

MRI plays an important role in the evaluation of kidney allografts for vascular complications as well as parenchymal insults. Transplant renal artery stenosis, the most common vascular complication of kidney transplant, can be evaluated by MRA using gadolinium and nongadolinium contrast agents as well as by unenhanced MRA techniques. Parenchymal injury occurs through a variety of pathways, including graft rejection, acute tubular injury, BK polyomavirus infection, drug-induced interstitial nephritis, and pyelonephritis. Investigational MRI techniques have sought to differentiate among these causes of dysfunction as well as to assess the degree of interstitial fibrosis or tubular atrophy (IFTA)-the common end pathway for all of these processes-which is currently evaluated by invasively obtained core biopsies. Some of these MRI sequences have shown promise in not only assessing the cause of parenchymal injury but also assessing IFTA noninvasively. This review describes current clinically used MRI techniques and previews promising investigational MRI techniques for assessing complications of kidney grafts.

Intravoxel incoherent motion diffusion-weighted imaging for predicting kidney allograft function decline: comparison with clinical parameters

OBJECTIVE

To evaluate the added benefit of diffusion-weighted imaging (DWI) over clinical parameters in predicting kidney allograft function decline.

METHODS

Data from 97 patients with DWI of the kidney allograft were retrospectively analyzed. The DWI signals were analyzed with both the mono-exponential and bi-exponential models, yielding total apparent diffusion coefficient (ADCT), true diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp). Three predictive models were constructed: Model 1 with clinical parameters, Model 2 with DWI parameters, and Model 3 with both clinical and DWI parameters. The predictive capability of each model was compared by calculating the area under the receiver-operating characteristic curve (AUROC).

RESULTS

Forty-five patients experienced kidney allograft function decline during a median follow-up of 98 months. The AUROC for Model 1 gradually decreased with follow-up time > 40 months, whereas Model 2 and Model 3 maintained relatively stable AUROCs. The AUROCs of Model 1 and Model 2 were not statistically significant. Multivariable analysis showed that the Model 3 included cortical D (HR = 3.93, p = 0.001) and cortical fp (HR = 2.85, p = 0.006), in addition to baseline estimated glomerular filtration rate (eGFR) and proteinuria. The AUROCs for Model 3 were significantly higher than those for Model 1 at 60-month (0.91 vs 0.86, p = 0.02) and 84-month (0.90 vs 0.83, p = 0.007) follow-up.

CONCLUSIONS

DWI parameters were comparable to clinical parameters in predicting kidney allograft function decline. Integrating cortical D and fp into the clinical model with baseline eGFR and proteinuria may add prognostic value for long-term allograft function decline.

CRITICAL RELEVANCE STATEMENT

Our findings suggested that cortical D and fp derived from IVIM-DWI increased the performance to predict long-term kidney allograft function decline. This preliminary study provided basis for the utility of multi-b DWI for managing patients with a kidney transplant.

KEY POINTS

• Both clinical and multi-b DWI parameters could predict kidney allograft function decline. • The ability to predict kidney allograft function decline was similar between DWI and clinical parameters. • Cortical D and fp derived from IVIM-DWI increased the performance to predict long-term kidney allograft function decline.

Utilization of the corticomedullary difference in magnetic resonance imaging-derived apparent diffusion coefficient for noninvasive assessment of chronic kidney disease in type 2 diabetes

BACKGROUNDS

Accumulating data demonstrated that the cortico-medullary difference in apparent diffusion coefficient (ΔADC) of diffusion-weighted magnetic resonance imaging (DWI) was a better correlation with kidney fibrosis, tubular atrophy progression, and a predictor of kidney function evolution in chronic kidney disease (CKD).

OBJECTIVES

We aimed to assess the value of ΔADC in evaluating disease severity, differential diagnosis, and the prognostic risk stratification for patients with type 2 diabetes (T2D) and CKD.

METHODS

Total 119 patients with T2D and CKD who underwent renal MRI were prospectively enrolled. Of them, 89 patients had performed kidney biopsy for pathological examination, including 38 patients with biopsy-proven diabetic kidney disease (DKD) and 51 patients with biopsy-proven non-diabetic kidney disease (NDKD) and Mix (DKD + NDKD). Clinicopathological characteristics were compared according to different ΔADC levels. Moreover, univariate and multivariate-linear regression analyses were performed to explore whether ΔADC was independently associated with estimated glomerular filtration rate (eGFR) and urinary albumin creatinine ratio (UACR). The diagnostic performance of ΔADC for discriminating DKD from NDKD + Mix was evaluated by receiver operating characteristic (ROC) analysis. In addition, an individual's 2- or 5-year risk probability of progressing to end-stage kidney disease (ESKD) was calculated by the kidney failure risk equation (KFRE). The effect of ΔADC on prognostic risk stratification was assessed. Additionally, net reclassification improvement (NRI) was used to evaluate the model performance.

RESULTS

All enrolled patients had a median ΔADC level of 86 (IQR 28, 155) × 10-6 mm2/s. ΔADC significantly decreased across the increasing staging of CKD (P < 0.001). Moreover, those with pathological-confirmed DKD has a significantly lower level of ΔADC than those with NDKD and Mix (P < 0.001). It showed that ΔADC was independently associated with eGFR (β = 1.058, 95% CI = [1.002,1.118], P = 0.042) and UACR (β = -3.862, 95% CI = [-7.360, -0.365], P = 0.031) at multivariate linear regression analyses. Besides, ΔADC achieved an AUC of 0.707 (71% sensitivity and 75% specificity) and AUC of 0.823 (94% sensitivity and 67% specificity) for discriminating DKD from NDKD + Mix and higher ESKD risk categories (≥50% at 5 years; ≥10% at 2 years) from lower risk categories (<50% at 5 years; <10% at 2 years). Accordingly, the optimal cutoff value of ΔADC for higher ESKD risk categories was 66 × 10-6 mm2/s, and the group with the low-cutoff level of ΔADC group was associated with 1.232 -fold (95% CI 1.086, 1.398) likelihood of higher ESKD risk categories as compared to the high-cutoff level of ΔADC group in the fully-adjusted model. Reclassification analyses confirmed that the final adjusted model improved NRI.

CONCLUSIONS

ΔADC was strongly associated with eGFR and UACR in patients with T2D and CKD. More importantly, baseline ΔADC was predictive of higher ESKD risk, independently of significant clinical confounding. Specifically, ΔADC <78 × 10-6 mm2/s and <66 × 10-6 mm2/s would help to identify T2D patients with the diagnosis of DKD and higher ESKD risk categories, respectively.

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.

Advances in imaging techniques to assess kidney fibrosis

As a sign of chronic kidney disease (CKD) progression, renal fibrosis is an irreversible and alarming pathological change. The accurate diagnosis of renal fibrosis depends on the widely used renal biopsy, but this diagnostic modality is invasive and can easily lead to sampling error. With the development of imaging techniques, an increasing number of noninvasive imaging techniques, such as multipara meter magnetic resonance imaging (MRI) and ultrasound elastography, have gained attention in assessing kidney fibrosis. Depending on their ability to detect changes in tissue stiffness and diffusion of water molecules, ultrasound elastography and some MRI techniques can indirectly assess the degree of fibrosis. The worsening of renal tissue oxygenation and perfusion measured by blood oxygenation level-dependent MRI and arterial spin labeling MRI separately is also an indirect reflection of renal fibrosis. Objective and quantitative indices of fibrosis may be available in the future by using novel techniques, such as photoacoustic imaging and fluorescence microscopy. However, these imaging techniques are susceptible to interference or may not be convenient. Due to the lack of sufficient specificity and sensitivity, these imaging techniques are neither widely accepted nor proposed by clinicians. These obstructions must be overcome by conducting technology research and more prospective studies. In this review, we emphasize the recent advancement of these noninvasive imaging techniques and provide clinicians a continuously updated perspective on the assessment of kidney fibrosis.

