Renal fat fraction and diffusion tensor imaging in patients with early-stage diabetic nephropathy

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.

Evaluation of renal function in chronic kidney disease (CKD) by mDIXON-Quant and Amide Proton Transfer weighted (APTw) imaging

BACKGROUND

Chronic kidney disease (CKD) is a long-term condition that affects >10% of the adult population worldwide. Noninvasive assessment of renal function has important clinical significance for disease diagnosis and prognosis evaluation.

OBJECTIVE

To explore the value of mDIXON-Quant combined with amide proton transfer weighted (APTw) imaging for accessing renal function in chronic kidney disease (CKD).

MATERIALS AND METHODS

Twenty-two healthy volunteers (HVs) and 30 CKD patients were included in this study, and the CKD patients were divided into the mild CKD (mCKD) group (14 cases) and moderate-to-severe CKD (msCKD) group (16 cases) according to glomerular filtration rate (eGFR). The cortex APT (cAPT), medulla APT (mAPT), cortex R2⁎ (cR2⁎), medulla R2⁎ (mR2⁎), cortex FF (cFF) and medulla FF (mFF) values of the right renal were independently measured by two radiologists. Intra-group correlation coefficient (ICC) test was used to test the inter-observer consistency. The analysis of variance (ANOVA) was used to compare the difference among three groups. Mann-Whitney U test was used to analyze the differences of R2⁎, FF and APT values among the patient and HV groups. Area under the receiver operating characteristic (ROC) curve (AUC) was used to analyze the diagnostic efficiency. The corresponding threshold, sensitivity, and specificity were obtained according to the maximum approximate index. The combined diagnostic efficacy of R2⁎, FF, and APT values was analyzed by binary Logistic regression, and the AUC of combined diagnosis was compared with the AUC of the single parameter by the Delong test.

RESULTS

The cAPT value of the HV, mCKD and msCKD groups increased gradually. The mAPT value and cR2⁎ values of the mCKD and msCKD groups were higher than those of the HV group, while the mFF value of the mCKD group was lower than HV group (all P < 0.05). The cAPT and mAPT values showed good diagnostic efficacy in evaluating different degrees of renal damage, while cR2⁎ and mFF values showed moderate diagnostic efficacy. When combining the APT, R2⁎, and FF values, the diagnostic efficiency was significantly improved.

CONCLUSION

mDIXON-Quant combined APTw imaging can be used for improved diagnosis of CKD.

Intramyocellular Triglyceride Content During the Early Course of Type 1 and Type 2 Diabetes

Intramyocellular lipid content (IMCL) is elevated in insulin-resistant humans, but it changes over time, and relationships with comorbidities remain unclear. We examined IMCL during the initial course of diabetes and its associations with complications. Participants of the German Diabetes Study (GDS) with recent-onset type 1 (n = 132) or type 2 diabetes (n = 139) and glucose-tolerant control subjects (n = 128) underwent 1H-MRS to measure IMCL and muscle volume, whole-body insulin sensitivity (hyperinsulinemic-euglycemic clamps; M-value), and cycling spiroergometry (VO2max). Subgroups underwent the same measurements after 5 years. At baseline, IMCL was ∼30% higher in type 2 diabetes than in other groups independently of age, sex, BMI, and muscle volume. In type 2 diabetes, the M-value was ∼36% and ∼62% lower compared with type 1 diabetes and control subjects, respectively. After 5 years, the M-value decreased by ∼29% in type 1 and ∼13% in type 2 diabetes, whereas IMCL remained unchanged. The correlation between IMCL and M-value in type 2 diabetes at baseline was modulated by VO2max. IMCL also associated with microalbuminuria, the Framingham risk score for cardiovascular disease, and cardiac autonomic neuropathy. Changes in IMCL within 5 years after diagnosis do not mirror the progression of insulin resistance in type 2 diabetes but associate with early diabetes-related complications.

ARTICLE HIGHLIGHTS

Intramyocellular lipid content (IMCL) can be elevated in insulin-resistant humans, but its dynamics and association with comorbidities remain unclear. Independently of age, sex, body mass, and skeletal muscle volume, IMCL is higher in recent-onset type 2, but not type 1 diabetes, and remains unchanged within 5 years, despite worsening insulin resistance. A degree of physical fitness modulates the association between IMCL and insulin sensitivity in type 2 diabetes. Whereas higher IMCL associates with lower insulin sensitivity in people with lower physical fitness, there is no association between IMCL and insulin sensitivity in those with higher degree of physical fitness. IMCL associates with progression of microalbuminuria, cardiovascular disease risk, and cardiac autonomic neuropathy.

The Fatty Kidney and Beyond: A Silent Epidemic

As the prevalence of obesity rises in the United States, so does the incidence of obesity-related kidney disease. Obesity itself is an independent risk factor for chronic kidney disease where the pathophysiology is complex, involving altered hemodynamics, renin-angiotensin-aldosterone system overactivation, and adipokines leading to inflammation and fibrosis. Obesity-related kidney disease comprises both obesity-related glomerulopathy and fatty kidney disease. Obesity-related glomerulopathy is a consequence of glomerular hyperfiltration and often presents clinically with subnephrotic proteinuria and pathologically with glomerulomegaly with or without focal glomerulosclerosis. Fatty kidney disease is the effect of renal ectopic fat contributing to chronic kidney disease. Whether the renal ectopic fat is a distinct clinical entity or a pathologic mechanism contributing to obesity-related glomerulopathy, the treatment paradigm of weight and proteinuria reduction remains the same. We present the pathophysiology behind obesity-related kidney disease, clinical outcomes, and treatment strategies, which include lifestyle interventions, use of renin-angiotensin-aldosterone system inhibitors, glucagon-like peptide 1 receptor agonists, sodium-glucose co-transporter-2 inhibitors, and bariatric surgery. With old and novel therapeutics, we are attempting to stave off the silent epidemic that obesity-related kidney disease is becoming.

Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review

Microvascular changes in diabetes affect the function of several critical organs, such as the kidneys, heart, brain, eye, and skin, among others. The possibility of detecting such changes early enough in order to take appropriate actions renders the development of appropriate tools and techniques an imperative need. To this end, several sensing and imaging techniques have been developed or employed in the assessment of microangiopathy in patients with diabetes. Herein, we present such techniques; we provide insights into their principles of operation while discussing the characteristics that make them appropriate for such use. Finally, apart from already established techniques, we present novel ones with great translational potential, such as optoacoustic technologies, which are expected to enter clinical practice in the foreseeable future.

mDIXON-Quant for differentiation of renal damage degree in patients with chronic kidney disease

Background

Chronic kidney disease (CKD) is a complex syndrome with high morbidity and slow progression. Early stages of CKD are asymptomatic and lack of awareness at this stage allows CKD to progress through to advanced stages. Early detection of CKD is critical for the early intervention and prognosis improvement.

Purpose

To assess the capability of mDIXON-Quant imaging to detect early CKD and evaluate the degree of renal damage in patients with CKD.

Study type

Retrospective.

Population

35 patients with CKD: 18 cases were classifified as the mild renal damage group (group A) and 17 cases were classifified as the moderate to severe renal damage group (group B). 22 healthy volunteers (group C).

Field strength/sequence

A 3.0 T/T1WI, T2WI and mDIXON-Quant sequences.

Assessment

Transverse relaxation rate (R2*) values and fat fraction (FF) values derived from the mDIXON-Quant were calculated and compared among the three groups.

Statistical tests

The intra-class correlation (ICC) test; Chi-square test or Fisher's exact test; Shapiro-Wilk test; Kruskal Wallis test with adjustments for multiplicity (Bonferroni test); Area under the receiver operating characteristic (ROC) curve (AUC). The significance threshold was set at P < 0.05.

Results

Cortex FF values and cortex R2* values were significantly different among the three groups (P=0.028, <0.001), while medulla R2* values and medulla FF values were not (P=0.110, 0.139). Cortex FF values of group B was significantly higher than that of group A (Bonferroni adjusted P = 0.027). Cortex R2* values of group A and group B were both significantly higher than that of group C (Bonferroni adjusted P = 0.012, 0.001). The AUC of cortex FF values in distinguishing group A and group B was 0.766. The diagnostic efficiency of cortex R2* values in distinguishing group A vs. group C and group B vs. group C were 0.788 and 0.829.

Conclusion

The mDIXON-Quant imaging had a potential clinical value in early diagnosis of CKD and assessing the degree of renal damage in CKD patients.

Magnetic Resonance Imaging in Clinical Trials of Diabetic Kidney Disease

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

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

Background

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

Methods

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

Results

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

Discussion

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

Systematic review registration

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

MRI texture-based machine learning models for the evaluation of renal function on different segmentations: a proof-of-concept study

BACKGROUND

To develop and validate an MRI texture-based machine learning model for the noninvasive assessment of renal function.

METHODS

A retrospective study of 174 diabetic patients (training cohort, n = 123; validation cohort, n = 51) who underwent renal MRI scans was included. They were assigned to normal function (n = 71), mild or moderate impairment (n = 69), and severe impairment groups (n = 34) according to renal function. Four methods of kidney segmentation on T2-weighted images (T2WI) were compared, including regions of interest covering all coronal slices (All-K), the largest coronal slices (LC-K), and subregions of the largest coronal slices (TLCO-K and PIZZA-K). The speeded-up robust features (SURF) and support vector machine (SVM) algorithms were used for texture feature extraction and model construction, respectively. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of models.

RESULTS

The models based on LC-K and All-K achieved the nonsignificantly highest accuracy in the classification of renal function (all p values > 0.05). The optimal model yielded high performance in classifying the normal function, mild or moderate impairment, and severe impairment, with an area under the curve of 0.938 (95% confidence interval [CI] 0.935-0.940), 0.919 (95%CI 0.916-0.922), and 0.959 (95%CI 0.956-0.962) in the training cohorts, respectively, as well as 0.802 (95%CI 0.800-0.807), 0.852 (95%CI 0.846-0.857), and 0.863 (95%CI 0.857-0.887) in the validation cohorts, respectively.

CONCLUSION

We developed and internally validated an MRI-based machine-learning model that can accurately evaluate renal function. Once externally validated, this model has the potential to facilitate the monitoring of patients with impaired renal function.

New insights into the role of empagliflozin on diabetic renal tubular lipid accumulation

BACKGROUND

Glucose cotransporter (SGLT) 2 suppression provides potent renal protective effect during diabetic kidney disease (DKD). This work aimed to explore how empagliflozin (EMPA, the selective and strong inhibitor of SGLT2) affected renal lipid deposition among patients undergoing type 2 diabetes mellitus (T2DM), a T2DM mouse model and human renal proximal tubular epithelial (HK-2) cells.

METHODS

This work divided subjects as 3 groups: non-diabetic volunteers, patients treated with metformin and those treated with metformin plus EMPA. In an in vivo study, EMPA was adopted for treating db/db mice that were raised with the basal diet or the high-advanced glycation end products (AGEs) diet. In addition, AGEs and/or EMPA was utilized to treat HK-2 cells in vitro.

