An intravoxel oriented flow model for diffusion-weighted imaging of the kidney

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.

Investigation of renal perfusion and pathological changes in patients with acute kidney disease and tubulointerstitial nephritis using intravoxel incoherent motion and arterial spin labelling MRI: a prospective, observational study protocol

INTRODUCTION

Acute kidney injury (AKI) is a critical condition with a complex aetiology and different outcomes, where haemodynamic dysfunction, renal hypoperfusion and inflammation serve as key contributors to its development and progression. Early and accurate diagnosis is vital for initiating targeted treatments like fluid resuscitation, vasoactive agents or steroid therapy, which are essential for improving patient outcomes. Intravoxel incoherent motion (IVIM) MRI assesses both capillary perfusion and tissue water diffusion, while arterial spin labelling (ASL) MRI measures renal blood flow without the need for contrast. Research on combined use of IVIM and ASL MRI in patients with AKI is rare. This study aims to investigate the MRI characteristics of IVIM and ASL in patients with tubulointerstitial nephritis (TIN) and to explore their relationship with pathological findings and renal recovery.

METHODS AND ANALYSIS

Single-centre, prospective, observational cohort study of 30 patients with biopsy-proven TIN. Participants will undergo renal IVIM and ASL MRI within 7 days post-biopsy. The pathological assessments of active and chronic tubulointerstitial injuries will be semiscored using modified Banff criteria. The estimated glomerular filtration rate (eGFR) during follow-up and prevalence of chronic kidney disease at 3 and 6 months will be reported. An eGFR below 45 mL/min is considered a poor renal outcome.

ETHICS AND DISSEMINATION

The study has been reviewed and approved by the Ethics Committee of Peking University First Hospital and written informed consent will be obtained from all participants (2022Y503). The study results will be disseminated through publication in a relevant peer-reviewed journal and presentation at academic meetings to increase awareness and share findings with the scientific community.

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.

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.

Integrated intravoxel incoherent motion tensor and diffusion tensor brain MRI in a single fast acquisition

The acquisition of intravoxel incoherent motion (IVIM) data and diffusion tensor imaging (DTI) data from the brain can be integrated into a single measurement, which offers the possibility to determine orientation-dependent (tensorial) perfusion parameters in addition to established IVIM and DTI parameters. The purpose of this study was to evaluate the feasibility of such a protocol with a clinically feasible scan time below 6 min and to use a model-selection approach to find a set of DTI and IVIM tensor parameters that most adequately describes the acquired data. Diffusion-weighted images of the brain were acquired at 3 T in 20 elderly participants with cerebral small vessel disease using a multiband echoplanar imaging sequence with 15 b-values between 0 and 1000 s/mm² and six non-collinear diffusion gradient directions for each b-value. Seven different IVIM-diffusion models with 4 to 14 parameters were implemented, which modeled diffusion and pseudo-diffusion as scalar or tensor quantities. The models were compared with respect to their fitting performance based on the goodness of fit (sum of squared fit residuals, chi² ) and their Akaike weights (calculated from the corrected Akaike information criterion). Lowest chi² values were found using the model with the largest number of model parameters. However, significantly highest Akaike weights indicating the most appropriate models for the acquired data were found with a nine-parameter IVIM-DTI model (with isotropic perfusion modeling) in normal-appearing white matter (NAWM), and with an 11-parameter model (IVIM-DTI with additional pseudo-diffusion anisotropy) in white matter with hyperintensities (WMH) and in gray matter (GM). The latter model allowed for the additional calculation of the fractional anisotropy of the pseudo-diffusion tensor (with a median value of 0.45 in NAWM, 0.23 in WMH, and 0.36 in GM), which is not accessible with the usually performed IVIM acquisitions based on three orthogonal diffusion-gradient directions.

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.

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.

