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

Investigation of diffusion time dependence of apparent diffusion coefficient and intravoxel incoherent motion parameters in the human kidney

PURPOSE

To characterize the diffusion time (Δeff) dependence of apparent diffusion coefficient (ADC) and intravoxel incoherent motion-related parameters in the human kidney at 3 T.

METHODS

Sixteen healthy volunteers underwent an MRI examination at 3 T including diffusion-weighted imaging at different Δeff ranging from 24.1 to 104.1 ms. The extended mono-exponential ADC and intravoxel incoherent motion models were fitted to the data for each Δeff and the medullary and cortical ADC, (pseudo-)diffusion coefficients (D* and D) and flow-related signal fraction (f) were calculated.

RESULTS

When all the data were used for fitting, a significant trend toward higher ADC with increasing Δeff was observed between 24.1 and 104.1 ms (median and interquartile range: 2.38 [2.19, 2.47] to 2.84 [2.36, 2.90] × 10-3 mm2/s for cortex, and 2.28 [2.18, 2.37] to 2.82 [2.58, 3.11] × 10-3 mm2/s for medulla). In contrast, no significant differences in ADC were found when only the data acquired at b-values higher than 200 s/mm2 were used for fitting. When the intravoxel incoherent motion model was applied, cortical and medullary f increased significantly (cortex: 0.21 [0.15 0.27] to 0.37 [0.32, 0.49] × 10-3 mm2/s; medulla: 0.15 [0.13 0.29] to 0.41 [0.36 0.51] × 10-3 mm2/s). No significant changes in cortical and medullary D and D* were observed as diffusion time increased.

CONCLUSION

Renal perfusion and tubular flow substantially contribute to the observed increase in ADC over a wide range of Δeff between 24 and 104 ms.

Magnetic resonance imaging of renal oxygenation

Renal hypoxia has a key role in the pathophysiology of many kidney diseases. MRI provides surrogate markers of oxygenation, offering a critical opportunity to detect renal hypoxia. However, studies that have assessed the diagnostic performance of oxygenation MRI for kidney disorders have provided inconsistent results because MRI metrics do not fully capture the complexity of renal oxygenation. Most oxygenation MRI studies are descriptive in nature and fail to detail the pathophysiological importance of the imaging findings. These limitations have restricted the clinical application of oxygenation MRI and the full potential of this technology to facilitate early diagnosis, risk prediction and treatment monitoring of kidney disease has not yet been realized. Understanding of the relationship between renal tissue oxygenation and MRI metrics, which is affected by kidney size, tubular volume fraction and renal blood volume fraction, and measurement of these factors using novel MR methods is imperative for correct physiological interpretation of renal MR oximetry findings. Next steps to enable the clinical adoption of MR oximetry should involve multidisciplinary collaboration to address standardization of acquisition and data analysis protocols and establish reference values of MRI metrics.

Presentation of microstructural diffusion components by color schemes in abdominal organs

PURPOSE

Development of a color scheme representation to facilitate the interpretation of tri-exponential DWI data from abdominal organs, where multi-exponential behavior is more pronounced.

METHODS

Multi-exponential analysis of DWI data provides information about the microstructure of the tissue under study. The tri-exponential signal analysis generates numerous parameter images that are difficult to analyze individually. Summarized color images can simplify at-a-glance analysis. A color scheme was developed in which the slow, intermediate, and fast diffusion components were each assigned to a different red, green, and blue color channel. To improve the appearance of the image, histogram equalization, gamma correction, and white balance were used, and the processing parameters were adjusted. Examples of the resulting color maps of the diffusion fractions of healthy and pathological kidney and prostate are shown.

RESULTS

The color maps obtained by the presented method show the merged information of the slow, intermediate, and fast diffusion components in a single view. A differentiation of the different fractions becomes clearly visible. Fast diffusion regimes, such as in the renal hilus, can be clearly distinguished from slow fractions, such as in dense tumor tissue.

CONCLUSION

Combining the diffusion information from tri-exponential DWI analysis into a single color image allows for simplified interpretation of the diffusion fractions. In the future, such color images may provide additional information about the microstructural nature of the tissue under study.

Probing Renal Microstructure and Function with Advanced Diffusion MRI: Concepts, Applications, Challenges, and Future Directions

Diffusion measurements in the kidney are affected not only by renal microstructure but also by physiological processes (i.e., glomerular filtration, water reabsorption, and urine formation). Because of the superposition of passive tissue diffusion, blood perfusion, and tubular pre-urine flow, the limitations of the monoexponential apparent diffusion coefficient (ADC) model in assessing pathophysiological changes in renal tissue are becoming apparent and motivate the development of more advanced diffusion-weighted imaging (DWI) variants. These approaches take advantage of the fact that the length scale probed in DWI measurements can be adjusted by experimental parameters, including diffusion-weighting, diffusion gradient directions and diffusion time. This forms the basis by which advanced DWI models can be used to capture not only passive diffusion effects, but also microcirculation, compartmentalization, tissue anisotropy. In this review, we provide a comprehensive overview of the recent advancements in the field of renal DWI. Following a short introduction on renal structure and physiology, we present the key methodological approaches for the acquisition and analysis of renal DWI data, including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), non-Gaussian diffusion, and hybrid IVIM-DTI. We then briefly summarize the applications of these methods in chronic kidney disease and renal allograft dysfunction. Finally, we discuss the challenges and potential avenues for further development of renal DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Understanding disciplinary perspectives: a framework to develop skills for interdisciplinary research collaborations of medical experts and engineers

BACKGROUND

Health professionals need to be prepared for interdisciplinary research collaborations aimed at the development and implementation of medical technology. Expertise is highly domain-specific, and learned by being immersed in professional practice. Therefore, the approaches and results from one domain are not easily understood by experts from another domain. Interdisciplinary collaboration in medical research faces not only institutional, but also cognitive and epistemological barriers. This is one of the reasons why interdisciplinary and interprofessional research collaborations are so difficult. To explain the cognitive and epistemological barriers, we introduce the concept of disciplinary perspectives. Making explicit the disciplinary perspectives of experts participating in interdisciplinary collaborations helps to clarify the specific approach of each expert, thereby improving mutual understanding.

METHOD

We developed a framework for making disciplinary perspectives of experts participating in an interdisciplinary research collaboration explicit. The applicability of the framework has been tested in an interdisciplinary medical research project aimed at the development and implementation of diffusion MRI for the diagnosis of kidney cancer, where the framework was applied to analyse and articulate the disciplinary perspectives of the experts involved.

RESULTS

We propose a general framework, in the form of a series of questions, based on new insights from the philosophy of science into the epistemology of interdisciplinary research. We explain these philosophical underpinnings in order to clarify the cognitive and epistemological barriers of interdisciplinary research collaborations. In addition, we present a detailed example of the use of the framework in a concrete interdisciplinary research project aimed at developing a diagnostic technology. This case study demonstrates the applicability of the framework in interdisciplinary research projects.

CONCLUSION

Interdisciplinary research collaborations can be facilitated by a better understanding of how an expert's disciplinary perspectives enables and guides their specific approach to a problem. Implicit disciplinary perspectives can and should be made explicit in a systematic manner, for which we propose a framework that can be used by disciplinary experts participating in interdisciplinary research project. Furthermore, we suggest that educators can explore how the framework and philosophical underpinning can be implemented in HPE to support the development of students' interdisciplinary expertise.

Quantification of Multi-Compartment Flow with Spectral Diffusion MRI

Purpose

Estimation of multi-compartment intravoxel 'flow' in fD in ml/100g/min with multi-b-value diffusion weighted imaging and a multi-Gaussian model in the kidneys.