RESULTS

Results showed that diabetic patients treated with metformin plus EMPA had lower AGEs levels and renal fat fraction (RFF) than those treated with metformin. Moreover, a significant and positive association was found between AGEs and RFF. Results from the basic study showed that EMPA decreased cholesterol level, tubular lipid droplets, and protein levels related to cholesterol metabolism in AGEs-mediated HK-2 cells, kidneys of db/db mice and those fed with the high-AGEs diet. Additionally, EMPA decreased AGEs levels in serum while inhibiting the expression of receptor of AGEs (RAGE) in vitro and in vivo.

CONCLUSION

EMPA inhibited the AGEs-RAGE pathway, thereby alleviating diabetic renal tubular cholesterol accumulation.

Correlation between Blood Oxygen Level-Dependent Magnetic Resonance Imaging Images and Prognosis of Patients with Multicenter Diabetic Nephropathy on account of Artificial Intelligence Segmentation Algorithm

This study was aimed to analyze the correlation between blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) images and prognosis of patients with diabetic nephropathy (DN) based on artificial intelligence (AI) segmentation algorithm, so as to provide references for diagnosis and treatment as well as prognosis analysis of patients DN. In this study, a kernel function-based fuzzy C-means algorithm (KFCM) model was proposed, and the FCM algorithm based on neighborhood pixel information (BCFCM) and the FCM algorithm based on efficiency improvement (EnFCM) were introduced for comparison to analyze the image segmentation effects of three algorithms. The results showed that the partition coefficient (V_pc) and partition entropy (V_pe) of the KFCM algorithm were 0.801 and 0.602, respectively, which were better than those of the traditional FCM, BCFCM, and EnFCM algorithm. At the same time, the effects of correlation between renal cortex R2∗ (RC-R2∗), renal medulla R2∗ (RM-R2∗), renal cortex D (RC-D), renal medulla D (RM-D) and renal function on the prognosis were compared. The results showed that the correlation coefficients between RC-R2∗, RM-R2∗, RC-D, RM-D and renal function were 0.57, 0.62, 0.49, and 0.38, respectively; among them, RC-R2∗ and RM-R2∗ were negatively correlated to the estimated glomerular filtration rate (eGFR), and the difference between the groups was statistically significant (P <0.05). Among the factors affecting the prognosis of DN patients, the GFR, hemoglobin (Hb), RC-R2∗, RM-R2∗, and RC-D were all related to the prognosis of DN, and the difference between groups was statistically obvious (P <0.05). It suggested that the KFCM algorithm proposed in this study showed the relatively best segmentation effect on BOLD-MRI images for DN patients; an increase in R2∗ indicated a poor prognosis, and an increase in the RC-D value indicated a better prognosis.

In Vivo Renal Lipid Quantification by Accelerated Magnetic Resonance Spectroscopic Imaging at 3T: Feasibility and Reliability Study

A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used for accelerating the acquisition of 48 × 48 voxels (each of 0.25 mL spatial resolution) without respiratory navigation implementations. The data were collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid–water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test–reposition–retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test–retest measurements showed a high degree of repeatability of MRSI-FF (CV = 4.3 ± 2.5%). Additionally, the matching level of the spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ± 6.4%). The MRSI acquisition duration was ~3 min only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.

Capability of intravoxel incoherent motion and diffusion tensor imaging to detect early kidney injury in type 2 diabetes

OBJECTIVES

To prospectively investigate the capability of intravoxel incoherent motion (IVIM) and conventional diffusion tensor imaging (DTI) to identify early kidney function injury in type 2 diabetes.

METHODS

Forty-one diabetes patients (normoalbuminuria: n = 27; microalbuminuria: n = 14) and 28 volunteers were recruited. All participants were examined using DTI and IVIM with 3.0-T MRI. DTI parameters (mean diffusivity [MD], fractional anisotropy [FA]), and IVIM parameters (true diffusion coefficient [D], pseudo-diffusion coefficient [D*], and pseudo-diffusion component fraction [f]) were measured in the renal parenchyma (cortex and medulla) by two experienced radiologists independently. Image features were compared among the groups using separate one-way analyses of variance. Diagnostic performances of various diffusion parameters for predicting diabetic renal damage were compared.

RESULTS

The medullary D and FA values were significantly different among the microalbuminuria subgroup, normoalbuminuria subgroup, and control group (all p < 0.001). In medulla, area under the curve (AUC) values for combined FA and D were significantly higher than single FA (AUC = 0.938, 0.769, respectively; p = 0.003), and the combined AUC of FA and D was numerically higher than that of single D (0.938 vs 0.878, p > 0.05). AUC of combined FA and D was 0.985, not significantly different from individual AUC for FA and D (AUC = 0.909 and 0.952, respectively; all p > 0.05) in differentiating the microalbuminuria subgroup from the control group.

CONCLUSION

IVIM-derived D and DTI-derived FA values were better than other parameters for evaluating early kidney impairment of diabetes. The single indicator FA and D performed as well as the combined diagnostic indicator in the medulla for differentiating the microalbuminuria subgroup from the control group.

KEY POINTS

• We speculated that early renal progression in type 2 diabetes result from restricted tubular flow and kidney tubule dysregulation may precede or at least accompany abnormal glomerular changes. • In medulla, the AUC values of FA and D and the combination of FA and D obtained by comparing the microalbuminuria subgroup with the control group were 0.909, 0.952, and 0.985, respectively. • IVIM-derived D and DTI-derived FA are effective MR biomarkers to evaluate early alterations of the renal function in patients with diabetes.