Short-Term Repeatability of in Vivo Cardiac Intravoxel Incoherent Motion Tensor Imaging in Healthy Human Volunteers

BACKGROUND

Intravoxel incoherent motion (IVIM) tensor imaging is a promising technique for diagnosis and monitoring of cardiovascular diseases. Knowledge about measurement repeatability, however, remains limited.

PURPOSE

To evaluate short-term repeatability of IVIM tensor imaging in normal in vivo human hearts.

STUDY TYPE

Prospective.

POPULATION

Ten healthy subjects without history of heart diseases.

FIELD STRENGTH/SEQUENCE

Balanced steady-state free-precession cine sequence and single-shot spin-echo echo planar IVIM tensor imaging sequence (9 b-values, 0-400 seconds/mm² and six diffusion-encoding directions) at 3.0 T.

ASSESSMENT

Subjects were scanned twice with an interval of 15 minutes, leaving the scanner between studies. The signal-to-noise ratio (SNR) was evaluated in anterior, lateral, septal, and inferior segments of the left ventricle wall. Fractional anisotropy (FA), mean diffusivity (MD), mean fraction (MF), and helix angle (HA) in the four segments were independently measured by five radiologists.

STATISTICAL TESTS

IVIM tensor indexes were compared between observers using a one-way analysis of variance or between scans using a paired t-test (normal data) or a Wilcoxon rank-sum test (non-normal data). Interobserver agreement and test-retest repeatability were assessed using the intraclass correlation coefficient (ICC), within-subject coefficient of variation (WCV), and Bland-Altman limits of agreements.

RESULTS

SNR of inferior segment was significantly lower than the other three segments, and inferior segment was therefore excluded from repeatability analysis. Interobserver repeatability was excellent for all IVIM tensor indexes (ICC: 0.886-0.972; WCV: 0.62%-4.22%). Test-retest repeatability was excellent for MD of the self-diffusion tensor (D) and MF of the perfusion fraction tensor (f_p ) (ICC: 0.803-0.888; WCV: 1.42%-9.51%) and moderate for FA and MD of the pseudo-diffusion tensor (D^* ) (ICC: 0.487-0.532; WCV: 6.98%-10.89%). FA of D and f_p and HA of D presented good test-retest repeatability (ICC: 0.732-0.788; WCV: 3.28%-8.71%).

DATA CONCLUSION

The D and f_p indexes exhibited satisfactory repeatability, but further efforts were needed to improve repeatability of D^* indexes.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Motion-compensated gradient waveforms for tensor-valued diffusion encoding by constrained numerical optimization

PURPOSE

Diffusion-weighted MRI is sensitive to incoherent tissue motion, which may confound the measured signal and subsequent analysis. We propose a "motion-compensated" gradient waveform design for tensor-valued diffusion encoding that negates the effects bulk motion and incoherent motion in the ballistic regime.

METHODS

Motion compensation was achieved by constraining the magnitude of gradient waveform moment vectors. The constraint was incorporated into a numerical optimization framework, along with existing constraints that account for b-tensor shape, hardware restrictions, and concomitant field gradients. We evaluated the efficacy of encoding and motion compensation in simulations, and we demonstrated the approach by linear and planar b-tensor encoding in a healthy heart in vivo.

RESULTS

The optimization framework produced asymmetric motion-compensated waveforms that yielded b-tensors of arbitrary shape with improved efficiency compared with previous designs for tensor-valued encoding, and equivalent efficiency to previous designs for linear (conventional) encoding. Technical feasibility was demonstrated in the heart in vivo, showing vastly improved data quality when using motion compensation. The optimization framework is available online in open source.

CONCLUSION

Our gradient waveform design is both more flexible and efficient than previous methods, facilitating tensor-valued diffusion encoding in tissues in which motion would otherwise confound the signal. The proposed design exploits asymmetric encoding times, a single refocusing pulse or multiple refocusing pulses, and integrates compensation for concomitant gradient effects throughout the imaging volume.