Theory and Methods

A multi-Gaussian model of intravoxel flow using water transport time to quantify f D (ml/100g/min) is presented and simulated. Multi-compartment anisotropic DWI signal is simulated with Rician noise and SNR=50 and analyzed with a rigid bi-exponential, a rigid tri-exponential and diffusion spectrum imaging model of intravoxel incoherent motion (spectral diffusion) to study extraction of multi-compartment flow. The regularization parameter for spectral diffusion is varied to study the impact on the resulting spectrum and computation speed. The application is demonstrated in a two-center study of 54 kidney allografts with 9 b-value advanced DWI that were split by function (CKD-EPI 2021 eGFR<45ml/min/1.73m2) and fibrosis (Banff 2017 interstitial fibrosis and tubular atrophy score 0-6) to demonstrate multi-compartment flow of various kidney pathologies.

Results

Simulation of anisotropic multi-compartment flow from spectral diffusion demonstrated strong correlation to truth for both three-compartment anisotropic diffusion ( y = 1.08 x + 0.1 , R 2 = 0.71 ) and two-compartment anisotropic diffusion ( y = 0.91 + 0.6 , R 2 = 0.74 ), outperforming rigid models in cases of variable compartment number. Use of a fixed regularization parameter set to λ = 0.1 increased computation up to 208-fold and agreed with voxel-wise cross-validated regularization (concordance correlation coefficient=0.99). Spectral diffusion of renal allografts showed decreasing trend of tubular and vascular flow with higher levels of fibrosis, and significant increase in tissue parenchyma flow (f-stat=3.86, p=0.02). Tubular f D was significantly decreased in allografts with impaired function (eGFR<45ml/min/1.73m2)(Mann-Whitney U t-stat=-2.14, p=0.04).

Conclusions

Quantitative multi-compartment intravoxel 'flow' can be estimated in ml/100g/min with f D from multi-Gaussian diffusion with water transport time, even with moderate anisotropy such as in kidneys. The use of spectral diffusion with a multi-Gaussian model and a fixed regularization parameter is particularly promising in organs such as the kidney with variable numbers of physiologic compartments.

Spatial profiling of in vivo diffusion-weighted MRI parameters in the healthy human kidney

OBJECTIVE

Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers.

MATERIALS AND METHODS

In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length.

RESULTS

Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001).

CONCLUSIONS

These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.

Assessing renal interstitial fibrosis using compartmental, non-compartmental, and model-free diffusion MRI approaches

OBJECTIVE

To assess renal interstitial fibrosis (IF) using diffusion MRI approaches, and explore whether corticomedullary difference (CMD) of diffusion parameters, combination among MRI parameters, or combination with estimated glomerular filtration rate (eGFR) benefit IF evaluation.

METHODS

Forty-two patients with chronic kidney disease were included, undergoing MRI examinations. MRI parameters from apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion-relaxation correlated spectrum imaging (DR-CSI) were obtained both for renal cortex and medulla. CMD of these parameters was calculated. Pathological IF scores (1-3) were obtained by biopsy. Patients were divided into mild (IF = 1, n = 23) and moderate-severe fibrosis (IF = 2-3, n = 19) groups. Group comparisons for MRI parameters were performed. Diagnostic performances were assessed by the receiver operator's curve analysis for discriminating mild from moderate-severe IF patients.

RESULTS

Significant inter-group differences existed for cortical ADC, IVIM-D, IVIM-f, DKI-MD, DR-CSI VB, and DR-CSI VC. Significant inter-group differences existed in ΔADC, ΔMD, ΔVB, ΔVC, ΔQB, and ΔQC. Among the cortical MRI parameters, VB displayed the highest AUC = 0.849, while ADC, f, and MD also showed AUC > 0.8. After combining cortical value and CMD, the diagnostic performances of the MRI parameters were slightly improved except for IVIM-D. Combining VB with f brings the best performance (AUC = 0.903) among MRI bi-variant models. A combination of cortical VB, ΔADC, and eGFR brought obvious improvement in diagnostic performance (AUC 0.963 vs 0.879, specificity 0.826 vs 0.896, and sensitivity 1.000 vs 0.842) than eGFR alone.

CONCLUSION

Our study shows promising results for the assessment of renal IF using diffusion MRI approaches.

CRITICAL RELEVANCE STATEMENT

Our study explores the non-invasive assessment of renal IF, an independent and effective predictor of renal outcomes, by comparing and combining diffusion MRI approaches including compartmental, non-compartmental, and model-free approaches.

KEY POINTS

Significant difference exists for diffusion parameters between mild and moderate-severe IF. Generally, cortical parameters show better performance than corresponding CMD. Bi-variant model lifts the diagnostic performance for assessing IF.

Influence of Magnetic Field Strength on Intravoxel Incoherent Motion Parameters in Diffusion MRI of the Calf

Background: The purpose of this study was to investigate the dependence of Intravoxel Incoherent Motion (IVIM) parameters measured in the human calf on B0. Methods: Diffusion-weighted image data of eight healthy volunteers were acquired using five b-values (0-600 s/mm2) at rest and after muscle activation at 0.55 and 7 T. The musculus gastrocnemius mediale (GM, activated) was assessed. The perfusion fraction f and diffusion coefficient D were determined using segmented fits. The dependence on field strength was assessed using Student's t-test for paired samples and the Wilcoxon signed-rank test. A biophysical model built on the three non-exchanging compartments of muscle, venous blood, and arterial blood was used to interpret the data using literature relaxation times. Results: The measured perfusion fraction of the GM was significantly lower at 7 T, both for the baseline measurement and after muscle activation. For 0.55 and 7 T, the mean f values were 7.59% and 3.63% at rest, and 14.03% and 6.92% after activation, respectively. The biophysical model estimations for the mean proton-density-weighted perfusion fraction were 3.37% and 6.50% for the non-activated and activated states, respectively. Conclusions: B0 may have a significant effect on the measured IVIM parameters. The blood relaxation times suggest that 7 T IVIM may be arterial-weighted whereas 0.55 T IVIM may exhibit an approximately equal weighting of arterial and venous blood.

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.

Tri- and bi-exponential diffusion analyses of the kidney: effect of respiratory-controlled acquisition on diffusion parameters

This study examined whether respiratory-controlled acquisition influences diffusion parameters obtained with intravoxel incoherent motion (IVIM) analysis using tri-exponential and bi-exponential models. Ten healthy volunteers were examined on a 3.0 T MRI system to obtain coronal diffusion-weighted images of both kidneys. The participants were scanned twice using respiratory-triggering (RT) and free-breathing (FB) acquisition to assess the repeatability of the measurements. We determined mean signal intensities in the renal cortex at each b value. Then, perfusion-related diffusion coefficient (Dp), fast-free diffusion coefficient (Df), slow-restricted diffusion coefficient (Ds), and their corresponding fractions (Fp, Ff, and Fs, respectively) were calculated using tri-exponential function. Moreover, perfusion-related diffusion coefficient (D*), the fraction (F), and perfusion-independent diffusion coefficient (D) were calculated using bi-exponential function. Normalized root-mean-square errors for the tri- and bi-exponential analyses (nRMSEtri and nRMSEbi, respectively) were determined to assess the deviation of the fitted to measured data, i.e., the fitting accuracy. Additionally, repeatability coefficients (RCs) were calculated from Bland-Altman plots to evaluate the repeatability of each diffusion parameter. These values were compared between the RT and FB groups. Dp and D* in the RT group were significantly lower than those in the FB group (P < 0.05). In addition, the RT group showed significantly lower nRMSEtri and nRMSEbi values than those in the FB group (P < 0.05). Moreover, Dp, Ds, Fs, and D* at RT showed lower RC values than those at FB. Respiratory-controlled acquisition affects perfusion-related diffusion parameters of the kidney obtained using tri-exponential and bi-exponential analyses.

Cardiac Phase and Flow Compensation Effects on REnal Flow and Microstructure AnisotroPy MRI in Healthy Human Kidney

BACKGROUND

Renal diffusion-weighted imaging (DWI) involves microstructure and microcirculation, quantified with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and hybrid models. A better understanding of their contrast may increase specificity.

PURPOSE

To measure modulation of DWI with cardiac phase and flow-compensated (FC) diffusion gradient waveforms.