Characterization of renal fibrosis in rats with chronic kidney disease by in vivo tomoelastography

Chronic kidney disease (CKD) is characterized by structural changes, such as tubular atrophy, renal fibrosis, and glomerulosclerosis, all of which affect the viscoelastic properties of biological tissues. However, detection of renal viscoelasticity changes because diagnostic markers by in vivo elastography lack histopathological validation through animal models. Therefore, we investigated in vivo multiparametric magnetic resonance imaging (mp-MRI), including multifrequency magnetic resonance elastography-based tomoelastography, in the kidneys of 10 rats with adenine-induced CKD and eight healthy controls. Kidney volume (in mm3 ), water diffusivity (apparent diffusion coefficient [ADC] in mm2 /s), shear wave speed (SWS; in m/s; related to stiffness), and wave penetration rate (PR; in m/s; related to inverse viscosity) were quantified by mp-MRI and correlated with histopathologically determined renal fibrosis (collagen area fraction [CAF]; in %). Kidney volume (40% ± 29%, p = 0.009), SWS (11% ± 12%, p = 0.016), and PR (20% ± 15%, p = 0.004) were significantly increased in CKD, which was accompanied by ADC (-24% ± 27%, p = 0.02). SWS, PR, and ADC were correlated with CAF with R = 0.63, 0.75, and -0.5 (all p < 0.05), respectively. In the CKD rats, histopathology showed tubule dilation due to adenine crystal deposition. Collectively, our results suggest that collagen accumulation during CKD progression transforms soft-compliant renal tissue into a more rigid-solid state with reduced water mobility. We hypothesized that tubule dilation-a specific feature of our model-might lead to higher intraluminal pressure, which could also contribute to elevated renal stiffness. Tomoelastography is a promising tool for noninvasively assessing disease progression, detecting biomechanical properties that are sensitive to different pathologic features of CKD.

Magnetic Resonance Imaging to Evaluate Kidney Structure, Function, and Pathology: Moving Toward Clinical Application

Recent advances in multiparametric magnetic resonance imaging (MRI) allow multiple quantitative measures to assess kidney morphology, tissue microstructure, oxygenation, kidney blood flow, and perfusion to be collected in a single scan session. Animal and clinical studies have investigated the relationship between the different MRI measures and biological processes, although their interpretation can be complex due to variations in study design and generally small participant numbers. However, emerging themes include the apparent diffusion coefficient derived from diffusion-weighted imaging, T1 and T2 mapping parameters, and cortical perfusion being consistently associated with kidney damage and predicting kidney function decline. Blood oxygen level-dependent (BOLD) MRI has shown inconsistent associations with kidney damage markers but has been predictive of kidney function decline in several studies. Therefore, multiparametric MRI of the kidneys has the potential to address the limitations of existing diagnostic methods to provide a noninvasive, noncontrast, and radiation-free method to assess whole kidney structure and function. Barriers to be overcome to facilitate widespread clinical application include improved understanding of biological factors that impact MRI measures, development of a larger evidence base for clinical utility, standardization of MRI protocols, automation of data analysis, determining optimal combination of MRI measures, and health economic evaluation.

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.

Pregnancy-Associated Renal Cortical Necrosis and Nonenhanced Functional MRI: A Case Series

Rationale & Objective

Pregnancy-associated renal cortical necrosis is a critical illness with a poor prognosis. We aimed to describe the clinical and magnetic resonance imaging (MRI) characteristics of a case series of patients with acute kidney injury in the setting of pregnancy-associated renal cortical necrosis.

Study Design

Case series.

Setting & Participants

Seventeen patients from a single center diagnosed by nonenhanced functional MRI and/or kidney pathology.

Results

All patients presented with postpartum acute kidney injury stage 3. Of the 17 patients, 15 (88%) had pregnancy-associated atypical hemolytic uremic syndrome, 11 (65%) had postpartum hemorrhage, 7 (41%) had preeclampsia/hemolysis elevated liver enzymes low platelet count syndrome, and 4 (24%) had disseminated intravascular coagulation. On T2-weighted MRI, the diffuse phenotype showed outer cortex swelling in the early phase, with a dark signal rim involving the inner cortex and Bertin column, which became more apparent over time along with cortical thinning, substantially decreasing T2 signal intensity. The focal phenotype showed focally distributed hypointense signals in the cortex. After 8-101 (median: 60) months of follow-up, 4 individuals had estimated glomerular filtration rates ≥60 mL/min/1.73 m², 6 had estimated glomerular filtration rates of 15-60 mL/min/1.73 m², and 7 had kidney failure requiring kidney replacement therapy. The diffuse phenotype was present in all of the individuals who remained kidney replacement therapy dependent.

Limitations

Retrospective study; small sample size.

Conclusions

Different forms of pregnancy-associated thrombotic microangiopathy were the major causative diseases in our pregnancy-associated renal cortical necrosis case series. Nonenhanced functional MRI may provide valuable data for establishing diagnosis and kidney prognosis.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Validation of automatically measured T1 map cortico-medullary difference (ΔT1) for eGFR and fibrosis assessment in allograft kidneys

MRI T1-mapping is an important non-invasive tool for renal diagnosis. Previous work shows that ΔT1 (cortex-medullary difference in T1) has significant correlation with interstitial fibrosis in chronic kidney disease (CKD) allograft patients. However, measuring cortico-medullary values by manually drawing ROIs over cortex and medulla (a gold standard method) is challenging, time-consuming, subjective and requires human training. Moreover, such subjective ROI placement may also affect the work reproducibility. This work proposes a deep learning-based 2D U-Net (RCM U-Net) to auto-segment the renal cortex and medulla of CKD allograft kidney T1 maps. Furthermore, this study presents a correlation of automatically measured ΔT1 values with eGFR and percentage fibrosis in allograft kidneys. Also, the RCM U-Net correlation results are compared with the manual ROI correlation analysis. The RCM U-Net has been trained and validated on T1 maps from 40 patients (n = 2400 augmented images) and tested on 10 patients (n = 600 augmented images). The RCM U-Net segmentation results are compared with the standard VGG16, VGG19, ResNet34 and ResNet50 networks with U-Net as backbone. For clinical validation of the RCM U-Net segmentation, another set of 114 allograft kidneys patient's cortex and medulla were automatically segmented to measure the ΔT1 values and correlated with eGFR and fibrosis. Overall, the RCM U-Net showed 50% less Mean Absolute Error (MAE), 16% better Dice Coefficient (DC) score and 12% improved results in terms of Sensitivity (SE) over conventional CNNs (i.e. VGG16, VGG19, ResNet34 and ResNet50) while the Specificity (SP) and Accuracy (ACC) did not show significant improvement (i.e. 0.5% improvement) for both cortex and medulla segmentation. For eGFR and fibrosis assessment, the proposed RCM U-Net correlation coefficient (r) and R-square (R2) was better correlated (r = -0.2, R2 = 0.041 with p = 0.039) to eGFR than manual ROI values (r = -0.19, R2 = 0.037 with p = 0.051). Similarly, the proposed RCM U-Net had noticeably better r and R2 values (r = 0.25, R2 = 0.065 with p = 0.007) for the correlation with the renal percentage fibrosis than the Manual ROI results (r = 0.3, R2 = 0.091 and p = 0.0013). Using a linear mixed model, T1 was significantly higher in the medulla than in the cortex (p<0.0001) and significantly lower in patients with cellular rejection when compared to both patients without rejection and those with humoral rejection (p<0.001). There was no significant difference in T1 between patients with and without humoral rejection (p = 0.43), nor between the types of T1 measurements (Gold standard manual versus automated RCM U-Net) (p = 0.7). The cortico-medullary area ratio measured by the RCM U-Net was significantly increased in case of cellular rejection by comparison to humoral rejection (1.6 +/- 0.39 versus 0.99 +/- 0.32, p = 0.019). In conclusion, the proposed RCM U-Net provides more robust auto-segmented cortex and medulla than the other standard CNNs allowing a good correlation of ΔT1 with eGFR and fibrosis as reported in literature as well as the differentiation of cellular and humoral transplant rejection. Therefore, the proposed approach is a promising alternative to the gold standard manual ROI method to measure T1 values without user interaction, which helps to reduce analysis time and improves reproducibility.