Investigation of intravoxel incoherent motion tensor imaging for the characterization of the in vivo human heart

PURPOSE

To investigate intravoxel incoherent motion (IVIM) tensor imaging of the in vivo human heart and elucidate whether the estimation of IVIM tensors is affected by the complexity of pseudo-diffusion components in myocardium.

METHODS

The cardiac IVIM data of 10 healthy subjects were acquired using a diffusion weighted spin-echo echo-planar imaging sequence along 6 gradient directions with 10 b values (0~400 s/mm² ). The IVIM data of left ventricle myocardium were fitted to the IVIM tensor model. The complexity of myocardial pseudo-diffusion components was reduced through exclusion of low b values (0 and 5 s/mm² ) from the IVIM curve-fitting analysis. The fractional anisotropy, mean fraction/mean diffusivity, and Westin measurements of pseudo-diffusion tensors (f_p and D*) and self-diffusion tensor (D), as well as the angle between the main eigenvector of f_p (or D*) and that of D, were computed and compared before and after excluding low b values.

RESULTS

The fractional anisotropy values of f_p and D* without low b value participation were significantly higher (P < .001) than those with low b value participation, but an opposite trend was found for the mean fraction/diffusivity values. Besides, after removing low b values, the angle between the main eigenvector of f_p (or D*) and that of D became small, and both f_p and D* tensors presented significant decrease of spherical components and significant increase of linear components.

CONCLUSION

The presence of multiple pseudo-diffusion components in myocardium indeed influences the estimation of IVIM tensors. The IVIM tensor model needs to be further improved to account for the complexity of myocardial microcirculatory network and blood flow.

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

This study aimed to demonstrate a reliable automatic segmentation method for independently separating reduced diffusion and decreased perfusion areas in ischemic stroke brains using constrained nonnegative matrix factorization (cNMF) pattern recognition in directional intravoxel incoherent motion MRI (IVIM-MRI). First, the feasibility of cNMF-based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for S₀ -normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from S₀ -normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM-MRI experiments (x, y and z diffusion-gradient directions, 20 b values at 7 T) were performed for normal (n = 4), sacrificed (n = 1, no flow) and ischemic stroke models (n = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double-exponential fitting. Consistent with the simulation, the double-exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion-gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF-based pattern recognition.

Optimal acquisition scheme for flow-compensated intravoxel incoherent motion diffusion-weighted imaging in the abdomen: An accurate and precise clinically feasible protocol

PURPOSE

Flow-compensated (FC) diffusion-weighted MRI (DWI) for intravoxel-incoherent motion (IVIM) modeling allows for a more detailed description of tissue microvasculature than conventional IVIM. The long acquisition time of current FC-IVIM protocols, however, has prohibited clinical application. Therefore, we developed an optimized abdominal FC-IVIM acquisition with a clinically feasible scan time.

METHODS

Precision and accuracy of the FC-IVIM parameters were assessed by fitting the FC-IVIM model to signal decay curves, simulated for different acquisition schemes. Diffusion-weighted acquisitions were added subsequently to the protocol, where we chose the combination of b-value, diffusion time and gradient profile (FC or bipolar) that resulted in the largest improvement to its accuracy and precision. The resulting two optimized FC-IVIM protocols with 25 and 50 acquisitions (FC-IVIMopt25 and FC-IVIMopt50 ), together with a complementary acquisition consisting of 50 diffusion-weighting (FC-IVIMcomp ), were acquired in repeated abdominal free-breathing FC-IVIM imaging of seven healthy volunteers. Intersession and intrasession within-subject coefficient of variation of the FC-IVIM parameters were compared for the liver, spleen, and kidneys.

RESULTS

Simulations showed that the performance of FC-IVIM improved in tissue with larger perfusion fraction and signal-to-noise ratio. The scan time of the FC-IVIMopt25 and FC-IVIMopt50 protocols were 8 and 16 min. The best in vivo performance was seen in FC-IVIMopt50 . The intersession within-subject coefficients of variation of FC-IVIMopt50 were 11.6%, 16.3%, 65.5%, and 36.0% for FC-IVIM model parameters diffusivity, perfusion fraction, characteristic time and blood flow velocity, respectively.