STUDY TYPE

Prospective.

POPULATION

Six healthy volunteers (ages: 22-48 years, five females), water phantom.

FIELD STRENGTH/SEQUENCE

3-T, prototype DWI sequence with 2D echo-planar imaging, and bipolar (BP) or FC gradients. 2D Half-Fourier Single-shot Turbo-spin-Echo (HASTE). Multiple-phase 2D spoiled gradient-echo phase contrast (PC) MRI.

ASSESSMENT

BP and FC water signal decays were qualitatively compared. Renal arteries and velocities were visualized on PC-MRI. Systolic (peak velocity), diastolic (end stable velocity), and pre-systolic (before peak velocity) phases were identified. Following mutual information-based retrospective self-registration of DWI within each kidney, and Marchenko-Pastur Principal Component Analysis (MPPCA) denoising, combined IVIM-DTI analysis estimated mean diffusivity (MD), fractional anisotropy (FA), and eigenvalues (λi) from tissue diffusivity (Dt ), perfusion fraction (fp ), and pseudodiffusivity (Dp , Dp,axial , Dp,radial ), for each tissue (cortex/medulla, segmented on b0/FA respectively), phase, and waveform (BP, FC). Monte Carlo water diffusion simulations aided data interpretation.

STATISTICAL TESTS

Mixed model regression probed differences between tissue types and pulse sequences. Univariate general linear model analysis probed variations among cardiac phases. Spearman correlations were measured between diffusion metrics and renal artery velocities. Statistical significance level was set at P < 0.05.

RESULTS

Water BP and FC signal decays showed no differences. Significant pulse sequence dependence occurred for λ1 , λ3 , FA, Dp , fp , Dp,axial , Dp,radial in cortex and medulla, and medullary λ2 . Significant cortex/medulla differences occurred with BP for all metrics except MD (systole [P = 0.224]; diastole [P = 0.556]). Significant phase dependence occurred for Dp , Dp,axial , Dp,radial for BP and medullary λ1 , λ2 , λ3 , MD for FC. FA correlated significantly with velocity. Monte Carlo simulations indicated medullary measurements were consistent with a 34 μm tubule diameter.

DATA CONCLUSION

Cardiac gating and flow compensation modulate of measurements of renal diffusion.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY STAGE: 2.

Capability of arterial spin labeling and intravoxel incoherent motion diffusion-weighted imaging to detect early kidney injury in chronic kidney disease

OBJECTIVES

To prospectively investigate the capability of arterial spin labeling (ASL) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the identification of early kidney injury in chronic kidney disease (CKD) patients with normal estimated glomerular filtration rate (eGFR).

METHODS

Fifty-four CKD patients confirmed by renal biopsy (normal eGFR group [eGFR ≥ 90 mL/min/1.73 m2]: n = 26; abnormal eGFR group [eGFR < 90 mL/min/1.73 m2]: n = 28) and 20 healthy volunteers (HV) were recruited. All subjects were examined by IVIM-DWI and ASL imaging. Renal blood flow (RBF) derived from ASL, true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) derived from IVIM-DWI were measured from the renal cortex. One-way analysis of variance was used to compare MRI parameters among the three groups. The correlation between eGFR and MRI parameters was evaluated by Spearman correlation analysis. Diagnostic performances of MRI parameters for detecting kidney injury were assessed by receiver operating characteristic (ROC) curves.

RESULTS

The renal cortical D, D*, f, and RBF values showed statistically significant differences among the three groups. eGFR was positively correlated with MRI parameters (D: r = 0.299, D*: r = 0.569, f: r = 0.733, RBF: r = 0.586). The areas under the curve (AUCs) for discriminating CKD patients from HV were 0.725, 0.752, 0.947, and 0.884 by D, D*, f, and RBF, respectively. D, D*, f, RBF, and eGFR identified CKD patients with normal eGFR with AUCs of 0.735, 0.612, 0.917, 0.827, and 0.733, respectively, and AUC of f value was significantly larger than that of eGFR.

CONCLUSION

IVIM-DWI and ASL were useful for detecting underlying pathologic injury in early CKD patients with normal eGFR.

KEY POINTS

• The renal cortical f and RBF values in the control group were significantly higher than those in the normal eGFR group. • A negative correlation was observed between the renal cortical D, D*, f, and RBF values and SCr and 24 h-UPRO, while eGFR was significantly positively correlated with renal cortical D, D*, f, and RBF values. • The AUC of renal cortical f values was statistically larger than that of eGFR for the discrimination between the CKD with normal eGFR group and the control group.

Image downsampling expedited adaptive least-squares (IDEAL) fitting improves intravoxel incoherent motion (IVIM) analysis in the human kidney

PURPOSE

To improve the reliability of intravoxel incoherent motion (IVIM) model parameter estimation for the DWI in the kidney using a novel image downsampling expedited adaptive least-squares (IDEAL) approach.

METHODS

The robustness of IDEAL was investigated using simulated DW-MRI data corrupted with different levels of Rician noise. Subsequently, the performance of the proposed method was tested by fitting bi- and triexponential IVIM model to in vivo renal DWI data acquired on a clinical 3 Tesla MRI scanner and compared to conventional approaches (fixed D* and segmented fitting).

RESULTS

The numerical simulations demonstrated that the IDEAL algorithm provides robust estimates of the IVIM parameters in the presence of noise (SNR of 20) as indicated by relatively low absolute percentage bias (maximal sMdPB <20%) and normalized RMSE (maximal RMSE <28%). The analysis of the in vivo data showed that the IDEAL-based IVIM parameter maps were less noisy and more visually appealing than those obtained using the fixed D* and segmented methods. Further, coefficients of variation for nearly all IVIM parameters were significantly reduced in cortex and medulla for IDEAL-based biexponential (coefficients of variation: 4%-50%) and triexponential (coefficients of variation: 7.5%-75%) IVIM modelling compared to the segmented (coefficients of variation: 4%-120%) and fixed D* (coefficients of variation: 17%-174%) methods, reflecting greater accuracy of this method.

CONCLUSION

The proposed fitting algorithm yields more robust IVIM parameter estimates and is less susceptible to poor SNR than the conventional fitting approaches. Thus, the IDEAL approach has the potential to improve the reliability of renal DW-MRI analysis for clinical applications.

Intravoxel incoherent motion diffusion-weighted MRI of renal parenchyma and its clinical significance in patients with untreated acute leukemia: a pilot study

PURPOSE

To evaluate quantitative parameters derived from intravoxel incoherent motion diffusion-weighted MRI (IVIM) of renal parenchyma in patients with untreated acute leukemia (AL) and analyze its prognostic significance and probable pathological mechanism.

METHODS

From March 2019 to November 2021, 67 newly diagnosed AL patients and 67 healthy controls matched in age and sex were recruited. All participants underwent IVIM in the kidneys, and D, D*, f, standard ADC values were measured. The differences of all parameters between AL and controls were analyzed. The relationship between imaging parameters and estimated glomerular filtration rate (eGFR) was studied. Univariable and multivariable analyses were performed to investigate prognostic significance of possible indicators.

RESULTS

The f and D value of renal medulla and D value of renal cortex in AL patients were lower than those in the healthy control group (t = - 2.173, t = - 3.463, t = - 2.030, respectively, all P < 0.05). The cortical f, cortical standard ADC, medullary f, and medullary standard ADC were correlated with the eGFR (r = 0.524, r = 0.401, r = 0.415, r = 0.325, respectively, all P < 0.05) in patients with AL. A medullary f value ≤ 9.51% (hazard ratio: 0.282; 95% confidence interval: 0.110, 0.719; P = 0.008) was associated with overall survival in a multivariable analysis.

CONCLUSION

The f and standard ADC values in renal parenchyma were the probable imaging markers of renal function in patients with newly diagnosed de novo AL. Lower renal medullary f value was a potential independent predictor for overall survival.