Renal fat fraction is significantly associated with the risk of chronic kidney disease in patients with type 2 diabetes

BACKGROUNDS

Ectopic fat deposition is closely related to chronic kidney disease (CKD). Currently, there are few population studies that have been conducted to determine the relationship between renal parenchyma fat deposition and the risk of CKD among patients with type 2 diabetes mellitus (T2DM). Therefore, we employed magnetic resonance imaging (MRI) to detect renal parenchyma fat content in individuals with T2DM, expressed as renal fat fraction (FF), to explore whether renal FF is an important risk factor for CKD in patients with T2DM.

METHODS

In this cross-sectional study, 189 subjects with T2DM were enrolled. CKD was defined as the estimated glomerular filtration rate (eGFR)<60 mL/min/1.73m². Measurement of the renal FF was performed on a 3.0-T MRI (MAGNETOM Skyra, Siemens, Erlangen, Germany). Binary logistic regression was used to determine the association between tertiles of renal FF and risk of CKD. Receiver-operator characteristic (ROC) curves were constructed to evaluate the sensitivity and specificity of renal FF in detecting CKD in T2DM patients.

RESULTS

The patients were divided into three groups according to tertiles of the renal FF level (2.498 - 7.434). As renal FF increases, patients tend to be older, and more abdominally obese, with a decreased eGFR (p<0.05). After adjustment for potential confounders, patients in the highest tertile of renal FF had a significantly increased risk of CKD than those in the lowest tertile (odds ratio (OR) = 3.98, 95% confidence interval (CI) = 1.12 - 14.09, p = 0.032), and the area under the ROC curve for this model was 0.836 (0.765-0.907).

CONCLUSIONS

The renal FF is significantly independently associated with CKD in patients with T2DM.

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

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

Role of Thioredoxin-Interacting Protein in Diabetic Fatty Kidney Induced by Advanced Glycation End-Products

Advanced glycation end-products (AGEs) have been identified as the etiological factors associated with the fatty kidney. Thioredoxin-interacting protein (TXNIP) might be a mediator involved in AGE-induced fatty kidney. This study focused on investigating how TXNIP affected the AGE-mediated renal lipid deposition. In an in vivo experiment, the db/db mice injected with the lentiviral vector encoding shRNA targeting TXNIP were given the AIN-76 basal or the high-AGE diet. TXNIP-targeting siRNA-transfected human renal proximal tubular epithelial (HK-2) cells were exposed to AGE-BSA in a study in vitro. The results showed that the silencing of TXNIP reduced tubular lipid droplets and intracellular cholesterol content, as well as upregulated Insig-1 and downregulated HMGCoAR, LDLr, nSREBP-2, and SCAP in the kidneys of the db/db mice, the high-AGE-diet-fed db/db mice, and AGE-BSA-treated HK-2 cells. Furthermore, AGE-BSA enhanced SCAP-SREBP-2 complex formation while promoting their transportation to the Golgi apparatus. However, these could be inhibited by TXNIP silencing in the HK-2 cells. The above findings indicated that TXNIP knockdown mitigated the accumulation of renal tubular lipids in diabetes through the regulation of SCAP, thereby inhibiting the SCAP-SREBP-2 signaling pathway, resulting in reduced cholesterol uptake and synthesis. Therefore, TXNIP might be a potential therapeutic target to treat a diabetic fatty kidney.

Multiparametric MRI analysis for the evaluation of renal function in patients with hyperuricemia: a preliminary study

Background

To investigate the renal dysfunction in patients with hyperuricemia by employing a multiparametric MRI protocol, consisting of quantitative water molecule diffusion, microstructure, microscopic perfusion, and oxygenation measurements in kidneys.

Materials and methods

A total of 48 patients with hyperuricemia (HU) and 22 age-matched healthy control subjects (HC) were enrolled in the study. For each participant, three different functional magnetic resonance imaging (fMRI) sequences were acquired and analyzed, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and blood-oxygen-level-dependent MRI (BOLD). Thereafter, an independent two-sample t-test was applied to discover the significant differences of MRI indices between the hyperuricemia (HU) and HC groups, and the specific potential biomarkers between two subgroups of HU group (asymptomatic hyperuricemia group (AH) and gouty arthritis group (GA)). Further, multivariate logistic regression analyses were performed to classify the AH from the GA group using the MRI indices with significant between-group differences. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was calculated to assess the performance of each MR index for differentiation between the AH and GA groups.

Results

Ten parametric values of the HU group were significantly lower than those of the HC group among the 14 fMRI parameters (P < 0.05). The cortical D, D^*, and f values and medullary D and R2^*values had significant differences between the AH and GA groups (P < 0.05). Combining the cortical D and f values and medullary R2* value gave the best diagnostic efficacy, yielding an AUC, sensitivity, and specificity of 0.967 ± 0.022, 91.67%, and 95.83%, respectively.

Conclusions

A multiparametric MR analysis plays an important role in the evaluation of renal dysfunction in hyperuricemia from multiple perspectives. It could be a promising method for noninvasive detection and identification of the early-stage renal damage induced by hyperuricemia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-021-00675-4.

Renal lipid accumulation induced by high-fat diet regulates glucose homeostasis via sodium-glucose cotransporter 2

AIMS

Visceral lipid accumulation is involved in a variety of physiological aberrations. In the current study, we aimed to investigate whether lipid accumulation had an impact on glucose reabsorption in the kidney.

