Our study aims to determine the patterns of renal oxygenation changes and microstructural changes by BOLD and DTI with deteriorating kidney function in patients with diabetic kidney disease (DKD).

Seventy-two patients with type 2 diabetes mellitus (DM) and twenty healthy controls (HCs) underwent laboratory examinations, and renal BOLD and DTI images were obtained on a 3T-MRI machine. R2^∗, fractional anisotropy (FA), and average diffusion coefficient (ADC) values were evaluated. DM patients were divided into three subgroups (Group-DI/DII/DIII, based on urinary albumin-creatinine ratio (UACR)) and a nondiabetic kidney disease group (Group-NDKD). D-value and MCR of R2^∗ and FA were proposed to evaluate the differentiation between medulla and cortex of the individual kidney among HCs and three subgroups for reducing individual differences. Comparisons were made between NDKD and kidney function-matched DKD patients. Correlations between MRI parameters and renal clinical indices were analyzed.

Compared with Group-HC/DI, medullary R2^∗ and FA values were significantly different in Group-DII/III. The D-value of R2^∗ and FA in Group-III were significantly smaller than that in Group-HC. However, only MCR of R2^∗ in Group-III was significantly smaller than that in HCs. Medullary R2^∗ and FA were negatively associated with serum creatinine (SCr) and cystatin C (Cys C) and positively associated with eGFR.

With renal function declining, BOLD and DTI could capture alterations including the first rising and then falling medullary R2^∗, continuously declining medullary FA, and apparent cortex-medullary differentiation in DKD patients. The MRI parameters showed renal changes accompanied by varying degrees of albuminuria, sharing common involvement in DKD and NDKD patients, but it was hard to distinguish between them. BOLD seemed more sensitive than DTI in identifying renal cortex-medullary differentiation.

• cartilage
• diffusion tensor imaging (DTI)
• knee
• tractography

• acute kidney injury
• diffusion-weighed magnetic resonance imaging
• ex vivo kidneys
• tubular lumen
• tubules

• distortion correction
• diffusion imaging
• reversed gradient

• Adult
• Diabetic Nephropathies/diagnostic imaging
• Diffusion Tensor Imaging/methods
• Feasibility Studies
• Humans
• Image Interpretation, Computer-Assisted/methods
• Kidney/diagnostic imaging
• Middle Aged
• Young Adult

• P41 EB017183 NIBIB NIH HHS
• R01 CA245671 NCI NIH HHS

• apparent diffusion coefficient
• diabetic nephropathy
• diffusion tensor imaging
• fractional anisotropy
• kidney

• Animals
• Anisotropy
• Diabetes Mellitus, Experimental/complications
• Diabetes Mellitus, Type 2/complications
• Diabetic Nephropathies/diagnostic imaging
• Diabetic Nephropathies/etiology
• Diabetic Nephropathies/pathology
• Diffusion Tensor Imaging/methods
• Male
• Rats
• Rats, Sprague-Dawley

• diffusion
• fractional anisotropy
• kidney
• microscopic anisotropy
• spherical tensor encoding
• tensor-valued diffusion encoding

• Adult
• Anisotropy
• Artifacts
• Diffusion Magnetic Resonance Imaging
• Female
• Healthy Volunteers
• Humans
• Image Processing, Computer-Assisted/methods
• Kidney/diagnostic imaging
• Kidney Medulla/diagnostic imaging
• Male
• Motion

• P41 EB015902 NIBIB NIH HHS

Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization.

Reported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ≥ 75% agreement.

Correlations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65–74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided.

The consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field.

The online version of this article (10.1007/s10334-019-00790-y) contains supplementary material, which is available to authorized users.

• ADC
• Biomarker
• DTI
• DWI
• IVIM

Diffusion tensor imaging (DTI) is particularly suitable for kidney studies due to tubules, collector ducts and blood vessels in the medulla that produce spatially restricted diffusion of water molecules, thus reflecting the high grade of anisotropy detectable by DTI. Kidney DTI is still a challenging technique where the off-resonance susceptibility artefacts and subject motion can severely affect the reproducibility of results. The aim of this study is to design a reliable processing pipeline by assessing different image processing approaches in terms of reproducibility and image artefacts correction. The results of four different processing pipelines (eddy: correction of eddy-currents and motion between DTI volume; eddy-s2v: eddy and within DTI volume motion correction; topup: eddy and geometric distortion correction; topup-s2v: topup and within DTI volume motion correction) are compared in terms of reproducibility by test-retest analysis in 14 healthy subjects. Within-subject coefficient of variation (wsCV) and intra-class correlation coefficient (ICC) are measured to assess the reproducibility and Dice similarity index is evaluated for the spatial alignment between DTI and anatomical images. Topup-s2v pipeline provides highest reproducibility (wsCV = 0.053, ICC = 0.814) and best correction of image distortion (Dice = 0.83). This study definitely provides a recipe for data processing, enabling for a clinical suitability of kidney DTI.