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.

Fibrosis imaging with multiparametric proton and sodium MRI in pig injury models

Chronic kidney disease (CKD) is common and has huge implications for health and mortality. It is aggravated by intrarenal fibrosis, but the assessment of fibrosis is limited to kidney biopsies, which carry a risk of complications and sampling errors. This calls for a noninvasive modality for diagnosing and staging intrarenal fibrosis. The current, exploratory study evaluates a multiparametric MRI protocol including sodium imaging (²³ Na-MRI) to determine the opportunities within this modality to assess kidney injury as a surrogate endpoint of fibrosis. The study includes 43 pigs exposed to ischemia-reperfusion injury (IRI) or unilateral ureteral obstruction (UUO), or serving as healthy controls. Fibrosis was determined using gene expression analysis of collagen. The medulla/cortex ratio of ²³ Na-MRI decreased in the injured kidney in the IRI pigs, but not in the UUO pigs (p = 0.0180, p = 0.0754). To assess the combination of MRI parameters in estimating fibrosis, we created a linear regression model consisting of the cortical apparent diffusion coefficient, ΔR2*, ΔT1, the ²³ Na medulla/cortex ratio, and plasma creatinine (R²  = 0.8009, p = 0.0117). The ²³ Na medulla/cortex ratio only slightly improved the fibrosis prediction model, leaving ²³ Na-MRI in an ambiguous place for evaluation of intrarenal fibrosis. Use of multiparametric MRI in combination with plasma creatinine shows potential for the estimation of fibrosis in human kidney disease, but more translational and clinical work is warranted before MRI can contribute to earlier diagnosis and evaluation of treatment for acute kidney injury and CKD.

The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model

We evaluated a multiclass classification model to predict estimated glomerular filtration rate (eGFR) groups in chronic kidney disease (CKD) patients using magnetic resonance imaging (MRI) texture analysis (TA). We identified 166 CKD patients who underwent MRI comprising Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images, apparent diffusion coefficient (ADC) maps, and T2* maps. The patients were divided into severe, moderate, and control groups based on eGFR borderlines of 30 and 60 mL/min/1.73 m². After extracting 93 texture features (TFs), dimension reduction was performed using inter-observer reproducibility analysis and sequential feature selection (SFS) algorithm. Models were created using linear discriminant analysis (LDA); support vector machine (SVM) with linear, rbf, and sigmoid kernels; decision tree (DT); and random forest (RF) classifiers, with synthetic minority oversampling technique (SMOTE). Models underwent 100-time repeat nested cross-validation. Overall performances of our classification models were modest, and TA based on T1-weighted IP/OP/WO images provided better performance than those based on ADC and T2* maps. The most favorable result was observed in the T1-weighted WO image using RF classifier and the combination model was derived from all T1-weighted images using SVM classifier with rbf kernel. Among the selected TFs, total energy and energy had weak correlations with eGFR.

Multiparametric quantitative renal MRI in children and young adults: comparison between healthy individuals and patients with chronic kidney disease

PURPOSE

Multiparametric quantitative renal MRI may provide noninvasive radiologic biomarkers of chronic kidney disease (CKD) based on investigations in animal models and adults. We aimed to (1) obtain normative multiparametric quantitative MRI data from the kidneys of healthy children and young adults, (2) compare MRI measurements between healthy control participants and patients with CKD, and (3) determine if MRI measurements correlate with clinical and laboratory data as well as histology.

METHODS

This was a prospective, case-control study of 20 healthy controls and 12 CKD patients who underwent percutaneous renal biopsy ranging from 12 to 23 years of age between October 2018 and March 2020. Kidney function was documented and pathology assessed for fibrosis/inflammation. Utilizing a field strength of 1.5T, we examined renal T1, T2, and T2* relaxation mapping, MR elastography (MRE), and diffusion-weighted imaging (DWI). A single analyst made all manual measurements for quantitative MRI pulse sequences. Independent measurements from cortex, medulla, and whole kidney were obtained by drawing regions of interest on single slices from the upper, mid, and lower kidney. A weighted average was calculated for each kidney; if two kidneys, the right and left were averaged. Continuous variables were compared with Mann-Whitney U test; bivariate relationships were assessed using Spearman rank-order correlation.

RESULTS

Median estimated glomerular filtration rate (eGFR) was 112.3 ml/min/1.73 m² in controls (n = 20, 10 females) and 55.0 ml/min/m² in CKD patients (n = 12, 2 females) (p < 0.0001). Whole kidney (1333 vs. 1291 ms; p = 0.018) and cortical (1212 vs 1137 ms; p < 0.0001) T1 values were higher in CKD patients. Cortical T1 values correlated with eGFR (rho = - 0.62; p = 0.0003) and cystatin C (rho = 0.58; p = 0.0007). Whole kidney (1.87 vs. 2.02 10^-3 mm²/s; p = 0.007), cortical (1.89 vs. 2.04 10^-3 mm²/s; p = 0.008), and medullary (1.87 vs. 1.98 10^-3 mm²/s; p = 0.0095) DWI apparent diffusion coefficients (ADC) were lower in CKD patients. Whole kidney ADC correlated with eGFR (rho = 0.45; p = 0.012) and cystatin C (rho = - 0.46; p = 0.009). Cortical histologic inflammation correlated with DWI ADC (rho = - 0.71; p = 0.011).

CONCLUSION

Renal T1 relaxation and DWI ADC measurements differ between pediatric healthy controls and CKD patients, correlate with laboratory markers of CKD, and may have histologic correlates.

MRI-based kidney radiomic analysis during chronic lithium treatment

BACKGROUND

Lithium therapy during bipolar disorder is associated with an increased risk of chronic kidney disease (CKD) that is slowly progressive and undetectable at early stages. We aimed at identifying kidney image texture features as possible imaging biomarkers of decreased measured glomerular filtration rate (mGFR) using radiomics of T2-weighted magnetic resonance imaging (MRI).

METHODS

One hundred and eight patients treated with lithium were evaluated including mGFR and kidney MRI, with T2-weighted sequence single-shot fast spin-echo. Computed radiomic analysis was performed after kidney segmentation. Significant features were selected to build a radiomic signature using multivariable Cox analysis to detect an mGFR <60 ml/min/1.73 m². The texture index was validated using a training and a validation cohort.

RESULTS

Texture analysis index was able to detect an mGFR decrease, with an AUC of 0.85 in the training cohort and 0.71 in the validation cohort. Patients with a texture index below the median were older (59 [42-66] vs. 46 [34-54] years, p = .001), with longer treatment duration (10 [3-22] vs. 6 [2-10] years, p = .02) and a lower mGFR (66 [46-84] vs. 83 [71-94] ml/min/1.73m², p < .001). Texture analysis index was independently and negatively associated with age (β = -.004 ± 0.001, p < .001), serum vasopressin (-0.005 ± 0.002, p = .02) and lithium treatment duration (-0.01 ± 0.003, p = .001), with a significant interaction between lithium treatment duration and mGFR (p = .02).