METHODS

We examined renal lipid content and renal threshold for glucose (RT_G) of each subject. We compared sodium-glucose cotransporter 2 (SGLT2) and sterol regulatory element-binding protein 1c (SREBP1c) levels in kidneys between rats fed with high fat diet (HFD) and normal chow diet. In vitro, HK2 cells were treated with palmitic acid (PA). Intracellular lipid droplet deposition, glucose uptake, SGLT2 and SREBP1c expression were examined.

RESULTS

Renal fat fraction was positively associated with RT_G among the recruited subjects. Moreover, renal lipid content was significantly increased in HFD rats, as well as SGLT2 expression. Accompanied with lipid droplet deposition in HK2 cells, PA stimulated SGLT2 expression and glucose uptake. In addition, after PA treatment, SREBP1c expression was significantly enhanced. However, transfection with siRNA-SREBP1c resulted in significant amelioration of lipid accumulation induced by PA in HK2 cells. Further examination indicated that accompanied with improvement of lipid deposition, SGLT2 expression and glucose uptake were attenuated.

CONCLUSIONS

The results of our study demonstrate the involvement of renal lipid accumulation in glucose homeostasis.

Novel biomarkers of diabetic kidney disease: current status and potential clinical application

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD). Although both albuminuria and glomerular filtration rate (GFR) are well-established diagnostic/prognostic biomarkers of DKD, they have important limitations. There is, thus, increasing quest to find novel biomarkers to identify the disease in an early stage and to improve risk stratification. In this review, we will outline the major pitfalls of currently available markers, describe promising novel biomarkers, and discuss their potential clinical relevance. In particular, we will focus on the importance of recent advancements in multi-omic technologies in the discovery of new DKD biomarkers. In addition, we will provide an update on new emerging approaches to explore renal function and structure, using functional tests and imaging.

Perspectives on the Role of Magnetic Resonance Imaging (MRI) for Noninvasive Evaluation of Diabetic Kidney Disease

Renal magnetic resonance imaging (MRI) techniques are currently in vogue, as they provide in vivo information on renal volume, function, metabolism, perfusion, oxygenation, and microstructural alterations, without the need for exogenous contrast media. New imaging biomarkers can be identified using these tools, which represent a major advance in the understanding and study of the different pathologies affecting the kidney. Diabetic kidney disease (DKD) is one of the most important diseases worldwide due to its high prevalence and impact on public health. However, its multifactorial etiology poses a challenge for both basic and clinical research. Therefore, the use of novel renal MRI techniques is an attractive step forward in the comprehension of DKD, both in its pathogenesis and in its detection and surveillance in the clinical practice. This review article outlines the most promising MRI techniques in the study of DKD, with the purpose of stimulating their clinical translation as possible tools for the diagnosis, follow-up, and monitoring of the clinical impacts of new DKD treatments.

Assessment of kidney function in chronic kidney disease by combining diffusion tensor imaging and total kidney volume

OBJECTIVE

This study aimed to investigate the value and feasibility of combining fractional anisotropy (FA) values from diffusion tensor imaging (DTI) and total kidney volume (TKV) for the assessment of kidney function in chronic kidney disease (CKD).

MATERIALS AND METHODS

Fifty-one patients were included in this study. All MRI examinations were performed with a 3.0 T scanner. DTI was used to measure FA values, and TKV was obtained from DTI and T2-weighted imaging (T2WI). Patients were divided into three groups (mild, moderate, severe) according to eGFR, which was calculated with serum creatinine. Differences in the FA values of the cortex and medulla were analysed among the three groups, and the relationships of FA values, TKV, and the product of the FA values and TKV with eGFR were analysed. Receiver operating characteristic (ROC) curve analysis was used to compare the diagnostic efficiency of the FA values, TKV, and the product of the FA values and TKV for kidney function in different CKD stages.

RESULTS

Medullary FA values (m-FA), TKV, and the product of the m-FA values and TKV (m-FA-TKV) were significantly correlated with eGFR (r = 0.653, 0.685, and 0.797, respectively; all P < 0.001). ROC curve analysis showed that m-FA-TKV exhibited better diagnostic performance than m-FA values (P = 0.022).

CONCLUSION

m-FA-TKV obtained by DTI significantly improves the accuracy of kidney function assessment in CKD patients.

Magnetic resonance diffusion tensor imaging applied to rat model of contrast-induced acute kidney injury

Objectives

In this preclinical investigation, the feasibility of using diffusion tensor imaging (DTI) to study contrast-induced acute kidney injury (CIAKI) is explored, comparing radiographic outcomes with histopathologic and immunohistochemical findings after repeated animal exposures to iodinated contrast agent.

Materials and Methods

Forty-five male wistar rats were allocated to three groups (n = 15 each), each receiving two separate injections 1 day apart: group 1 (iodixanol then saline); group 2 (iodixanol twice); and control group (saline twice). Five rats were then randomly selected from each group at three separate time points (1 h, 24 h, and 120 h) for magnetic resonance imaging (MRI). Upon MRI completion, the animals were sacrificed, examining renal tissue and serum creatinine level. DTI data served to calculate fractional anisotropy (FA) and apparent diffusion coefficient (ADC).

Results

FA values were significantly lower in group 2 than in the others. Compared with controls, FA assessments at 1 h, 24 h, and 120 h after injections commenced were significantly lower in group 2; and ADC was significantly more pronounced at 24 h. Serum creatinine levels at 24 h were markedly elevated in both groups 1 and 2. Pearson correlation analysis revealed significant negative correlations between FA (r = −0.730; p < 0.05) or ADC (r = −0.827; p < 0.05) and tubular injury and between FA (r = −0.563; p < 0.05) or ADC (r = −0.805; p < 0.05) and hypoxia-inducible factor-1α.