• Clear cell Renal cell carcinoma
• diffusion kurtosis tensor imaging
• histopathologic correlation

• DTI
• IVIM
• diffusion MRI
• diffusion tensor imaging
• kidneys
• tractography

• Adult
• Computer Simulation
• Diffusion Tensor Imaging/methods
• Female
• Humans
• Image Enhancement/methods
• Image Interpretation, Computer-Assisted/methods
• Imaging, Three-Dimensional/methods
• Kidney/anatomy & histology
• Kidney/diagnostic imaging
• Kidney/physiology
• Male
• Middle Aged
• Models, Biological
• Motion
• Reproducibility of Results
• Sensitivity and Specificity

Functional magnetic resonance imaging (MRI) provided critical functional information in addition to the anatomic profiles offered by conventional MRI, and has been enormously used in the initial diagnosis and followed evaluation of various diseases. Diffusion tensor imaging (DTI) is a newly developed and advanced technique that measures the diffusion properties including both diffusion motion and its direction in situ, and has been extensively applied in central nerve system with acknowledged success. Technical advances have enabled DTI in abdominal and pelvic organs. Its application is increasing, yet remains less understood. A systematic overview of clinical application of DTI in abdominal and pelvic organs such as liver, pancreas, kidneys, prostate, uterus, etc., is therefore presented. Exploration of techniques with less artifacts and more normative post-processing enabled generally satisfactory image quality and repeatability of measurement. DTI appears to be more valuable in the evaluation of diffused diseases of organs with highly directionally arranged structures, such as the assessment of function impairment of native and transplanted kidneys. However, the utility of DTI to diagnose focal lesions, such as liver mass, pancreatic and prostate tumor, remains limited. Besides, diffusion of different layers of the uterus and the fiber structure disruption can be depicted by DTI. Finally, a discussion of future directions of research is given. The underlying heterogeneous pathologic conditions of certain diseases need to be further differentiated, and it is suggested that DTI parameters might potentially depict certain pathologic characterization such as cell density. Nevertheless, DTI should be better integrated into the current multi-modality evaluation in clinical practice.

• Functional magnetic resonance imaging
• Diffusion tensor imaging
• Abdomen
• Pelvis
• Kidney

• Diffusionstensorbildgebung
• Echo Planar Imaging
• Echoplanar Bildgebung
• Intravoxel Incoherent Motion
• Niere
• Turbo Spin Echo
• diffusion tensor imaging
• intravoxel incoherent motion
• kidney

• Diffusion
• fibrosis
• kidney
• kurtosis

• Algorithms
• Animals
• Diffusion Magnetic Resonance Imaging/methods
• Humans
• Image Enhancement/methods
• Image Interpretation, Computer-Assisted/methods
• Kidney/diagnostic imaging
• Kidney/pathology
• Mice
• Mice, Transgenic
• Reproducibility of Results
• Sensitivity and Specificity

• R01 EB012874 NIBIB NIH HHS

• Akaike information criterion
• biophysical mechanisms of MR diffusion
• diffusion tensor imaging
• flow fraction
• intravoxel incoherent motion
• renal

• Algorithms
• Diffusion Magnetic Resonance Imaging/methods
• Humans
• Image Enhancement/methods
• Image Interpretation, Computer-Assisted/methods
• Imaging, Three-Dimensional/methods
• Kidney/anatomy & histology
• Multimodal Imaging/methods
• Reproducibility of Results
• Sensitivity and Specificity

Brief bursts of RF noise during MR data acquisition (“k‐space spikes”) cause disruptive image artifacts, manifesting as stripes overlaid on the image. RF noise is often related to hardware problems, including vibrations during gradient‐heavy sequences, such as diffusion‐weighted imaging. In this study, we present an application of the Robust Principal Component Analysis (RPCA) algorithm to remove spike noise from k‐space. Methods: Corrupted k‐space matrices were decomposed into their low‐rank and sparse components using the RPCA algorithm, such that spikes were contained within the sparse component and artifact‐free k‐space data remained in the low‐rank component. Automated center refilling was applied to keep the peaked central cluster of k‐space from misclassification in the sparse component. Results: This algorithm was demonstrated to effectively remove k‐space spikes from four data types under conditions generating spikes: (i) mouse heart T₁ mapping, (ii) mouse heart cine imaging, (iii) human kidney diffusion tensor imaging (DTI) data, and (iv) human brain DTI data. Myocardial T₁ values changed by 86.1 ± 171 ms following despiking, and fractional anisotropy values were recovered following despiking of DTI data. Conclusion: The RPCA despiking algorithm will be a valuable postprocessing method for retrospectively removing stripe artifacts without affecting the underlying signal of interest. Magn Reson Med 75:2517–2525, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

• robust principal component analysis
• spike noise
• stripe artifact