Diffusion‐Weighted imaging and diffusion tensor imaging detect delayed graft function and correlate with allograft fibrosis in patients early after kidney transplantation

Hueper, Katja; Khalifa, Abedalrazag; Bräsen, Jan Hinrich; Chieu, Van Dai Vo; Gutberlet, Marcel; Wintterle, Sabine; Lehner, Frank; Richter, Nicolas; Peperhove, Matti; Tewes, Susanne; Weber, Kristina; Haller, Hermann; Wacker, Frank; Gwinner, Wilfried; Gueler, Faikah; Hartung, Dagmar

doi:10.1002/jmri.25158

Cited by 89 publications

(94 citation statements)

References 37 publications

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“…The tractography‐based parameters of all models are most similar to those of the medulla, which is in agreement with the widely accepted belief that diffusion anisotropy originates in the radially oriented structures in the medulla 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 27. However, tract‐based FA is significantly higher than ROI‐based FA in the medulla.…”

Section: Discussionsupporting

confidence: 85%

“…The higher diffusion anisotropy is usually attributed to the radial organization of tubules and vasculature in the renal pyramids 1, 4, 5, 6, 7, 8, 9, 11. In addition, it has been shown that it is possible to differentiate between healthy and diseased tissue using diffusion tensor MRI parameters MD and FA, for example, in follow‐up of kidney transplants12, 13 and in the early detection of diabetic nephropathy 14…”

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confidence: 99%

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Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

Baalen

Leemans

Dik

et al. 2016

J. Magn. Reson. Imaging

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PurposeTo evaluate if a three‐component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue.Materials and MethodsTen healthy volunteers were examined at 3T, with T 2‐weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono‐, bi‐, and triexponential fit parameters (D 1, D 2, D 3, f fast2, f fast3, and f interm) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R2 ( normalRadj2) and the Shapiro‐Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared.ResultsFitting the diffusion signal was feasible for all models. The three‐component model was best able to describe fast signal decay at low b values (b < 50), which was most apparent in normalRadj2 of the ROI containing high diffusion signals (ROIrest), which was 0.42 ± 0.14, 0.61 ± 0.11, 0.77 ± 0.09, and 0.81 ± 0.08 for DTI, one‐, two‐, and three‐component models, respectively, and in visual comparison of the fitted and measured S0. None of the models showed significant differences (P > 0.05) between the diffusion constant of the medulla and cortex, whereas the f fast component of the two and three‐component models were significantly different (P < 0.001).ConclusionTriexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information. Level of Evidence: 2 Technical Efficacy: Stage 1J. MAGN. RESON. IMAGING 2017;46:228–239

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Section: Discussionsupporting

confidence: 85%

mentioning

confidence: 99%

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

Baalen

Leemans

Dik

et al. 2016

J. Magn. Reson. Imaging

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“…Several studies from the research group of Hueper et al, using a kidney transplantation animal model, have shown promising results for the use of MR after transplantation [16][17][18][19]. This same research group and several others have initiated studies to translate these outcomes to the clinical setting, showing significant associations between renal allograft function and several MRI sequences in small and heterogeneous cohorts [20][21][22][23][24]. These outcomes have not yet been validated in a larger and more homogenous population of renal transplant recipients and have therefore not yet been introduced to clinical protocols for post-transplant follow-up.…”

Section: Lessons Learntmentioning

confidence: 99%

Have we forgotten imaging prior to and after kidney transplantation?

et al. 2018

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“…Applying a diffusion weighting (indicated by the b-value) causes loss of signal which is proportional to the ADC and can be modeled using a mono-exponential function. Seven studies investigated mono-exponential DWI in kidney transplantation patients (Table 4) (Thoeny et al, 2006; Blondin et al, 2011; Hueper et al, 2011, 2016; Lanzman et al, 2013; Park et al, 2014; Fan et al, 2016) Next to the microscopic diffusion of water the signal measured in DWI is also sensitive to the microcirculation. As such, the measured ADC using low b-values reflects both diffusion and perfusion and the signal can be better described using a bi-exponential model that accounts for contribution of both compartments, which is also known as Intravoxel incoherent motion (IVIM) imaging.…”

Section: Clinical Experience With Functional Mri In Kidney Allograftsmentioning

confidence: 99%

Innovative Perspective: Gadolinium-Free Magnetic Resonance Imaging in Long-Term Follow-Up after Kidney Transplantation

et al. 2017

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Since the mid-1980s magnetic resonance imaging (MRI) has been investigated as a non- or minimally invasive tool to probe kidney allograft function. Despite this long-standing interest, MRI still plays a subordinate role in daily practice of transplantation nephrology. With the introduction of new functional MRI techniques, administration of exogenous gadolinium-based contrast agents has often become unnecessary and true non-invasive assessment of allograft function has become possible. This raises the question why application of MRI in the follow-up of kidney transplantation remains restricted, despite promising results. Current literature on kidney allograft MRI is mainly focused on assessment of (sub) acute kidney injury after transplantation. The aim of this review is to survey whether MRI can provide valuable diagnostic information beyond 1 year after kidney transplantation from a mechanistic point of view. The driving force behind chronic allograft nephropathy is believed to be chronic hypoxia. Based on this, techniques that visualize kidney perfusion and oxygenation, scarring, and parenchymal inflammation deserve special interest. We propose that functional MRI mechanistically provides tools for diagnostic work-up in long-term follow-up of kidney allografts.

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Diffusion‐Weighted imaging and diffusion tensor imaging detect delayed graft function and correlate with allograft fibrosis in patients early after kidney transplantation

Abstract: Combined DTI and DWI detected allograft dysfunction early after kidney transplantation and correlated with allograft fibrosis. J. Magn. Reson. Imaging 2016;44:112-121.

Cited by 89 publications

References 37 publications

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

Have we forgotten imaging prior to and after kidney transplantation?

Innovative Perspective: Gadolinium-Free Magnetic Resonance Imaging in Long-Term Follow-Up after Kidney Transplantation

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