CONCLUSIONS

A renal texture index was developed among patients treated with lithium associated with a decreased mGFR. This index might be relevant in the diagnosis of lithium-induced renal toxicity.

Cardiac Remodeling in Hypertension: Clinical Impact on Brain, Heart, and Kidney Function

Hypertension is the most common causative factor of cardiac remodeling, which, in turn, has been associated with changes in brain and kidney function. Currently, the role of blood biomarkers as indices of cardiac remodeling remains unclear. In contrast, cardiac imaging, including echocardiography and cardiovascular magnetic resonance (CMR), has been a valuable noninvasive tool to assess cardiac remodeling. Cardiac remodeling during the course of systemic hypertension is not the sole effect of the latter. "Remodeling" of other vital organs, such as brain and kidney, also takes place. Therefore, it will be more accurate if we discuss about "hypertensive remodeling" involving the heart, the brain, and the kidneys, rather than isolated cardiac remodeling. This supports the idea of their simultaneous assessment to identify the early, silent lesions of total "hypertensive remodeling". In this context, magnetic resonance imaging is the ideal modality to provide useful information about these organs in a noninvasive fashion and without radiation. For this purpose, we propose a combined protocol to employ MRI in the simultaneous assessment of the heart, brain and kidneys. This protocol should include all necessary indices for the evaluation of "hypertensive remodeling" in these 3 organs, and could be performed within a reasonable time, not exceeding one hour, so that it remains patient-friendly. Furthermore, a combined protocol may offer "all in one examination" and save time. Finally, the amount of contrast agent used will be limited granted that post-contrast evaluations of the three organs will be performed after 1 injection.

Diffusion-Weighted MRI in the Genitourinary System

Diffusion weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence's usage in female pelvis, prostate, bladder, penis, testis and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging-Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors has significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or in the bladder and testicular mpMRI.

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.

Diffusion-Magnetic Resonance Imaging predicts decline of kidney function in chronic kidney disease and in patients with a kidney allograft

Kidney cortical interstitial fibrosis is highly predictive of kidney prognosis and is currently assessed by evaluation of a biopsy. Diffusion-weighted magnetic resonance imaging is a promising non-invasive tool to evaluate kidney fibrosis. We recently adapted diffusion-weighted imaging sequence for discrimination between the kidney cortex and medulla and found that the cortico-medullary difference in apparent diffusion coefficient (ΔADC) correlated with histological interstitial fibrosis. Here, we assessed whether ΔADC as measured with diffusion-weighted magnetic resonance imaging is predictive of kidney function decline and dialysis initiation in chronic kidney disease (CKD) and patients with a kidney allograft in a prospective study encompassing 197 patients. We measured ΔADC in 43 patients with CKD (estimated GFR (eGFR) 55ml/min/1.73m²) and 154 patients with a kidney allograft (eGFR 53ml/min/1.73m²). Patients underwent a kidney biopsy and diffusion-weighted magnetic resonance imaging within one week of biopsy; median follow-up of 2.2 years with measured laboratory parameters. The primary outcome was a rapid decline of kidney function (eGFR decline over 30% or dialysis initiation) during follow up. Significantly, patients with a negative ΔADC had 5.4 times more risk of rapid decline of kidney function or dialysis (95% confidence interval: 2.29-12.58). After correction for kidney function at baseline and proteinuria, low ADC still predicted significant kidney function loss with a hazard ratio of 4.62 (95% confidence interval 1.56-13.67) independent of baseline age, sex, eGFR and proteinuria. Thus, low ΔADC can be a predictor of kidney function decline and dialysis initiation in patients with native kidney disease or kidney allograft, independent of baseline kidney function and proteinuria.

Evaluation of renal fibrosis in various causes of glomerulonephritis by MR elastography: a clinicopathologic comparative analysis

BACKGROUND

Renal parenchymal fibrosis is the most important determinant of kidney disease progression and it is determined via biopsy. The aim of this study is to evaluate the renal stiffness noninvasively by magnetic resonance elastography (MRE) and to compare it with clinicopathologic parameters in glomerulonephritis and AA amyloidosis patients.

METHODS

Thirty-four patients with glomerular filtration rate (GFR) over 20 ml/min/1.73m² had non-contrast MRE prospectively. Kidney stiffness values were obtained from whole kidney, cortex, and medulla. Values were correlated with GFR, albuminuria, proteinuria, and degree of fibrosis that are assessed via renal biopsy. Patients were grouped clinicopathologically to assess the relation between stiffness and chronicity.

RESULTS

Mean whole kidney, cortex, and medulla stiffnesses were 3.78 (± 1.26), 3.63 (± 1.25), and 4.77 (± 2.03) kPa, respectively. Mean global glomerulosclerosis was 22% (± 18%) and median segmental glomerulosclerosis was 4% (min-max: 0%-100%). Extent of tubulointerstitial fibrosis was less than 25% in 26 of the patients (76.5%), 25%-50% in 6 of the patients (17.6%), and higher than 50% in 2 of the patients (5.9%). Fourteen patients were defined to have chronic renal parenchymal injury. MRE-derived stiffness values correlated negatively with parameters of fibrosis. Lower stiffness values were observed in patients with chronic renal injury compared to those without (P < 0.05 for whole kidney and medulla MRE-derived stiffness).

CONCLUSION

MRE-derived stiffness values were lower in patients with chronic injury. Stiffness decreases as glomerulosclerosis and tubulointerstitial fibrosis progresses in patients with primary glomerulonephritis and AA amyloidosis. With future studies, there may be a role for MRE to assess renal function in concert with conventional markers.

Assessment of renal function using magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses

Background

The incidence of chronic kidney disease (CKD) is high, and is easy to develop into end-stage renal disease (ESRD), which requires kidney dialysis or kidney transplantation. Therefore, we want to explore the clinical value of magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses (SLEEK) in assessing renal function in the early stage.

Methods

One hundred and twenty-nine patients underwent abdominal MRI examination, including a coronal SLEEK sequence. The patients were divided into the control group [CG, 47 cases, estimated glomerular filtration rate (eGFR) >90], the mild renal function impairment (mRI) group (48 cases, eGFR =60–90), and the moderate to severe renal function impairment (m-sRI) group (34 cases, eGFR <60). Two experienced radiologists delineated cortex and medulla regions of interest (ROIs) on SLEEK images to obtain cortex and medulla quantitative histogram parameters [Mean, Median, Percentiles (5^th, 10^th, 25^th, 75^th, and 90^th), Skewness, Kurtosis, and Entropy] using FireVoxel. These histogram parameters were compared by proper statistical methods such as one-way analysis of variance, the χ² test, and receiver operating characteristic (ROC) curve analysis.

Results

Four histogram parameters (Inhomogeneity_cortex, Skewness_cortex, Kurtosis_medulla, and Entropy_medulla) differed significantly between the CG and the mRI group. One medulla (Entropy_medulla) and nine cortex (Mean_cortex, Median_cortex, Kurtosis_cortex, Entropy_cortex, and 5^th, 10^th, 25^th, 75^th, and 90^th Percentile_cortex) histogram parameters were significantly different between the m-RI and m-sRI groups. The most relevant parameter to eGFR was Inhomogenity_cortex (r=−0.450, P<0.001). Inhomogeneity_cortex had the largest area under the curve (AUC) for differentiating the mRI group from the CG (AUC =0.718; 95% CI: 0.616–0.806), while 25^th Percentile_cortex generated the largest AUC (AUC =0.786; 95% CI: 0.681–0.869) for differentiating the mRI and m-sRI groups.

Conclusions

Quantitative histogram parameters based on a SLEEK sequence can be used to supplement renal dysfunction assessment. Cortex histogram parameters are more valuable for evaluating renal function than medulla histogram parameters.