Conclusions

Analytic approaches to DTI with better reproducibility should aid in monitoring the early pathophysiologic derangements of CIAKI, thus facilitating timely reversal of the detrimental effects.

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.

Diffusion Tensor Imaging in Rat Models of Preclinical Diabetic Nephropathy: A Preliminary Study

PURPOSE

This study aimed to investigate the value of diffusion tensor imaging to assess renal injury in a rat model of preclinical diabetic nephropathy.

METHODS

Twenty-eight male Sprague Dawley rats were divided into two groups: the normal control (NC) group of 10 rats and the diabetic nephropathy (DN) group of 18 rats. Eight weeks after diabetes induction by streptozotocin, 3.0-T magnetic resonance (MR) imaging (b = 0 and 600 s/mm², 15 diffusion directions) using a 32-channel knee coil was performed. After MR imaging, we measured serum creatinine, and collected double kidney tissues for pathology. The apparent diffusion coefficients(ADC) and fractional anisotropy(FA) values of the renal cortex and medulla were calculated for all kidneys. Physiological parameters, laboratory parameters, and imaging results were compared between the two groups.

RESULTS

All DN group animals developed hyperglycemia, polyuria, and emaciation. Serum creatinine was not significantly different between the groups (P > 0.05). Urinary albumin at 2, 4, and 8 weeks was higher in the DN group than in the NC group but <20 µg/min (P < 0.05). Pathologically, renal damage in the DN rats was observed. The ADC value was significantly increased in DN animals in the cortex (1.75×10^-3mm²/s),medulla(1.53×10^-3mm²/s)compared with NC group(cortex, 1.52×10^-3mm²/s; medulla,1.35×10^-3mm²/s). The FA value was significantly reduced in DN animals in the cortex (0.21),medulla(0.25)compared with NC group(cortex,0.26;medulla,0.3).

CONCLUSIONS

Increased apparent diffusion coefficients and decreased fractional anisotropy values on diffusion tensor imaging were associated with preclinical DN. Diffusion tensor imaging may be useful in early, non-invasive, quantitative detection, and therapy monitoring of DN.

Noninvasive evaluation of early diabetic nephropathy using diffusion kurtosis imaging: an experimental study

OBJECTIVES

To evaluate the value of renal diffusion kurtosis imaging (DKI) in the diagnosis of early diabetic nephropathy (DN) in a rat model.

MATERIALS AND METHODS

Forty male Zucker diabetic fatty rats that spontaneously developed type 2 diabetes mellitus (DM) and 20 age-matched nondiabetic lean Zucker rats were included. Renal DKI scans and histological examinations were performed on the rats in batches at the end of the 4th, 8th, 12th, 16th, and 20th week after DM model was built. Based on renal histopathological appearance, included animals were divided into three groups: a nondiabetic control group, a DM group without DN, and an early DN group. Mean kurtosis (MK) and mean diffusivity (MD) values of renal cortex and medulla were analyzed statistically.

RESULTS

MK values of renal cortex and medulla tended to increase from the control group to the early DN group, respectively, while MD values tended to decrease. The cutoff MD and MK values of renal cortex and medulla showed different values in discriminating early DN from controls. Among them, cutoff MK value of medulla of 0.62 was the best parameter (sensitivity, 93.9%; specificity, 96.4%; and area under the curve, 0.95). For discriminate early DN from DM without DN and DM without DN from controls, cutoff MK value of renal cortex or medulla achieved an area under the curve of 0.76-0.85.

CONCLUSIONS

MR DKI may be valuable for the noninvasive detection of early DN, and MK value might serve as a more sensitive biomarker of early DN than MD value.

KEY POINTS

• In this article, diffusion kurtosis imaging (DKI) was used to detect the changes in the kidneys due to early diabetic nephropathy (DN). • MR DKI may be valuable for the noninvasive detection of early DN. • The mean kurtosis values of renal cortex and medulla might serve as a more sensitive biomarker of early DN than the mean diffusivity values.

DTI-based radiomics signature for the detection of early diabetic kidney damage

OBJECTIVE

To explore whether a radiomics signature based on diffusion tensor imaging (DTI) can detect early kidney damage in diabetic patients.

MATERIALS AND METHODS

Twenty-eight healthy volunteers (group A) and thirty type 2 diabetic patients (group B) with micro-normoalbuminuria, a urinary albumin-to-creatinine ratio (ACR) < 30 mg/g and an estimated glomerular filtration rate (eGFR) of 60-120 mL/(min 1.73 m²) were recruited. Kidney DTI was performed using 1.5T magnetic resonance imaging (MRI).The radiologist manually drew regions of interest (ROI) on the fractional anisotropy (FA) map of the right kidney ROI including the cortex and medulla. The texture features of the ROIs were extracted using MaZda software. The Fisher coefficient, mutual information (MI), and probability of classification error and average correlation coefficient (POE + ACC) methods were used to select the texture features. The most valuable texture features were further selected by the least absolute shrinkage and selection operator (LASSO) algorithm. A LASSO regression model based on the radiomics signature was established. The diagnostic performance of the model for detecting early diabetic kidney changes was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). Empower (R), R, and MedCalc15.8 software were used for statistical analysis RESULTS: A total of 279 texture features were extracted from ROI of the kidney, and 30 most valuable texture features were selected from groups A and B using MaZda software. After LASSO-logistic regression, a diagnostic model of diabetic kidney damage based on texture features was established. Model discrimination evaluation: AUC = 0.882 (0.770 ± 0.952). Model calibration evaluation: Hosmer-Lemeshow X2 = 5.3611, P = 0.7184, P > 0.05, the model has good calibration.