Parametric MRI Detects Aristolochic Acid Induced Acute Kidney Injury

Exposure to aristolochic acid (AA) is of increased concern due to carcinogenic and nephrotoxic effects, and incidence of aristolochic acid nephropathy (AAN) is increasing. This study characterizes renal alterations during the acute phase of AAN using parametric magnetic resonance imaging (MRI). An AAN and a control group of male Wistar rats received administration of aristolochic acid I (AAI) and polyethylene glycol (PEG), respectively, for six days. Both groups underwent MRI before and 2, 4 and 6 days after AAI or PEG administration. T₂ relaxation times and apparent diffusion coefficients (ADCs) were determined for four renal layers. Serum creatinine levels (sCr) and blood urea nitrogen (BUN) were measured. Tubular injury scores (TIS) were evaluated based on histologic findings. Increased T₂ values were detected since day 2 in the AAN group, but decreased ADCs and increased sCr levels and BUN were not detected until day 4. Significant linear correlations were observed between T₂ of the cortex and the outer stripe of outer medulla and TIS. Our results demonstrate that parametric MRI facilitates early detection of renal injury induced by AAI in a rat model. T₂ mapping may be a valuable tool for assessing kidney injury during the acute phase of AAN.

Precision of region of interest-based tri-exponential intravoxel incoherent motion quantification and the role of the Intervoxel spatial distribution of flow velocities

PURPOSE

The purpose of this work was to obtain precise tri-exponential intravoxel incoherent motion (IVIM) quantification in the liver using 2D (b-value and first-order motion moment [M1 ]) IVIM-DWI acquisitions and region of interest (ROI)-based fitting techniques.

METHODS

Diffusion MRI of the liver was performed in 10 healthy volunteers using three IVIM-DWI acquisitions: conventional monopolar, optimized monopolar, and optimized 2D (b-M1 ). For each acquisition, bi-exponential and tri-exponential full, segmented, and over-segmented ROI-based fitting and a newly proposed blood velocity SDdistribution (BVD) fitting technique were performed to obtain IVIM estimates in the right and left liver lobes. Fitting quality was evaluated using corrected Akaike information criterion. Precision metrics (test-retest repeatability, inter-reader reproducibility, and inter-lobar agreement) were evaluated using Bland-Altman analysis, repeatability/reproducibility coefficients (RPCs), and paired sample t-tests. Precision was compared across acquisitions and fitting methods.

RESULTS

High repeatability and reproducibility was observed in the estimations of the diffusion coefficient (Dtri  = [1.03 ± 0.11] × 10-3  mm2 /s; RPCs ≤ 1.34 × 10-4  mm2 /s), perfusion fractions (F1  = 3.19 ± 1.89% and F2  = 16.4 ± 2.07%; RPCs ≤ 2.51%), and blood velocity SDs (Vb,1  = 1.44 ± 0.14 mm/s and Vb,2  = 3.62 ± 0.13 mm/s; RPCs ≤ 0.41 mm/s) in the right liver lobe using the 2D (b-M1 ) acquisition in conjunction with BVD fitting. Using these methods, significantly larger (p < 0.01) estimates of Dtri and F1 were observed in the left lobe in comparison to the right lobe, while estimates of Vb,1 and Vb,2 demonstrated high interlobar agreement (RPCs ≤ 0.45 mm/s).

CONCLUSIONS

The 2D (b-M1 ) IVIM-DWI data acquisition in conjunction with BVD fitting enables highly precise tri-exponential IVIM quantification in the right liver lobe.

Measuring glomerular blood transfer rate in kidney using diffusion-weighted arterial spin labeling

PURPOSE

To propose a two-compartment renal perfusion model for calculating glomerular blood transfer rate ( k G $$ {k}_G $$ ) as a new measure of renal function.

THEORY

The renal perfusion signal was divided into preglomerular and postglomerular flows according to flow velocity. By analyzing perfusion signals acquired with and without diffusion gradients, we estimated k G $$ {k}_G $$ , the blood transfer rate from the afferent arterioles into the glomerulus.

METHODS

A multislice multidelay diffusion-weighted arterial spin labeling sequence was applied to subjects with no history of renal dysfunctions. In the multiple b-value experiment, images were acquired with seven b-values to validate the bi-exponential decays of the renal perfusion signal and to determine the appropriate b-value for suppressing preglomerular flow. In the caffeine challenge, six subjects were scanned twice on the caffeine day and the control day. The k G $$ {k}_G $$ values of the two dates were compared.

RESULTS

The perfusion signal showed a bi-exponential decay with b-values. There was no significant difference in renal blood flow and arterial transit time between caffeine and control days. In contrast, cortical k G $$ {k}_G $$ was significantly higher on the caffeine day (caffeine day: 106 . 0 ± 20 . 3 $$ 106.0\pm 20.3 $$ min - 1 $$ {}^{-1} $$ control day: 78 . 8 ± 22 . 9 $$ 78.8\pm 22.9 $$ min - 1 $$ {}^{-1} $$ ). These results were consistent with those from the literature.

CONCLUSION

We showed that the perfusion signal consists of two compartments of preglomerular flow and postglomerular flow. The proposed diffusion-weighted arterial spin labeling could measure the glomerular blood transfer rate ( k G $$ {k}_G $$ ), which was sensitive enough to noninvasively monitor the caffeine-induced vasodilation of afferent arterioles.

b value and first-order motion moment optimized data acquisition for repeatable quantitative intravoxel incoherent motion DWI

PURPOSE

To design a b value and first-order motion moment (M1 ) optimized data acquisition for repeatable intravoxel incoherent motion (IVIM) quantification in the liver.

METHODS

Cramer-Rao lower bound optimization was performed to determine optimal monopolar and optimal 2D samplings of the b-M1 space based on noise performance. Monte Carlo simulations were used to evaluate the bias and variability in estimates obtained using the proposed optimal samplings and conventional monopolar sampling. Diffusion MRI of the liver was performed in 10 volunteers using 3 IVIM acquisitions: conventional monopolar, optimized monopolar, and b-M1 -optimized gradient waveforms (designed based on the optimal 2D sampling). IVIM parameter maps of diffusion coefficient, perfusion fraction, and blood velocity SD were obtained using nonlinear least squares fitting. Noise performance (SDs), stability (outlier percentage), and test-retest or scan-rescan repeatability (intraclass correlation coefficients) were evaluated and compared across acquisitions.

RESULTS

Cramer-Rao lower bound and Monte Carlo simulations demonstrated improved noise performance of the optimal 2D sampling in comparison to monopolar samplings. Evaluating the designed b-M1 -optimized waveforms in healthy volunteers, significant decreases (p < 0.05) in the SDs and outlier percentages were observed for measurements of diffusion coefficient, perfusion fraction, and blood velocity SD in comparison to measurements obtained using monopolar samplings. Good-to-excellent repeatability (intraclass correlation coefficients ≥ 0.77) was observed for all 3 parameters in both the right and left liver lobes using the b-M1 -optimized waveforms.

CONCLUSIONS

2D b-M1 -optimized data acquisition enables repeatable IVIM quantification with improved noise performance. 2D acquisitions may advance the establishment of IVIM quantitative biomarkers for liver diseases.

Simultaneous Quantification of Anisotropic Microcirculation and Microstructure in Peripheral Nerve

Peripheral nerve injury is a significant public health challenge, and perfusion in the nerve is a potential biomarker for assessing the injury severity and prognostic outlook. Here, we applied a novel formalism that combined intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) to simultaneously characterize anisotropic microcirculation and microstructure in the rat sciatic nerve. Comparison to postmortem measurements revealed that the in vivo IVIM-DTI signal contained a fast compartment (2.32 ± 0.04 × 10−3 mm2/s mean diffusivity, mean ± sem, n = 6, paired t test p < 0.01) that could be attributed to microcirculation in addition to a slower compartment that had similar mean diffusivity as the postmortem nerve (1.04 ± 0.01 vs. 0.96 ± 0.05 × 10−3 mm2/s, p > 0.05). Although further investigation and technical improvement are warranted, this preliminary study demonstrates both the feasibility and potential for applying the IVIM-DTI methodology to peripheral nerves for quantifying perfusion in the presence of anisotropic tissue microstructure.

Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions

Throughout the body, muscle structure and function can be interrogated using a variety of noninvasive magnetic resonance imaging (MRI) methods. Recently, intravoxel incoherent motion (IVIM) MRI has gained momentum as a method to evaluate components of blood flow and tissue diffusion simultaneously. Much of the prior research has focused on highly vascularized organs, including the brain, kidney, and liver. Unique aspects of skeletal muscle, including the relatively low perfusion at rest and large dynamic range of perfusion between resting and maximal hyperemic states, may influence the acquisition, postprocessing, and interpretation of IVIM data. Here, we introduce several of those unique features of skeletal muscle; review existing studies of IVIM in skeletal muscle at rest, in response to exercise, and in disease states; and consider possible confounds that should be addressed for muscle-specific evaluations. Most studies used segmented nonlinear least squares fitting with a b-value threshold of 200 sec/mm2 to obtain IVIM parameters of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). In healthy individuals, across all muscles, the average ± standard deviation of D was 1.46 ± 0.30 × 10-3  mm2 /sec, D* was 29.7 ± 38.1 × 10-3  mm2 /sec, and f was 11.1 ± 6.7%. Comparisons of reported IVIM parameters in muscles of the back, thigh, and leg of healthy individuals showed no significant difference between anatomic locations. Throughout the body, exercise elicited a positive change of all IVIM parameters. Future directions including advanced postprocessing models and potential sequence modifications are discussed. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

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.

Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver

PURPOSE

Intravoxel incoherent motion (IVIM) studies are performed with different acquisition protocols. Comparing them requires knowledge of echo time (TE) dependencies. The TE-dependence of the biexponential perfusion fraction f is well-documented, unlike that of its triexponential counterparts f₁ and f₂ and the biexponential and triexponential pseudodiffusion coefficients D^* , D 1 ∗ , and D 2 ∗ . The purpose was to investigate the TE-dependence of these parameters and to check whether the triexponential pseudodiffusion compartments are associated with arterial and venous blood.

METHODS

Fifteen healthy volunteers (19-58 y; mean: 24.7 y) underwent diffusion-weighted imaging of the abdomen with 24 b-values (0.2-800 s/mm² ) at TEs of 45, 60, 75, and 90 ms. Regions of interest (ROIs) were manually drawn in the liver. One set of bi- and triexponential IVIM parameters per volunteer and TE was determined. The TE-dependence was assessed with the Kruskal-Wallis test.

RESULTS

TE-dependence was observed for f (P < .001), f₁ (P = .001), and f₂ (P < .001). Their median values at the four measured TEs were: f: 0.198/0.240/0.274/0.359, f₁ : 0.113/0.139/0.146/0.205, f₂ : 0.115/0.155/0.182/0.194. D, D^* , D 1 ∗ , and D 2 ∗ showed no significant TE-dependence. Their values were: diffusion coefficient D (10^-4 mm² /s): 9.45/9.63/9.75/9.41, biexponential D^* (10^-2 mm² /s): 5.26/5.52/6.13/5.82, triexponential D 1 ∗ (10^-2 mm² /s): 1.73/2.91/2.25/2.51, triexponential D 2 ∗ (mm² /s): 0.478/1.385/0.616/0.846.

CONCLUSION

f₁ and f₂ show similar TE-dependence as f, ie, increase with rising TE; an effect that must be accounted for when comparing different studies. The diffusion and pseudodiffusion coefficients might be compared without TE correction. Because of the similar TE-dependence of f₁ and f₂ , the triexponential pseudodiffusion compartments are most probably not associated to venous and arterial blood.

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.

Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model

PURPOSE

To compare the diagnostic efficiency of the mono-exponential model and bi-exponential model deriving from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating the pathological grade of esophageal squamous cell carcinoma (ESCC).

METHODS

Fifty-four patients with ESCC were divided into three groups of poorly-differentiated (PD), moderately-differentiated (MD), and well-differentiated (WD), and underwent the IVIM-DWI scan. Mono-exponential (Dmono, D*mono, and fmono) and bi-exponential fit parameters (Dbi, D*bi, and fbi) were calculated using the IVIM data for the tumors. Mean parameter values of three groups were compared using a one-way ANOVA followed by post hoc tests. The receiver operating characteristic curve was drawn for differentiating pathological grade of ESCC. Correlations between pathological grades and IVIM parameters were analyzed.

RESULTS

There were significant differences in fmono and fbi among the PD, MD and WD ESCC groups (all p<0.05). The fmono were 0.32 ± 0.07, 0.23 ± 0.08, and 0.16 ± 0.05, respectively, and the fbi were 0.35 ± 0.08, 0.26 ± 0.10, and 0.18 ± 0.07, respectively. There was a significant difference in the Dmono between the WD and the PD group (1.48 ± 0.51* 10-3 mm2/s versus 1.05 ± 0.44*10-3 mm2/s, p<0.05), but there was no significant difference between the WD and MD groups, MD and PD groups (all p>0.05). The D*mono, Dbi, and D*bi showed no significant difference among the three groups (all p>0.05). The area under the curve (AUC) of Dmono, fmono and fbi in differentiating WD from PD ESCC were 0.764, 0.961 and 0.932, and the sensitivity and specificity were 92.9% and 60%, 92.9% and 90%, 85.7% and 100%, respectively. The AUC of fmono and fbi in differentiating MD from PD ESCC were 0.839 and 0.757, and the sensitivity and specificity were 78.6% and 80%, 85.7% and 70%, respectively. The AUC of fmono and fbi in differentiating MD from WD ESCC were 0.746 and 0.740, and the sensitivity and specificity were 65% and 85%, 80% and 60%, respectively. The pathologically differentiated grade was correlated with all IVIM parameters (all p<0.05).

CONCLUSIONS

The mono-exponential IVIM model is superior to the bi-exponential IVIM model in differentiating pathological grades of ESCC, which may be a promising imaging method to predict pathological grades of ESCC.

Evidence of Tri-Exponential Decay for Liver Intravoxel Incoherent Motion MRI: A Review of Published Results and Limitations

Diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) have been explored to assess liver tumors and diffused liver diseases. IVIM reflects the microscopic translational motions that occur in voxels in magnetic resonance (MR) DWI. In biologic tissues, molecular diffusion of water and microcirculation of blood in the capillary network can be assessed using IVIM DWI. The most commonly applied model to describe the DWI signal is a bi-exponential model, with a slow compartment of diffusion linked to pure molecular diffusion (represented by the coefficient D_slow), and a fast compartment of diffusion, related to microperfusion (represented by the coefficient D_fast). However, high variance in D_fast estimates has been consistently shown in literature for liver IVIM, restricting its application in clinical practice. This variation could be explained by the presence of another very fast compartment of diffusion in the liver. Therefore, a tri-exponential model would be more suitable to describe the DWI signal. This article reviews the published evidence of the existence of this additional very fast diffusion compartment and discusses the performance and limitations of the tri-exponential model for liver IVIM in current clinical settings.

Spectral diffusion analysis of kidney intravoxel incoherent motion MRI in healthy volunteers and patients with renal pathologies

PURPOSE

To assess the feasibility of measuring tubular and vascular signal fractions in the human kidney using nonnegative least-square (NNLS) analysis of intravoxel incoherent motion data collected in healthy volunteers and patients with renal pathologies.

METHODS

MR imaging was performed at 3 Tesla in 12 healthy subjects and 3 patients with various kidney pathologies (fibrotic kidney disease, failed renal graft, and renal masses). Relative signal fractions f and mean diffusivities of the diffusion components in the cortex, medulla, and renal lesions were obtained using the regularized NNLS fitting of the intravoxel incoherent motion data. Test-retest repeatability of the NNLS approach was tested in 5 volunteers scanned twice.