Native T1 Mapping in Assessing Kidney Fibrosis for Patients With Chronic Glomerulonephritis

Purpose: To assess the utility of non-contrast enhanced native T1 mapping of the renal cortex in assessing renal fibrosis for patients with chronic glomerulonephritis (CGN). Methods: A total of 119 patients with CGN and 19 healthy volunteers (HVs) were recruited for this study. Among these patients, 43 had undergone kidney biopsy measurements. Clinical information and biopsy pathological scores were collected. According to the results of the renal biopsy, the patients were classified into the high (25-50%), low (<25%) and no renal interstitial fibrosis (IF) (0%) groups. The correlations between the T1 value in the renal cortex and each of the clinical parameters were separately analyzed. The relationships between each fibrosis group and the T1 value were also evaluated and compared between groups. Binary logistic regression analysis was further used to determine the relationship between the T1 value and renal fibrosis. Receiver operating characteristic (ROC) curves were plotted to analyze the diagnostic value of the T1 value for renal fibrosis. Results: Compared with those of the HVs, the T1 values were significantly higher in patients at all stages of chronic kidney disease (CKD) (all p < 0.05). Significant T1 differences were also revealed between patients with different stages of CKD (p < 0.05). Additionally, the T1 value correlated well with CKD stage (p < 0.05), except between CKD 2 and 3. In addition, the T1 value was positively correlated with cystatin C, neutrophil gelatinase-associated lipocalin, and serum creatinine and negatively correlated with hemoglobin, kidney length, estimated glomerular filtration rate and hematocrit (all p < 0.05). Compared with those of the no IF group, the T1 values were increased in the low- and high-IF groups (both p < 0.05). Logistic regression analysis showed that an elevated T1 value was an independent risk factor for renal fibrosis. ROC analysis suggested that the optimal critical value of T1 for predicting renal fibrosis was 1,695 ms, with a specificity of 0.778 and a sensitivity of 0.625. Conclusion: Native T1 mapping demonstrated good diagnostic performance in evaluating renal function and was an effective noninvasive method for detecting renal fibrosis in CGN patients.

Hyperpolarized pyruvate to measure the influence of PKM2 activation on glucose metabolism in the healthy kidney

The purpose of the current study was to investigate if hyperpolarized [1-13 C]pyruvate can inform us on the metabolic consequences for the kidney glucose metabolism upon treatment with the pyruvate kinase M2 (PKM2) activator TEPP-46, which has shown promise as a novel therapeutic target for diabetic nephropathy. A healthy male Wistar rat model was employed to study the conversion of [1-13 C]pyruvate to [1-13 C]lactate in the kidney 2 and 4 h after treatment with TEPP-46. All rats were scanned with hyperpolarized [1-13 C]pyruvate kidney MR and vital parameters and blood samples were taken after scanning. The PKM2 activator TEPP-46 increases the glycolytic activity in the kidneys, leading to an increased lactate production, as seen by hyperpolarized pyruvate-to-lactate conversion. The results are supported by an increase in blood lactate, a decreased blood glucose level and an increased pyruvate kinase (PK) activity. The metabolic changes observed in both kidneys following treatment with TEPP-46 are largely independent of renal function and could as such represent a new and extremely sensitive metabolic readout for future drugs targeting PKM2. These results warrant further studies in disease models to evaluate if [1-13 C]pyruvate-to-[1-13 C]lactate conversion can predict treatment outcome.

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.

Diffusion-Weighted Imaging and Mapping of T1 and T2 Relaxation Time for Evaluation of Chronic Renal Allograft Rejection in a Translational Mouse Model

We hypothesized that multiparametric MRI is able to non-invasively assess, characterize and monitor renal allograft pathology in a translational mouse model of chronic allograft rejection. Chronic rejection was induced by allogenic kidney transplantation (ktx) of BALB/c-kidneys into C57BL/6-mice (n = 23). Animals after isogenic ktx (n = 18) and non-transplanted healthy animals (n = 22) served as controls. MRI sequences (7T) were acquired 3 and 6 weeks after ktx and quantitative T1, T2 and apparent diffusion coefficient (ADC) maps were calculated. In addition, in a subset of animals, histological changes after ktx were evaluated. Chronic rejection was associated with a significant prolongation of T1 time compared to isogenic ktx 3 (1965 ± 53 vs. 1457 ± 52 ms, p < 0.001) and 6 weeks after surgery (1899 ± 79 vs. 1393 ± 51 ms, p < 0.001). While mean T2 times and ADC were not significantly different between allogenic and isogenic kidney grafts, histogram-based analysis of ADC revealed significantly increased tissue heterogeneity in allografts at both time points (standard derivation/entropy/interquartile range, p < 0.05). Correspondingly, histological analysis showed severe inflammation, graft fibrosis and tissue heterogeneity in allogenic but not in isogenic kidney grafts. In conclusion, renal diffusion weighted imaging and mapping of T2 and T1 relaxation times enable detection of chronic renal allograft rejection in mice. The combined quantitative assessment of mean values and histograms provides non-invasive information of chronic changes in renal grafts and allows longitudinal monitoring.

Renal tubular dilation and fibrosis after unilateral ureter obstruction revealed by relaxometry and spin-lock exchange MRI

We evaluated the use of quantitative MRI relaxometry, including the dispersion of spin-lock relaxation with different locking fields, for detecting and assessing tubular dilation and fibrosis in a mouse model of unilateral ureter obstruction (UUO). C57BL/6 J and BALB/c mice that exhibit different levels of tubular dilation and renal fibrosis after UUO were subjected to MR imaging at 7 T. Mice were imaged before UUO surgery, and at 5, 10 and 15 days after surgery. We acquired maps of relaxation rates and fit the dispersion of spin-lock relaxation rates R1ρ at different locking fields (frequencies) to a model of exchanging water pools, and assessed the sensitivity of the derived quantities for detecting tubular dilation and fibrosis in kidney. Histological scores for tubular dilation and fibrosis, based on luminal space and positive fibrotic areas in sections, were obtained for comparison. Histology detected extensive tubular dilation and mild to moderate fibrosis in the UUO kidneys, in which enlargement of luminal space, deposition of collagen, and reductions in capillary density were observed in the cortex and outer stripe of the outer medulla. Relaxation rates R1 , R2 and R1ρ clearly decreased in these regions of UUO kidneys longitudinally. While R1 showed the highest detectability to tubular dilation and overall changes in UUO kidneys, Sρ , a parameter derived from R1ρ dispersion data, showed the highest correlation with renal fibrosis in UUO. While relaxation parameters are sensitive to tubular dilation in UUO kidneys, Sρ depends primarily on the average exchange rate between water and other chemically shifted resonances such as hydroxyls and amides, and provides additional specific information for evaluating fibrosis in kidney disease.

Imaging of renal fibrosis

PURPOSE OF REVIEW

Fibrosis is an important biomarker of chronic kidney injury, and a powerful predictor of renal outcome. Currently, the only method for measuring fibrotic burden is histologic analysis, which requires a kidney biopsy in humans, or kidney removal in animal models. These requirements have not only hindered our ability to manage patients effectively, but have also prevented a full understanding of renal fibrosis pathogenesis, and slowed the translation of new antifibrotic agents. The development of noninvasive fibrosis imaging tools could thus transform both clinical care and renal fibrosis research.

RECENT FINDINGS

Conventional imaging modalities have historically failed to image fibrosis successfully. However, recent exciting technological advances have greatly enhanced their capabilities. New techniques, for example, may allow imaging of the physical consequences of scarring, as surrogate measures of renal fibrosis. Similarly, other groups have developed ways to directly image extracellular matrix, either with the use of contrast-enhanced probes, or using matrix components as endogenous contrast agents.