CONCLUSION

The texture features based on DTI could play a promising role in detecting early diabetic kidney damage.

21st Century Advances in Multimodality Imaging of Obesity for Care of the Cardiovascular Patient

Although obesity is typically defined by body mass index criteria, this does not differentiate true body fatness, as this includes both body fat and muscle. Therefore, other fat depots may better define cardiometabolic and cardiovascular disease (CVD) risk imposed by obesity. Data from translational, epidemiological, and clinical studies over the past 3 decades have clearly demonstrated that accumulation of adiposity in the abdominal viscera and within tissue depots lacking physiological adipose tissue storage capacity (termed "ectopic fat") is strongly associated with the development of a clinical syndrome characterized by atherogenic dyslipidemia, hyperinsulinemia/glucose intolerance/type 2 diabetes mellitus, hypertension, atherosclerosis, and abnormal cardiac remodeling and heart failure. This state-of-the-art paper discusses the impact of various body fat depots on cardiometabolic parameters and CVD risk. Specifically, it reviews novel and emerging imaging techniques to evaluate adiposity and the risk of cardiometabolic diseases and CVD.

Crescent-Like Lesions as an Early Signature of Nephropathy in a Rat Model of Prediabetes Induced by a Hypercaloric Diet

Diabetic nephropathy (DN) is a major microvascular complication of diabetes. Obesity and hyperlipidemia, fueled by unhealthy food habits, are risk factors to glomerular filtration rate (GFR) decline and DN progression. Several studies recommend that diabetic patients should be screened early (in prediabetes) for kidney disease, in order to prevent advanced stages, for whom the current interventions are clearly inefficient. This ambition greatly depends on the existence of accurate early biomarkers and novel molecular targets, which only may arise with a more thorough knowledge of disease pathophysiology. We used a rat model of prediabetes induced by 23 weeks of high-sugar/high-fat (HSuHF) diet to characterize the phenotype of early renal dysfunction and injury. When compared with the control animals, HSuHF-treated rats displayed a metabolic phenotype compatible with obese prediabetes, displaying impaired glucose tolerance and insulin sensitivity, along with hypertriglyceridemia, and lipid peroxidation. Despite unchanged creatinine levels, the prediabetic animals presented glomerular crescent-like lesions, accompanied by increased kidney Oil-Red-O staining, triglycerides content and mRNA expression of IL-6 and iNOS. This model of HSuHF-induced prediabetes can be a useful tool to study early features of DN, namely crescent-like lesions, an early signature that deserves in-depth elucidation.

Renal and renal sinus fat volumes as quantified by magnetic resonance imaging in subjects with prediabetes, diabetes, and normal glucose tolerance

Purpose

We hypothesize that MRI-based renal compartment volumes, particularly renal sinus fat as locally and potentially independently acting perivascular fat tissue, increase with glucose intolerance. We therefore analyze the distribution of renal volumes in individuals with normal glucose levels and prediabetic and diabetic individuals and investigate potential associations with other typical cardiometabolic biomarkers.

Material and methods

The sample comprised N = 366 participants who were either normoglycemic (N = 230), had prediabetes (N = 87) or diabetes (N = 49), as determined by Oral Glucose Tolerance Test. Other covariates were obtained by standardized measurements and interviews. Whole-body MR measurements were performed on a 3 Tesla scanner. For assessment of the kidneys, a coronal T1w dual-echo Dixon and a coronal T2w single shot fast spin echo sequence were employed. Stepwise semi-automated segmentation of the kidneys on the Dixon-sequences was based on thresholding and geometric assumptions generating volumes for the kidneys and sinus fat. Inter- and intra-reader variability were determined on a subset of 40 subjects. Associations between glycemic status and renal volumes were evaluated by linear regression models, adjusted for other potential confounding variables. Furthermore, the association of renal volumes with visceral adipose tissue was assessed by linear regression models and Pearson’s correlation coefficient.

Results

Renal volume, renal sinus volume and renal sinus fat increased gradually from normoglycemic controls to individuals with prediabetes to individuals with diabetes (renal volume: 280.3±64.7 ml vs 303.7±67.4 ml vs 320.6±77.7ml, respectively, p < 0.001). After adjustment for age and sex, prediabetes and diabetes were significantly associated to increased renal volume, sinus volume (e.g. β_Prediabetes = 10.1, 95% CI: [6.5, 13.7]; p<0.01, β_Diabetes = 11.86, 95% CI: [7.2, 16.5]; p<0.01) and sinus fat (e.g. β_Prediabetes = 7.13, 95% CI: [4.5, 9.8]; p<0.001, β_Diabetes = 7.34, 95% CI: [4.0, 10.7]; p<0.001). Associations attenuated after adjustment for additional confounders were only significant for prediabetes and sinus volume (ß = 4.0 95% CI [0.4, 7.6]; p<0.05). Hypertension was significantly associated with increased sinus volume (β = 3.7, 95% CI: [0.4, 7.0; p<0.05]) and absolute sinus fat volume (β = 3.0, 95% CI: [0.7, 5.3]; p<0.05). GFR and all renal volumes were significantly associated as well as urine creatinine levels and renal sinus volume (β = 1.6, 95% CI: [0.1, 2.9]; p<0.05).

Conclusion

Renal volume and particularly renal sinus fat volume already increases significantly in prediabetic subjects and is significantly associated with VAT. This shows, that renal sinus fat is a perivascular adipose tissue, which early undergoes changes in the development of metabolic disease. Our findings underpin that renal sinus fat is a link between metabolic disease and associated chronic kidney disease, making it a potential imaging biomarker when assessing perivascular adipose tissue.