RESULTS

In the healthy kidneys, the NNLS method yielded diffusion spectra with 3 distinguishable components that may be linked to the slow tissue water diffusion, intermediate tubular and vascular flow, and fast blood flow in larger vessels with the relative signal fractions, f_slow , f_interm and f_fast , respectively. In the pathological kidneys, the diffusion spectra varied substantially from those acquired in the healthy kidneys. Overall, the renal cyst showed substantially higher f_interm and lower f_slow , whereas the fibrotic kidney, failed renal graft, and renal cell carcinoma demonstrated the opposite trend.

CONCLUSION

NNLS-based intravoxel incoherent motion could potentially become a valuable tool in assessing changes in tubular and vascular volume fractions under pathophysiological conditions.

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.

An optimized b-value distribution for triexponential intravoxel incoherent motion (IVIM) in the liver

PURPOSE

To find an optimized b-value distribution for reproducible triexponential intravoxel incoherent motion (IVIM) exams in the liver.

METHODS

A numeric optimization of b-value distributions was performed using the triexponential IVIM equation and 27 different IVIM parameter sets. Starting with an initially optimized distribution of 6 b-values, the number of b-values was increased stepwise. Each new b-value was chosen from a set of 64 predefined b-values based on the computed summed relative mean error of the fitted triexponential IVIM parameters. This process was repeated for up to 100 b-values. In simulations and in vivo measurements, optimized b-value distributions were compared to 4 representative distributions found in literature.

RESULTS

The first 16 optimized b-values were 0, 0.3, 0.3, 70, 200, 800, 70, 1, 3.5, 5, 70, 1.2, 6, 45, 1.5, and 60 in units of s/mm² . Low b-values were much more frequent than high b-values. The optimized b-value distribution resulted in a higher fit stability compared to distributions used in literature in both, simulation and in vivo measurements. Using more than 6 b-values, ideally 16 or more, increased the fit stability considerably.

CONCLUSION

Using optimized b-values, the fit uncertainty in triexponential IVIM can be largely reduced. Ideally, 16 or more b-values should be acquired.

Multiparametric Renal MRI: An Intrasubject Test-Retest Repeatability Study

Background

Renal multiparametric magnetic resonance imaging (MRI) is a promising tool for diagnosis, prognosis, and treatment monitoring in kidney disease.

Purpose

To determine intrasubject test–retest repeatability of renal MRI measurements.

Study Type

Prospective.

Population

Nineteen healthy subjects aged over 40 years.

Field Strength/Sequences

T₁ and T₂ mapping, R₂* mapping or blood oxygenation level‐dependent (BOLD) MRI, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI), 2D phase contrast, arterial spin labelling (ASL), dynamic contrast enhanced (DCE) MRI, and quantitative Dixon for fat quantification at 3T.

Assessment

Subjects were scanned twice with ~1 week between visits. Total scan time was ~1 hour. Postprocessing included motion correction, semiautomated segmentation of cortex and medulla, and fitting of the appropriate signal model.

Statistical Test

To assess the repeatability, a Bland–Altman analysis was performed and coefficients of variation (CoVs), repeatability coefficients, and intraclass correlation coefficients were calculated.

Results

CoVs for relaxometry (T₁, T₂, R₂*/BOLD) were below 6.1%, with the lowest CoVs for T₂ maps and highest for R₂*/BOLD. CoVs for all diffusion analyses were below 7.2%, except for perfusion fraction (F_P), with CoVs ranging from 18–24%. The CoV for renal sinus fat volume and percentage were both around 9%. Perfusion measurements were most repeatable with ASL (cortical perfusion only) and 2D phase contrast with CoVs of 10% and 13%, respectively. DCE perfusion had a CoV of 16%, while single kidney glomerular filtration rate (GFR) had a CoV of 13%. Repeatability coefficients (RCs) ranged from 7.7–87% (lowest/highest values for medullary mean diffusivity and cortical F_P, respectively) and intraclass correlation coefficients (ICCs) ranged from −0.01 to 0.98 (lowest/highest values for cortical F_P and renal sinus fat volume, respectively).

Data Conclusion

CoVs of most MRI measures of renal function and structure (with the exception of F_P and perfusion as measured by DCE) were below 13%, which is comparable to standard clinical tests in nephrology.

Level of Evidence

2

Technical Efficacy

Stage 1

Magnetization Transfer Imaging Is Unaffected by Decreases in Renal Perfusion in Swine

OBJECTIVES

Multiparametric renal magnetic resonance imaging (MRI), including diffusion-weighted imaging, magnetic resonance elastography, and magnetization transfer imaging (MTI), is valuable in the noninvasive assessment of renal fibrosis. However, hemodynamic changes in diseased kidneys may impede their ability to measure renal fibrosis. Because MTI assesses directly tissue content of macromolecules, we test the hypothesis that MTI would be insensitive to renal hemodynamic changes in swine kidneys with acute graded ischemia.

MATERIALS AND METHODS

Seven domestic pigs underwent placement of an inflatable silicone cuff around the right renal artery to induce graded renal ischemia. Multiparametric MRI was performed at baseline, 50%, 75%, and 100% renal artery stenosis as well as reperfusion. Measurements included regional perfusion, R2*, apparent diffusion coefficient (ADC), stiffness, and magnetization transfer ratio (MTR) using arterial spin-labeled MRI, blood oxygenation-dependent MRI, diffusion-weighted imaging, magnetic resonance elastography, and MTI, respectively. Histology was performed to rule out renal fibrosis.

RESULTS

During graded ischemia, decreases in renal perfusion were accompanied with elevated R2*, decreased ADC, and stiffness, whereas no statistically significant changes were observed in the MTR. No fibrosis was detected by histology. After release of the obstruction, renal perfusion showed only partial recovery, associated with return of kidney R2*, ADC, and stiffness to baseline levels, whereas cortical MTR decreased slightly.

CONCLUSIONS

Renal MTI is insensitive to decreases in renal perfusion and may offer reliable assessment of renal structural changes.

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Objectives

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.

Materials and methods

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.

Results

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.

Discussion

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.

Electronic supplementary material

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

Use of intravoxel incoherent motion imaging to monitor a rat kidney chronic allograft damage model

BACKGROUND

Chronic allograft damage (CAD) is the leading cause of long-term graft dysfunction. A noninvasive method that can diagnose CAD early and monitor its development is needed.

METHODS

Kidneys from Fisher rats were transplanted into Lewis rats to establish a CAD model (n = 20). The control group underwent syngeneic kidney transplantation (n = 20). The serum creatinine of the rats was monitored. At 4, 12, and 20 weeks after modeling, a magnetic resonance imaging (MRI) examination was performed. The apparent diffusion coefficient (ADC), pseudo diffusion coefficient (D*), true diffusion coefficient (D) and perfusion fraction (f) of the two groups were analyzed. Chronic allograft damage index (CADI) scoring was used to evaluate the transplanted kidney specimens. Immunohistochemistry was used to detect the expression of fibrosis markers in the transplanted kidney tissues and to analyze their correlations with all MRI parameters.

RESULTS

The transplanted kidneys in the experimental group developed CAD changes before the appearance of elevated creatinine. The MRI parameters in the experimental group [ADC (1.460 ± 0.109 VS 2.095 ± 0.319, P < 0.001), D (1.435 ± 0.102 VS 1.969 ± 0.305, P < 0.001), and f (26.532 ± 2.136 VS 32.255 ± 4.013, P < 0.001)] decreased, and D* (20.950 ± 2.273 VS 21.415 ± 1.598, P = 0.131) was not significantly different from those in the control group. ADC, D and f were negatively correlated with the CADI and the α-SMA and vimentin expression levels.

CONCLUSION

Intravoxel incoherent motion (IVIM) imaging could detect CAD earlier than creatinine and reflect the degree of fibrosis in grafts quantitatively.