SUMMARY

New developments in imaging technology have the potential to transform our ability to visualize renal fibrosis and to monitor its progression. In doing so, these advances could have major implications for kidney disease care, the development of new antiscarring agents, and our understanding of renal fibrosis in general.

Longitudinal Multiparametric MRI Assessment of Irradiated Salivary Gland in a Rat Model: Correlated With Histological Findings

BACKGROUND

Several magnetic resonance imaging (MRI) sequences have been applied to assess injured glands but without histological validation.

PURPOSE

To evaluate longitudinal changes in multiparametric MRI (mp-MRI) of irradiated salivary glands in a rat model and investigate correlations between mp-MRI and histological findings.

STUDY TYPE

Prospective.

ANIMAL MODEL

Submandibular glands of 36 rats were radiated using a single dose of 15 Gy X-ray (irradiation [IR] group), and 6 other rats were enrolled into sham-IR group. mp-MRI were scanned 1 day after sham-IR (n = 6), or 1, 2, 4, 8, 12, 24 weeks after IR (n = 36, 6 per subgroup).

FIELD STRENGTH/SEQUENCE

A 3.0-T/Diffusion-weighted imaging (DWI), readout-segmented echo-planar imaging (EPI) sequence; intravoxel incoherent motion DWI, single-shot EPI sequence; T1 mapping, dual-flip-angle gradient-echo sequence with volumetric interpolated breath-hold examination; T2 mapping, turbo spin-echo sequence.

ASSESSMENT

Parameters including apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D^* ), perfusion fraction (f), T1 and T2 value were obtained. Histological examinations, including hematoxylin and eosin staining (for acinar cell fraction [AC%] detection), Masson's trichrome staining (for degree of fibrosis [F%] determination) and CD34-immunohistochemical staining (for microvessel density [MVD] calculation), were performed at corresponding time points.

STATISTICAL TESTS

One-way analysis of variance was used to compare the mp-MRI and histological parameters among different groups. Spearman correlation analysis was applied to determine the correlation between mp-MRI and histological parameters. Two-sided P ≤ 0.05 was considered statistically significant.

RESULTS

Changes of mp-MRI parameters (ADC, D, D^* , f, T1, T2) and histological results (AC%, F%, MVD) among the seven groups were all significant. ADC, D, and T2 values negatively correlated with AC% (ADC, r = -0.728; D, r = -0.773; T2, r = -0.600), f positively correlated with MVD (r = 0.496), and T1 values positively correlated with F% (r = 0.714). DATA CONCLUSION: mp-MRI might be able to noninvasively and quantitatively evaluate the dynamic pathological changes within the irradiated salivary glands.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system

Background

The use of rigid multi-exponential models (with a priori predefined numbers of components) is common practice for diffusion-weighted MRI (DWI) analysis of the kidney. This approach may not accurately reflect renal microstructure, as the data are forced to conform to the a priori assumptions of simplified models. This work examines the feasibility of less constrained, data-driven non-negative least squares (NNLS) continuum modelling for DWI of the kidney tubule system in simulations that include emulations of pathophysiological conditions.

Methods

Non-linear least squares (LS) fitting was used as reference for the simulations. For performance assessment, a threshold of 5% or 10% for the mean absolute percentage error (MAPE) of NNLS and LS results was used. As ground truth, a tri-exponential model using defined volume fractions and diffusion coefficients for each renal compartment (tubule system: D_tubules , f_tubules ; renal tissue: D_tissue , f_tissue ; renal blood: D_blood , f_blood ;) was applied. The impact of: (I) signal-to-noise ratio (SNR) =40-1,000, (II) number of b-values (n=10-50), (III) diffusion weighting (b-range_small =0-800 up to b-range_large =0-2,180 s/mm²), and (IV) fixation of the diffusion coefficients D_tissue and D_blood was examined. NNLS was evaluated for baseline and pathophysiological conditions, namely increased tubular volume fraction (ITV) and renal fibrosis (10%: grade I, mild) and 30% (grade II, moderate).

Results

NNLS showed the same high degree of reliability as the non-linear LS. MAPE of the tubular volume fraction (f_tubules ) decreased with increasing SNR. Increasing the number of b-values was beneficial for f_tubules precision. Using the b-range_large led to a decrease in MAPE _ftubules compared to b-range_small. The use of a medium b-value range of b=0-1,380 s/mm² improved f_tubules precision, and further b_max increases beyond this range yielded diminishing improvements. Fixing D_blood and D_tissue significantly reduced MAPE _ftubules and provided near perfect distinction between baseline and ITV conditions. Without constraining the number of renal compartments in advance, NNLS was able to detect the (fourth) fibrotic compartment, to differentiate it from the other three diffusion components, and to distinguish between 10% vs. 30% fibrosis.

Conclusions

This work demonstrates the feasibility of NNLS modelling for DWI of the kidney tubule system and shows its potential for examining diffusion compartments associated with renal pathophysiology including ITV fraction and different degrees of fibrosis.

Diffusion Tensor Imaging in early prediction of renal fibrosis in patients with renal disease: Functional and histopathological correlations

AIM

Renal fibrosis (RF) is a well-known marker of chronic kidney disease (CKD) progression. However, renal biopsy is an available tool for evaluation of RF, non-invasive tools are needed not only to detect but also to monitor the progression of fibrosis. The aim of this study is to evaluate the role of diffusion tensor imaging (DTI) in the assessment of renal dysfunction and RF in patients with renal disease.

METHODS

Fifty-six patients with renal disorders and 22 healthy controls were recruited. All participants underwent DTI. Renal biopsy was performed for all patients. Mean renal medullary and cortical fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were compared between patients and healthy controls and correlated to serum creatinine (SCr), estimated glomerular filtration rate (eGFR), 24-h urinary protein (24h-UPRO) and renal histopathological scores.

RESULTS

Cortical FA values were significantly higher (P = .001), while cortical ADC values were significantly lower in the patients' group (P = .002). Cortical FA values positively correlated to SCr (P = .006) and negatively correlated to eGFR (P = .03), while cortical ADC negatively correlated to percentage of sclerotic glomeruli, atrophic tubules and interstitial fibrosis (P = .001 for all variables). Medullary ADC negatively correlated to tubular atrophy (P = .02). The diagnostic performance of DTI for detecting RF was supported by ROC curve. Multiple linear regression analysis revealed that the mean cortex ADC was significantly decreased by 0.199 mg/dL for patients with >50% glomerulosclerosis in renal biopsy.

CONCLUSION

DTI appears to represent a valuable tool for the non-invasive assessment of renal dysfunction and renal fibrosis.

Texture analysis based on quantitative magnetic resonance imaging to assess kidney function: a preliminary study

Background

Magnetic resonance imaging (MRI) has demonstrated its potential in the evaluation of renal function. Texture analysis (TA) is a novel technique to quantify tissue heterogeneity. We aim to investigate the feasibility of using TA based on the apparent diffusion coefficient (ADC), as well as T1 and T2 maps to evaluate renal function.

Methods

Patients with impaired renal function and subjects with a normal renal function who underwent renal diffusion weighted imaging (DWI), as well as T1 and T2 mapping at 3T, were prospectively enrolled. The participants were classified into four groups according to the estimated glomerular filtration rate (eGFR, mL/min/1.73 m²): normal (eGFR ≥90), mildly impaired (60≤ eGFR <90), moderately impaired (30≤ eGFR <60), and severely impaired (eGFR <30) renal function groups. Texture features quantified from the renal cortex or medulla were selected to build classifiers to discriminate different renal function groups by plotting receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Results

In total, 116 candidates were included (94 patients and 22 healthy volunteers, mean age 37.9±14.9 years). There were 46 participants in the normal renal function group, 14 in the mildly impaired renal function group, 27 in the moderately impaired renal function group, and 29 in the severely impaired renal function group. Texture features from the ADC and T1 maps exhibited a good correlation to eGFR. The AUC, sensitivity, specificity, PPV, and NPV to differentiate between the normal and impaired renal function groups were 0.835, 0.792, 0.867, 0.905, and 0.722, respectively; to differentiate between the mildly impaired and moderately impaired groups were 0.937, 0.889, 0.857, 0.923, and 0.800, respectively; and to differentiate between the moderately impaired and severely impaired groups was 0.940, 0.759, 0.889, 0.880, and 0.774, respectively.

