Diffusion-weighted imaging in the assessment of renal function in patients with diabetes mellitus type 2

Mrdanin, Tijana; Nikolić, Olivera; Molnar, Una; Mitrović, Milena; Till, Viktor

doi:10.1007/s10334-020-00869-x

Cited by 11 publications

(8 citation statements)

References 44 publications

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“…In the same year, Inoue et al compared 50 diabetic people with different levels of eGFR and albuminuria to 76 healthy controls and found that the cortical ADC was lower in patients with DKD, and correlated linearly with the eGFR: the lower the eGFR, the lower the ADC [37] More recently, Cakmak et al [45] confirmed that ADC correlated strongly with the clinical categories of DKD in 78 T2D individuals with DKD. A substantial association between ADC and eGFR has also been seen in several other studies [46,47]. Moreover, diabetic murine models demonstrated a direct relationship between ADC and interstitial fibrosis [48,49].…”

Section: Dwi-mrisupporting

confidence: 65%

Magnetic Resonance Imaging to Diagnose and Predict the Outcome of Diabetic Kidney Disease—Where Do We Stand?

Pruijm

Aslam

Milani

et al. 2022

Kidney and Dialysis

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Diabetic kidney disease (DKD) is a major public health problem and its incidence is rising. The disease course is unpredictable with classic biomarkers, and the search for new tools to predict adverse renal outcomes is ongoing. Renal magnetic resonance imaging (MRI) now enables the quantification of metabolic and microscopic properties of the kidneys such as single-kidney, cortical and medullary blood flow, and renal tissue oxygenation and fibrosis, without the use of contrast media. A rapidly increasing number of studies show that these techniques can identify early kidney damage in patients with DKD, and possibly predict renal outcome. This review provides an overview of the currently most frequently used techniques, a summary of the results of some recent studies, and our view on their potential applications, as well as the hurdles to be overcome for the integration of these techniques into the clinical care of patients with DKD.

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Section: Dwi-mrisupporting

confidence: 65%

Magnetic Resonance Imaging to Diagnose and Predict the Outcome of Diabetic Kidney Disease—Where Do We Stand?

Pruijm

Aslam

Milani

et al. 2022

Kidney and Dialysis

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“…Lu et al reported lower medullary FA and ADC in diabetics subjects compared to controls [76]. The medullary FA was also correlated with kidney function [76,77], suggesting that DTI-MRI allows evaluating renal fibrosis in DKD. These findings were recently confirmed in patients with mild DKD, including the ability to detect renal lipid deposition [78], and in diabetic murine models, finding association with histopathological changes of interstitial fibrosis and glomerulosclerosis [79][80][81].…”

Section: Dwi/dtimentioning

confidence: 98%

“…Inoue et al analyzed almost 50 diabetic subjects with all categories of GFR and albuminuria, compared with 76 healthy controls, concluding that ADC allows accurately detecting tubulointerstitial alterations at the renal cortex level [68]. Further studies demonstrated a significant correlation between ADC and GFR [77,83]. In turn, Çakmak et al observed, in 78 T2D subjects with DKD aged between 26 and 70 years, that ADC showed significant correlation with clinical categories of DKD [84].…”

Section: Dwi/dtimentioning

confidence: 99%

“…Another study, also in T2D but with low-moderate CKD risk (G1, A1-A2), showed that the combination of ADC with FA values is able to yield information about renal involvement even in early DKD [86]. However, FA seems to be more sensitive to detect these alterations [77]. More recently, another study in T2D concluded that both parameters (ADC and FA) are able to differentiate between healthy and diabetic volunteers, as well as predict the presence of severe albuminuria and correlate with kidney injury biomarkers, such as serum creatinine, urinary TGF-β1, and N-acetyl-beta-D-glucosaminidase [87].…”

Section: Dwi/dtimentioning

confidence: 99%

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

Mora-Gutiérrez

Fernández‐Seara

Echeverria‐Chasco

et al. 2021

JCM

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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.

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“…Functional MRI scan techniques, diffusion tensor imaging (DTI), and diffusion-weighted imaging (DWI) may provide early noninvasive detection of functional changes in the kidney by following the diffusion of water molecules ( 6 ). A multitude of previous studies have proven the correlation of DTI and DWI quantitative parameters (fractional anisotropy (FA) and apparent diffusion coefficient (ADC)) with estimated glomerular filtration rate (eGFR), glomerulosclerosis, tubular damage, and interstitial fibrosis ( 7 – 10 ) due to which these parameters could be useful for the evaluation of diabetic patients with early DN ( 11 ).…”

Section: Introductionmentioning

confidence: 99%

Application of MR Imaging Features in Differentiation of Renal Changes in Patients With Stage III Type 2 Diabetic Nephropathy and Normal Subjects

Huang

Fan

et al. 2022

Front. Endocrinol.

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ObjectiveThe objective of the study was to explore the value of MRI texture features based on T1WI, T2-FS and diffusion-weighted imaging (DWI) in differentiation of renal changes in patients with stage III type 2 diabetic nephropathy (DN) and normal subjects.Materials and MethodsA retrospective analysis was performed to analyze 44 healthy volunteers (group A) and 40 patients with stage III type 2 diabetic nephropathy (group B) with microalbuminuria. Urinary albumin to creatinine ratio (ACR) <30 mg/g, estimated glomerular filtration rate (eGFR) in the range of 60–120 ml/(min 1.73 m2), and randomly divided into primary cohort and test cohort. Conventional MRI and DWI of kidney were performed using 1.5 T magnetic resonance imaging (MRI). The outline of the renal parenchyma was manually labeled in fat-suppressed T2-weighted imaging (FS-T2WI), and PyRadiomics was used to extract radiomics features. The radiomics features were then selected by the least absolute shrinkage and selection operator (LASSO) method.ResultsThere was a significant difference in sex and body mass index (BMI) (P <0.05) in the primary cohort, with no significant difference in age. In the final results, the wavelet and Laplacian–Gaussian filtering are used to extract 1,892 image features from the original T1WI image, and the LASSO algorithm is used for selection. One first-order feature and six texture features are selected through 10 cross-validations. In the mass, 1,638 imaging extracts features from the original T2WI image.1 first-order feature and 5 texture features were selected. A total of 1,241 imaging features were extracted from the original ADC images, and 5 texture features were selected. Using LASSO-Logistic regression analysis, 10 features were selected for modeling, and a combined diagnosis model of diabetic nephropathy based on texture features was established. The average unit cost in the logistic regression model was 0.98, the 95% confidence interval for the predictive efficacy was 0.9486–1.0, specificity 0.97 and precision 0.93, particularly. ROC curves also revealed that the model could distinguish with high sensitivity of at least 92%.ConclusionIn consequence, the texture features based on MR have broad application prospects in the early detection of DN as a relatively simple and noninvasive tool without contrast media administration.

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Diffusion-weighted imaging in the assessment of renal function in patients with diabetes mellitus type 2

Cited by 11 publications

References 44 publications

Magnetic Resonance Imaging to Diagnose and Predict the Outcome of Diabetic Kidney Disease—Where Do We Stand?

Magnetic Resonance Imaging to Diagnose and Predict the Outcome of Diabetic Kidney Disease—Where Do We Stand?

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

Application of MR Imaging Features in Differentiation of Renal Changes in Patients With Stage III Type 2 Diabetic Nephropathy and Normal Subjects

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