On the sensitivity of the diffusion MRI signal to brain activity in response to a motor cortex paradigm

Diffusion functional magnetic resonance imaging (dfMRI) is a promising technique to map functional activations by acquiring diffusion‐weighed spin‐echo images. In previous studies, dfMRI showed higher spatial accuracy at activation mapping compared to classic functional MRI approaches. However, it remains unclear whether dfMRI measures result from changes in the intracellular/extracellular environment, perfusion, and/or T₂ values. We designed an acquisition/quantification scheme to disentangle such effects in the motor cortex during a finger‐tapping paradigm. dfMRI was acquired at specific diffusion weightings to selectively suppress perfusion and free‐water diffusion, then time series of the apparent diffusion coefficient (ADC‐fMRI) and of intravoxel incoherent motion (IVIM) effects were derived. ADC‐fMRI provided ADC estimates sensitive to changes in perfusion and free‐water volume, but not to T₂/T₂* values. With IVIM modeling, we isolated the perfusion contribution to ADC, while suppressing T₂ effects. Compared to conventional gradient‐echo blood oxygenation level‐dependent fMRI, activation maps obtained with dfMRI and ADC‐fMRI had smaller clusters, and the spatial overlap between the three techniques was below 50%. Increases of perfusion fractions were observed during task in both dfMRI and ADC‐fMRI activations. Perfusion effects were more prominent with ADC‐fMRI than with dfMRI but were significant in less than 25% of activation regions. IVIM modeling suggests that the sensitivity to task of dfMRI derives from a decrease of intracellular/extracellular diffusion and an increase of the pseudo‐diffusion signal fraction, leading to different, more confined spatial activation patterns compared to classic functional MRI.

Noninvasive assessment of renal fibrosis by magnetic resonance imaging and ultrasound techniques

Renal fibrosis is a useful biomarker for diagnosis and guidance of therapeutic interventions of chronic kidney disease (CKD), a worldwide disease that affects more than 10% of the population and is one of the major causes of death. Currently, tissue biopsy is the gold standard for assessment of renal fibrosis. However, it is invasive, and prone to sampling error and observer variability, and may also result in complications. Recent advances in diagnostic imaging techniques, including magnetic resonance imaging (MRI) and ultrasonography, have shown promise for noninvasive assessment of renal fibrosis. These imaging techniques measure renal fibrosis by evaluating its impacts on the functional, mechanical, and molecular properties of the kidney, such as water mobility by diffusion MRI, tissue hypoxia by blood oxygenation level dependent MRI, renal stiffness by MR and ultrasound elastography, and macromolecule content by magnetization transfer imaging. Other MR techniques, such as T1/T2 mapping and susceptibility-weighted imaging have also been explored for measuring renal fibrosis. Promising findings have been reported in both preclinical and clinical studies using these techniques. Nevertheless, limited specificity, sensitivity, and practicality in these techniques may hinder their immediate application in clinical routine. In this review, we will introduce methodologies of these techniques, outline their applications in fibrosis imaging, and discuss their limitations and pitfalls.

Interdisciplinary expertise in medical practice: Challenges of using and producing knowledge in complex problem-solving

Purpose: Clarification of interdisciplinary expertise as the ability to deal with the cognitive and epistemological challenges of multi- and interdisciplinary problem-solving-such as in developing and implementing medical technology for diagnoses and treatment of patients in collaborations between clinicians, technicians, and engineers-and of the higher-order cognitive skills needed as part of this expertise. Method: Clarify the epistemological difficulties of combining scientific knowledge, methodologies and technologies from different disciplines in problem-solving, by drawing on recent developments in the philosophy of science. Conclusion: We argue that interdisciplinary expertise involves the cognitive ability to connect, translate and establish links between disciplinary knowledge, as well as the metacognitive ability to understand and explain the role of the disciplinary perspective-consisting of, e.g. basic concepts, theories, models, methodologies, technologies, and specific ways of measuring, reasoning and modeling in a discipline-in how knowledge is used and produced.

On the Field Strength Dependence of Bi- and Triexponential Intravoxel Incoherent Motion (IVIM) Parameters in the Liver

BACKGROUND

Studies on intravoxel incoherent motion (IVIM) imaging are carried out with different acquisition protocols.

PURPOSE

To investigate the dependence of IVIM parameters on the B₀ field strength when using a bi- or triexponential model.

STUDY TYPE

Prospective.

STUDY POPULATION

20 healthy volunteers (age: 19-28 years).

FIELD STRENGTH/SEQUENCE

Volunteers were examined at two field strengths (1.5 and 3T). Diffusion-weighted images of the abdomen were acquired at 24 b-values ranging from 0.2 to 500 s/mm² .

ASSESSMENT

ROIs were manually drawn in the liver. Data were fitted with a bi- and a triexponential IVIM model. The resulting parameters were compared between both field strengths.

STATISTICAL TESTS

One-way analysis of variance (ANOVA) and Kruskal-Wallis test were used to test the obtained IVIM parameters for a significant field strength dependency.

RESULTS

At b-values below 6 s/mm² , the triexponential model provided better agreement with the data than the biexponential model. The average tissue diffusivity was D = 1.22/1.00 μm² /msec at 1.5/3T. The average pseudodiffusion coefficients for the biexponential model were D^* = 308/260 μm² /msec at 1.5/3T; and for the triexponential model D 1 * = 81.3/65.9 μm² /msec, D 2 * = 2453/2333 μm² /msec at 1.5/3T. The average perfusion fractions for the biexponential model were f = 0.286/0.303 at 1.5/3T; and for the triexponential model f₁ = 0.161/0.174 and f₂ = 0.152/0.159 at 1.5/3T. A significant B₀ dependence was only found for the biexponential pseudodiffusion coefficient (ANOVA/KW P = 0.037/0.0453) and tissue diffusivity (ANOVA/KW: P < 0.001).

DATA CONCLUSION

Our experimental results suggest that triexponential pseudodiffusion coefficients and perfusion fractions obtained at different field strengths could be compared across different studies using different B₀ . However, it is recommended to take the field strength into account when comparing tissue diffusivities or using the biexponential IVIM model. Considering published values for oxygenation-dependent transversal relaxation times of blood, it is unlikely that the two blood compartments of the triexponential model represent venous and arterial blood.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1883-1892.

Estimation of intravoxel incoherent motion parameters using low b-values

Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. However, IVIM imaging at low b-values is a persistent problem. This paper aims to investigate in a systematic and detailed manner how the number of low b-values influences the estimation of IVIM parameters. To this end, diffusion-weighted (DW) data with different low b-values were simulated to get insight into the distributions of subsequent IVIM parameters. Then, in vivo DW data with different numbers of low b-values and different number of excitations (NEX) were acquired. Finally, least-squares (LSQ) and Bayesian shrinkage prior (BSP) fitting methods were implemented to estimate IVIM parameters. The influence of the number of low b-values on IVIM parameters was analyzed in terms of relative error (RE) and structural similarity (SSIM). The results showed that the influence of the number of low b-values on IVIM parameters is variable. LSQ is more dependent on the number of low b-values than BSP, but the latter is more sensitive to noise.

Mono, bi- and tri-exponential diffusion MRI modelling for renal solid masses and comparison with histopathological findings

PURPOSE

To compare diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and tri-exponential models of the diffusion magnetic resonance imaging (MRI) signal for the characterization of renal lesions in relationship to histopathological findings.

METHODS

Sixteen patients planned to undergo nephrectomy for kidney tumour were scanned before surgery at 3 T magnetic resonance imaging (MRI), with T2-weighted imaging, DTI and diffusion weighted imaging (DWI) using ten b-values. DTI parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squared fitting of the DTI data and bi-, and tri-exponential fit parameters (Dbi, fstar,and Dtri, ffast,finterm) using a nonlinear fit of the multiple b-value DWI data. Average parameters were calculated for regions of interest, selecting the lesions and healthy kidney tissue. Tumour type and specificities were determined after surgery by histological examination. Mean parameter values of healthy tissue and solid lesions were compared using a Wilcoxon-signed ranked test and MANOVA.