Conclusions

TA based on ADC and T1 maps is feasible for evaluating renal function with relatively good accuracy.

Experimental Protocols for MRI Mapping of Renal T1

The water proton longitudinal relaxation time, T₁, is a common and useful MR parameter in nephrology research. Here we provide three step-by-step T₁-mapping protocols suitable for different types of nephrology research. Firstly, we provide a single-slice 2D saturation recovery protocol suitable for studies of global pathology, where whole-kidney coverage is unnecessary. Secondly, we provide an inversion recovery type imaging protocol that may be optimized for specific kidney disease applications. Finally, we also provide imaging protocol for small animal kidney imaging in a clinical scanner.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure.

MRI Mapping of Renal T1: Basic Concept

In renal MRI, measurement of the T₁ relaxation time of water molecules may provide a valuable biomarker for a variety of pathological conditions. Due to its sensitivity to the tissue microenvironment, T₁ has gained substantial interest for noninvasive imaging of renal pathology, including inflammation and fibrosis. In this chapter, we will discuss the basic concept of T₁ mapping and different T₁ measurement techniques and we will provide an overview of emerging preclinical applications of T₁ for imaging of kidney disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Evaluation of Renal Fibrosis by Mapping Histology and Magnetic Resonance Imaging

Background

Renal fibrosis is a key driver of progression in chronic kidney disease (CKD). Recent advances in diagnostic imaging techniques have shown promising results for the noninvasive assessment of renal fibrosis. However, the specificity and accuracy of these techniques are controversial because they indirectly assess renal fibrosis. This limits fibrosis assessment by imaging in CKD for clinical practice. To validate magnetic resonance imaging (MRI) assessment for fibrosis, we derived representative models by mapping histology-proven renal fibrosis and imaging in CKD.

Methods

Ninety-seven adult Chinese CKD participants with histology were studied. The kidney cortex interstitial extracellular matrix volume was calculated by the Aperio ScanScope system using Masson's trichrome slices. The kidney cortex microcirculation was quantitatively assessed by peritubular capillary density using CD34 staining. The imaging techniques included intravoxel incoherent motion diffusion-weighted imaging and magnetic resonance elastography (MRE) imaging. Relevant analyses were performed to evaluate the correlations between MRI parameters and histology variables. Multiple linear regression models were used to describe the relationships between a response variable and other variables. The best-fit lines, which minimize the sum of squared residuals of the multiple linear regression models, were generated.

Results

MRE values were negatively associated with the interstitial extracellular matrix volume (Rho = -0.397, p < 0.001). The best mapping model of extracellular matrix volume with the MRE value and estimated glomerular filtration rate (eGFR) we obtained was as follows: Interstitial extracellular matrix volume = 218.504 - 14.651 × In(MRE) - 18.499 × In(eGFR). DWI-fraction values were positively associated with peritubular capillary density (Rho = 0.472, p < 0.001). The best mapping model of peritubular capillary density with DWI-fraction value and eGFR was as follows: Peritubular capillaries density = 17.914 + 9.403 × (DWI - fraction) + 0.112 × (eGFR).

Conclusions

The study provides histological evidence to support that MRI can effectively evaluate fibrosis in the kidney. These findings picture the graphs of the mapping model from imaging and eGFR into fibrosis, which has significant value for clinical implementation.

Multiparametric MRI assessment of renal structure and function in acute kidney injury and renal recovery

Background

Acute kidney injury (AKI) is associated with a marked increase in mortality as well as subsequent chronic kidney disease (CKD) and end-stage kidney disease. We performed multiparametric magnetic resonance imaging (MRI) with the aim of identifying potential non-invasive MRI markers of renal pathophysiology in AKI and during recovery.

Methods

Nine participants underwent inpatient MRI scans at time of AKI; seven had follow-up scans at 3 months and 1 year following AKI. Multiparametric renal MRI assessed total kidney volume (TKV), renal perfusion using arterial spin labelling, T₁ mapping and blood oxygen level-dependent (BOLD) R₂* mapping.

Results

Serum creatinine concentration had recovered to baseline levels at 1-year post-AKI in all participants. At the time of AKI, participants had increased TKV, increased cortex/medulla T₁ and reduced cortical perfusion compared with the expected ranges in healthy volunteers and people with CKD. TKV and T₁ values decreased over time after AKI and returned to expected values in most but not all patients by 1 year. Cortical perfusion improved to a lesser extent and remained below the expected range in the majority of patients by 1-year post-AKI. BOLD R₂* data showed a non-significant trend to increase over time post-AKI.

Conclusions

We observed a substantial increase in TKV and T₁ during AKI and a marked decrease in cortical perfusion. Despite biochemical recovery at 1-year post-AKI, MRI measures indicated persisting abnormalities in some patients. We propose that such patients may be more likely to have further AKI episodes or progress to CKD and further longitudinal studies are required to investigate this. .

Kidney Allograft Fibrosis: Diagnostic and Therapeutic Strategies

Interstitial fibrosis with tubule atrophy (IF/TA) is the response to virtually any sustained kidney injury and correlates inversely with kidney function and allograft survival. IF/TA is driven by various pathways that include hypoxia, renin-angiotensin-aldosterone system, transforming growth factor (TGF)-β signaling, cellular rejection, inflammation and others. In this review we will focus on key pathways in the progress of renal fibrosis, diagnosis and therapy of allograft fibrosis. This review discusses the role and origin of myofibroblasts as matrix producing cells and therapeutic targets in renal fibrosis with a particular focus on renal allografts. We summarize current trends to use multi-omic approaches to identify new biomarkers for IF/TA detection and to predict allograft survival. Furthermore, we review current imaging strategies that might help to identify and follow-up IF/TA complementary or as alternative to invasive biopsies. We further discuss current clinical trials and therapeutic strategies to treat kidney fibrosis.Supplemental Visual Abstract; http://links.lww.com/TP/C141.

New imaging techniques in AKI

PURPOSE OF REVIEW

Acute kidney injury (AKI) is a common complication in critically ill patients. Understanding the pathophysiology of AKI is essential to guide patient management. Imaging techniques that inform the pathogenesis of AKI in critically ill patients are urgently needed, in both research and ultimately clinical settings. Renal contrast-enhanced ultrasonography (CEUS) and multiparametric MRI appear to be the most promising imaging techniques for exploring the pathophysiological mechanisms involved in AKI.

RECENT FINDINGS

CEUS and MRI can be used to noninvasively and safely evaluate renal macrocirculation and microcirculation and oxygenation in critical ill patients. These techniques show that a decrease in renal blood flow, particularly cortical blood flow, may be observed in septic AKI and may contribute to its development. MRI may be a valuable method to quantify long-term renal damage after AKI that cannot currently be detected using standard clinical approaches.

SUMMARY

CEUS and multiparametric renal MRI are promising imaging techniques but more evidence is needed to show how they can first be more widely used in a research setting to test key hypotheses about the pathophysiology and recovery of AKI, and then ultimately be adopted in clinical practice to guide patient management.