Evaluation of salivary gland fat fraction values in patients with primary Sjögren's syndrome by mDIXON quant imaging: Initial findings

PURPOSE

To explore the role of salivary fat fraction (FF) values in evaluating patients with primary Sjögren's syndrome (pSS).

MATERIAL AND METHOD

A total of 28 patients with pSS, ten patients with suspected pSS, and 28 volunteers were enrolled. The FF values of the parotid and submandibular glands were generated from mDIXON Quant. A one-way analysis of variance was used to compare the FF values among the groups. A receiver-operating characteristic analysis was applied to assess the diagnostic performance of the parotid and submandibular FF values in distinguishing patients with pSS from non-pSS subjects. In particular, we focused on distinguishing patients with grade 0 pSS from those with suspected pSS.

RESULTS

The parotid and submandibular mean FF value of patients with pSS was significantly higher than that of healthy volunteers. The submandibular mean FF value of patients with pSS was higher than those suspected ones. Submandibular FF value performed better than parotid FF value in differentiating patients with pSS from those non-pSS subjects (area under the curve [AUC] = 0.927 vs. 0.734), patients with pSS from patients with suspected pSS (AUC = 0.907 vs. 0.725). This value also performed better at distinguishing patients with grade 0 pSS from those patients with suspected pSS (AUC = 0.925 vs. 0.783).

CONCLUSIONS

The salivary gland FF value, especially the submandibular gland FF value, distinguished patients with pSS from those patients with suspected pSS and healthy volunteers.

Molecular imaging of diabetes and diabetic complications: Beyond pancreatic β-cell targeting

Diabetes is a chronic non-communicable disease affecting over 400 million people worldwide. Diabetic patients are at a high risk of various complications, such as cardiovascular, renal, and other diseases. The pathogenesis of diabetes (both type 1 and type 2 diabetes) is associated with a functional impairment of pancreatic β-cells. Consequently, most efforts to manage and prevent diabetes have focused on preserving β-cells and their function. Advances in imaging techniques, such as magnetic resonance imaging, magnetic resonance spectroscopy, positron emission tomography, and single-photon-emission computed tomography, have enabled noninvasive and quantitative detection and characterization of the population and function of β-cells in vivo. These advantages aid in defining and monitoring the progress of diabetes and determining the efficacy of anti-diabetic therapies. Beyond β-cell targeting, molecular imaging of biomarkers associated with the development of diabetes, e.g., lymphocyte infiltration, insulitis, and metabolic changes, may also be a promising strategy for early detection of diabetes, monitoring its progression, and occurrence of complications, as well as facilitating exploration of new therapeutic interventions. Moreover, molecular imaging of glucose uptake, production and excretion in specified tissues is critical for understanding the pathogenesis of diabetes. In the current review, we summarize and discuss recent advances in noninvasive imaging technologies for imaging of biomarkers beyond β-cells for early diagnosis of diabetes, investigation of glucose metabolism, and precise diagnosis and monitoring of diabetic complications for better management of diabetic patients.

In vivo evaluation of early renal damage in type 2 diabetic patients on 3.0 T MR diffusion tensor imaging

AIM

To investigate the utility of renal diffusion tensor imaging (DTI) to detect early renal damage in patients with type 2 diabetes.

METHODS

Twenty-six diabetic patients (12 with microalbuminuria (MAU), and 14 with normoalbuminuria) and fourteen healthy volunteers were prospectively included in this study. Renal DTI on 3.0 T MR was performed, and estimated glomerular filtration rate (eGFR) was recorded for each subject. Mean cortical and medullary fractional anisotropy (FA) values were calculated by placing multiple representative regions of interest. Mean FA values were statistically compared among groups. Correlations between FA values and eGFR were evaluated.

RESULTS

Both cortical and medullary FA were significantly reduced in diabetic patients compared to healthy controls (0.403 ± 0.064 vs 0.463 ± 0.047, P = 0.004, and 0.556 ± 0.084 vs 0.645 ± 0.076, P = 0.002, respectively). Cortical FA was significantly lower in diabetic patients with NAU than healthy controls (0.412 ± 0.068 vs 0.463 ± 0.047, P = 0.02). Medullary FA in diabetic patients with NAU and healthy controls were similar (0.582 ± 0.096 vs 0.645 ± 0.076, P = 0.06). Both cortical FA and medullary FA correlated with eGFR (r = 0.382, P = 0.015 and r = 0.552, P = 0.000, respectively).

CONCLUSION

FA of renal parenchyma on DTI might serve as a more sensitive biomarker of early diabetic nephropathy than MAU.

Renal Functional MRI and Its Application

Renal function varies according to the nature and stage of diseases. Renal functional magnetic resonance imaging (fMRI), a technique considered superior to the most common method used to estimate the glomerular filtration rate, allows for noninvasive, accurate measurements of renal structures and functions in both animals and humans. It has become increasingly prevalent in research and clinical applications. In recent years, renal fMRI has developed rapidly with progress in MRI hardware and emerging postprocessing algorithms. Function-related imaging markers can be acquired via renal fMRI, encompassing water molecular diffusion, perfusion, and oxygenation. This review focuses on the progression and challenges of the main renal fMRI methods, including dynamic contrast-enhanced MRI, blood oxygen level-dependent MRI, diffusion-weighted imaging, diffusion tensor imaging, arterial spin labeling, fat fraction imaging, and their recent clinical applications.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:863-881.