RESULTS

Thirteen solid lesions (nine clear cell carcinomas, two papillary renal cell carcinoma, one haemangioma and one oncocytoma) and four cysts were included. The mean MD of solid lesions are significantly (p < 0.05) lower than healthy cortex and medulla, (1.94 ± 0.32*10- 3 mm2/s versus 2.16 ± 0.12*10- 3 mm2/s and 2.21 ± 0.14*10- 3 mm2/s, respectively) whereas ffast is significantly higher (7.30 ± 3.29% versus 4.14 ± 1.92% and 4.57 ± 1.74%) and finterm is significantly lower (18.7 ± 5.02% versus 28.8 ± 5.09% and 26.4 ± 6.65%). Diffusion coefficients were high (≥2.0*10- 3 mm2/s for MD, 1.90*10- 3 mm2/s for Dbi and 1.6*10- 3 mm2/s for Dtri) in cc-RCCs with cystic structures and/or haemorrhaging and low (≤1.80*10- 3 mm2/s for MD, 1.40*10- 3 mm2/s for Dbi and 1.05*10- 3 mm2/s for Dtri) in tumours with necrosis or sarcomatoid differentiation.

CONCLUSION

Parameters derived from a two- or three-component fit of the diffusion signal are sensitive to histopathological features of kidney lesions.

A robust deconvolution method to disentangle multiple water pools in diffusion MRI

The diffusion-weighted magnetic resonance imaging (dMRI) signal measured in vivo arises from multiple diffusion domains, including hindered and restricted water pools, free water and blood pseudo-diffusion. Not accounting for the correct number of components can bias metrics obtained from model fitting because of partial volume effects that are present in, for instance, diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Approaches that aim to overcome this shortcoming generally make assumptions about the number of considered components, which are not likely to hold for all voxels. The spectral analysis of the dMRI signal has been proposed to relax assumptions on the number of components. However, it currently requires a clinically challenging signal-to-noise ratio (SNR) and accounts only for two diffusion processes defined by hard thresholds. In this work, we developed a method to automatically identify the number of components in the spectral analysis, and enforced its robustness to noise, including outlier rejection and a data-driven regularization term. Furthermore, we showed how this method can be used to take into account partial volume effects in DTI and DKI fitting. The proof of concept and performance of the method were evaluated through numerical simulations and in vivo MRI data acquired at 3 T. With simulations our method reliably decomposed three diffusion components from SNR = 30. Biases in metrics derived from DTI and DKI were considerably reduced when components beyond hindered diffusion were taken into account. With the in vivo data our method determined three macro-compartments, which were consistent with hindered diffusion, free water and pseudo-diffusion. Taking free water and pseudo-diffusion into account in DKI resulted in lower mean diffusivity and higher fractional anisotropy values in both gray and white matter. In conclusion, the proposed method allows one to determine co-existing diffusion compartments without prior assumptions on their number, and to account for undesired signal contaminations within clinically achievable SNR levels.

A Modified Tri-Exponential Model for Multi-b-value Diffusion-Weighted Imaging: A Method to Detect the Strictly Diffusion-Limited Compartment in Brain

Purpose: To present a new modified tri-exponential model for diffusion-weighted imaging (DWI) to detect the strictly diffusion-limited compartment, and to compare it with the conventional bi- and tri-exponential models.

Methods: Multi-b-value diffusion-weighted imaging (DWI) with 17 b-values up to 8,000 s/mm² were performed on six volunteers. The corrected Akaike information criterions (AICc) and squared predicted errors (SPE) were calculated to compare these three models.

Results: The mean f₀ values were ranging 11.9–18.7% in white matter ROIs and 1.2–2.7% in gray matter ROIs. In all white matter ROIs: the AICcs of the modified tri-exponential model were the lowest (p < 0.05 for five ROIs), indicating the new model has the best fit among these models; the SPEs of the bi-exponential model were the highest (p < 0.05), suggesting the bi-exponential model is unable to predict the signal intensity at ultra-high b-value. The mean ADC_very−slow values were extremely low in white matter (1–7 × 10⁻⁶ mm²/s), but not in gray matter (251–445 × 10⁻⁶ mm²/s), indicating that the conventional tri-exponential model fails to represent a special compartment.

Conclusions: The strictly diffusion-limited compartment may be an important component in white matter. The new model fits better than the other two models, and may provide additional information.

REnal Flow and Microstructure AnisotroPy (REFMAP) MRI in Normal and Peritumoral Renal Tissue

BACKGROUND

Diffusion-weighted imaging (DWI) provides insight into the pathophysiology underlying renal dysfunction. Variants of DWI include intravoxel incoherent motion (IVIM), which differentiates between microstructural diffusion and vascular or tubular flow, and diffusion tensor imaging (DTI), which quantifies diffusion directionality.

PURPOSE

To investigate the reproducibility of joint IVIM-DTI and compare controls to presurgical renal mass patients.

STUDY TYPE

Prospective cross-sectional.

SUBJECTS

Thirteen healthy controls and ten presurgical renal mass patients were scanned. Ten controls were scanned twice to investigate reproducibility.

FIELD STRENGTH/SEQUENCE

Subjects were scanned on a 3T system using 10 b-values and 20 diffusion directions for IVIM-DTI in a study approved by the local Institutional Review Board.

ASSESSMENT

Retrospective coregistration and measurement of joint IVIM-DTI parameters were performed.

STATISTICAL ANALYSIS

Parameter reproducibility was defined as intraclass correlation coefficient (ICC) >0.7 and coefficient of variation (CV) <30%. Patient data were stratified by lesion side (contralateral/ipsilateral) for comparison with controls. Corticomedullary differentiation was evaluated.

RESULTS

In controls, the reproducible subset of REnal Flow and Microstructure AnisotroPy (REFMAP) parameters had average ICC = 0.82 and CV = 7.5%. In renal mass patients, medullary fractional anisotropy (FA) was significantly lower than in controls (0.227 ± 0.072 vs. 0.291 ± 0.044, P = 0.016 for the kidney contralateral to the mass and 0.228 ± 0.070 vs. 0.291 ± 0.044, P = 0.018 for the kidney ipsilateral). In the kidney ipsilateral to the mass, cortical D_p,radial was significantly higher than in controls (P = 0.012). Conversely, medullary D_p,axial was significantly lower in contralateral than ipsilateral kidneys (P = 0.027) and normal controls (P = 0.044).

DATA CONCLUSION

REFMAP-MRI parameters provide unique information regarding renal dysfunction. In presurgical renal mass patients, directional flow changes were noted that were not identified with IVIM analysis alone. Both contralateral and ipsilateral kidneys in patients show reductions in structural diffusivities and anisotropy, while flow metrics showed opposing changes in contralateral vs. ipsilateral kidneys.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Motion-Robust Spatially Constrained Parameter Estimation in Renal Diffusion-Weighted MRI by 3D Motion Tracking and Correction of Sequential Slices

In this work, we introduce a novel motion-robust spatially constrained parameter estimation (MOSCOPE) technique for kidney diffusion-weighted MRI. The proposed motion compensation technique does not require a navigator, trigger, or breath-hold but only uses the intrinsic features of the acquired data to track and compensate for motion to reconstruct precise models of the renal diffusion signal. We have developed a technique for physiological motion tracking based on robust state estimation and sequential registration of diffusion sensitized slices acquired within 200ms. This allows a sampling rate of 5Hz for state estimation in motion tracking that is sufficiently faster than both respiratory and cardiac motion rates in children and adults, which range between 0.8 to 0.2Hz, and 2.5 to 1Hz, respectively. We then apply the estimated motion parameters to data from each slice and use motion-compensated data for 1) robust intra-voxel incoherent motion (IVIM) model estimation in the kidney using a spatially constrained model fitting approach, and 2) robust weighted least squares estimation of the diffusion tensor model. Experimental results, including precision of IVIM model parameters using bootstrap-sampling and in-vivo whole kidney tractography, showed significant improvement in precision and accuracy of these models using the proposed method compared to models based on the original data and volumetric registration.

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

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.