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

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

Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts

The specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Retrospective Distortion and Motion Correction for Free-Breathing DW-MRI of the Kidneys Using Dual-Echo EPI and Slice-to-Volume Registration

BACKGROUND

Diffusion-weighted MRI (DW-MRI) of the kidneys is a technique that provides information about the microstructure of renal tissue without requiring exogenous contrasts such as gadolinium, and it can be used for diagnosis in cases of renal disease and assessing response-to-therapy. However, physiological motion and large geometric distortions due to main B₀ field inhomogeneities degrade the image quality, reduce the accuracy of quantitative imaging markers, and impede their subsequent clinical applicability.

PURPOSE

To retrospectively correct for geometric distortion for free-breathing DW-MRI of the kidneys at 3T, in the presence of a nonstatic distortion field due to breathing and bulk motion.

STUDY TYPE

Prospective.

SUBJECTS

Ten healthy volunteers (ages 29-38, four females).

FIELD STRENGTH/SEQUENCE

3T; DW-MR dual-echo echo-planar imaging (EPI) sequence (10 b-values and 17 directions) and a T₂ volume.

ASSESSMENT

The distortion correction was evaluated subjectively (Likert scale 0-5) and numerically with cross-correlation between the DW images at b = 0 s/mm² and a T₂ volume. The intravoxel incoherent motion (IVIM) and diffusion tensor (DTI) model-fitting performance was evaluated using the root-mean-squared error (nRMSE) and the coefficient of variation (CV%) of their parameters.

STATISTICAL TESTS

Statistical comparisons were done using Wilcoxon tests.

RESULTS

The proposed method improved the Likert scores by 1.1 ± 0.8 (P < 0.05), the cross-correlation with the T₂ reference image by 0.13 ± 0.05 (P < 0.05), and reduced the nRMSE by 0.13 ± 0.03 (P < 0.05) and 0.23 ± 0.06 (P < 0.05) for IVIM and DTI, respectively. The CV% of the IVIM parameters (slow and fast diffusion, and diffusion fraction for IVIM and mean diffusivity, and fractional anisotropy for DTI) was reduced by 2.26 ± 3.98% (P = 6.971 × 10^-2 ), 11.24 ± 26.26% (P = 6.971 × 10^-2 ), 4.12 ± 12.91% (P = 0.101), 3.22 ± 0.55% (P < 0.05), and 2.42 ± 1.15% (P < 0.05).

DATA CONCLUSION

The results indicate that the proposed Di + MoCo method can effectively correct for time-varying geometric distortions and for misalignments due to breathing motion. Consequently, the image quality and precision of the DW-MRI model parameters improved.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 1.

Recommendations for Preclinical Renal MRI: A Comprehensive Open-Access Protocol Collection to Improve Training, Reproducibility, and Comparability of Studies

Renal MRI holds incredible promise for making a quantum leap in improving diagnosis and care of patients with a multitude of diseases, by moving beyond the limitations and restrictions of current routine clinical practice. Clinical and preclinical renal MRI is advancing with ever increasing rapidity, and yet, aside from a few examples of renal MRI in routine use, it is still not good enough. Several roadblocks are still delaying the pace of progress, particularly inefficient education of renal MR researchers, and lack of harmonization of approaches that limits the sharing of results among multiple research groups.Here we aim to address these limitations for preclinical renal MRI (predominantly in small animals), by providing a comprehensive collection of more than 40 publications that will serve as a foundational resource for preclinical renal MRI studies. This includes chapters describing the fundamental principles underlying a variety of renal MRI methods, step-by-step protocols for executing renal MRI studies, and detailed guides for data analysis. This collection will serve as a crucial part of a roadmap toward conducting renal MRI studies in a robust and reproducible way, that will promote the standardization and sharing of data.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.

Quantitative MRI of the liver: Evaluation of extracellular volume fraction and other quantitative parameters in comparison to MR elastography for the assessment of hepatopathy

BACKGROUND

Chronic liver diseases pose a major health problem worldwide, while common tests for diagnosis and monitoring of diffuse hepatopathy have considerable limitations. Preliminary data on the quantification of hepatic extracellular volume fraction (ECV) with magnetic resonance imaging (MRI) for non-invasive assessment of liver fibrosis are encouraging, with ECV having the potential to overcome several of these constraints.

PURPOSE

To clinically evaluate ECV provided by quantitative MRI for assessing the severity of liver disease.

MATERIALS AND METHODS

In this prospective study, multiparametric liver MRI, including T1 mapping and magnetic resonance elastography (MRE), was performed in subjects with and without hepatopathy between November 2018 and October 2019. T1, T2, T2*, proton density fat fraction and stiffness were extracted from parametric maps by regions of interest and ECV was calculated from T1 relaxometries. Serum markers of liver disease were obtained by clinical database research. For correlation analysis, Spearman rank correlation was used. ROC analysis of serum markers and quantitative MRI data for discrimination of liver cirrhosis was performed with MRE as reference standard.

RESULTS

109 participants were enrolled (50.7 ± 16.1 years, 61 men). ECV, T1 and MRE correlated significantly with almost all serum markers of liver disease, with ECV showing the strongest associations (up to r = 0.67 with MELD, p < 0.01). ECV and T1 correlated with MRE (0.75 and 0.73, p < 0.01 each). ECV (AUC 0.89, cutoff 32.2%, sensitivity 85%, specificity 87%) and T1 mapping (AUC 0.85, cutoff 592.5 ms, sensitivity 83%, specificity 75%) featured good performances in detection of liver cirrhosis with only ECV performing significantly superior to model of end stage liver disease (MELD), AST/ALT ratio and international normalized ratio (p < 0.01, respectively).

CONCLUSION

Quantification of hepatic extracellular volume fraction with MRI is suitable for estimating the severity of liver disease when using MRE as the standard of reference. It represents a promising tool for non-invasive assessment of liver fibrosis and cirrhosis.

Quantitative assessment of renal structural and functional changes in chronic kidney disease using multi-parametric magnetic resonance imaging

Background

Multi-parametric magnetic resonance imaging (MRI) provides the potential for a more comprehensive non-invasive assessment of organ structure and function than individual MRI measures, but has not previously been comprehensively evaluated in chronic kidney disease (CKD).

Methods

We performed multi-parametric renal MRI in persons with CKD (n = 22, 61 ± 24 years) who had a renal biopsy and measured glomerular filtration rate (mGFR), and matched healthy volunteers (HV) (n = 22, 61 ± 25 years). Longitudinal relaxation time (T₁), diffusion-weighted imaging, renal blood flow (phase contrast MRI), cortical perfusion (arterial spin labelling) and blood-oxygen-level-dependent relaxation rate (R₂*) were evaluated.

Results

MRI evidenced excellent reproducibility in CKD (coefficient of variation <10%). Significant differences between CKD and HVs included cortical and corticomedullary difference (CMD) in T₁, cortical and medullary apparent diffusion coefficient (ADC), renal artery blood flow and cortical perfusion. MRI measures correlated with kidney function in a combined CKD and HV analysis: estimated GFR correlated with cortical T₁ (r = −0.68), T₁ CMD (r = −0.62), cortical (r = 0.54) and medullary ADC (r = 0.49), renal artery flow (r = 0.78) and cortical perfusion (r = 0.81); log urine protein to creatinine ratio (UPCR) correlated with cortical T₁ (r = 0.61), T₁ CMD (r = 0.61), cortical (r = −0.45) and medullary ADC (r = −0.49), renal artery flow (r = −0.72) and cortical perfusion (r = −0.58). MRI measures (cortical T₁ and ADC, T₁ and ADC CMD, cortical perfusion) differed between low/high interstitial fibrosis groups at 30–40% fibrosis threshold.

Conclusion

Comprehensive multi-parametric MRI is reproducible and correlates well with available measures of renal function and pathology. Larger longitudinal studies are warranted to evaluate its potential to stratify prognosis and response to therapy in CKD.