CONCLUSIONS

We have optimized the FC-IVIM protocol, allowing for clinically feasible scan times (8-16 min).

Diffusion tensor imaging of the abdominal organs: Influence of oriented intravoxel flow compartments

Water flow in partially oriented intravoxel compartments mimics an anisotropic fast-diffusion regime, which contributes to the signal attenuation in diffusion-weighted images. In the abdominal organs, this flow may reflect physiological fluid movements (eg, tubular urine flow in kidneys, or bile flow through the liver) and have a clinical relevance. This study investigated the influence of anisotropic intravoxel water flow on diffusion tensor imaging (DTI) of the abdominal organs. Diffusion-weighted images were acquired in five healthy volunteers using an EPI sequence with diffusion preparation (TR/TE: 1000 ms/71 ms; b-values: 0, 10, 20, 40, 70, 120, 250, 450, 700, 1000 s/mm² ; 12 noncollinear diffusion-encoding directions). DTI of liver and kidneys was performed assuming (i) monoexponential decay of the diffusion-weighted signal, and (ii) accounting for potential anisotropy of the fast-diffusion compartments using a tensorial generalization of the IVIM model. Additionally, potential dependency of the metrics of the tensors from the anatomical location was evaluated. Significant differences in the metrics of the diffusion tensor (DT) were found in both liver and kidneys when comparing the two models. In both organs, the trace and the fractional anisotropy of the DT were significantly higher in the monoexponential model than when accounting for perfusion. The comparison of areas of the liver proximal to the hilum with distal regions and of renal cortex with the medulla also proved a location dependency of the size of the fast-diffusion compartments. Pseudo-diffusion correction in DTI enables the assessment of the solid parenchyma regardless of the organ perfusion or other pseudo-diffusive fluid movements. This may have a clinical relevance in the assessment of parenchymal pathologies (eg, liver fibrosis). The fast pseudo-diffusion components present a detectable anisotropy, which may reflect the hepatic microcirculation or other sources of mesoscopic fluid movement in the abdominal organs.

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.

Acute renal impairment characterization using diffusion magnetic resonance imaging: Validation by histology

Diffusion magnetic resonance imaging has been demonstrated to be a simple, noninvasive and accurate method for the detection of renal microstructure and microcirculation, which are closely linked to renal function. Moreover, serum endothelin-1 (ET-1) was also reported as a good indicator of early renal injury. The aim of this study was to evaluate the feasibility and capability of diffusion MRI and ET-1 to detect acute kidney injury by an operation simulating high-pressure renal pelvic perfusion, which is commonly used during ureteroscopic lithotripsy. Histological findings were used as a reference. Fourteen New Zealand rabbits in an experimental group and 14 in a control group were used in this study. Diffusion tensor imaging and intravoxel incoherent motion diffusion-weighted imaging were acquired by a 3.0 T MRI scanner. Significant corticomedullary differences were found in the values of the apparent diffusion coefficient (ADC), pure tissue diffusion, volume fraction of pseudo-diffusion (fp) and fractional anisotropy (FA) (P < 0.05 for all) in both preoperation and postoperation experimental groups. Compared with the control group, the values of cortical fp_mean , medullary ADC_mean and FA_mean decreased significantly (P < 0.05) after the operation in the experimental group. Also, the change rate of medullary ADC_mean in the experimental group was more pronounced than that in the control group (P = 0.018). No significant change was found in serum ET-1 concentration after surgery in either the experimental (P = 0.80) or control (P = 0.17) groups. In the experimental group, histological changes were observed in the medulla, while no visible change was found in the cortex. This study demonstrated the feasibility of diffusion MRI to detect the changes of renal microstructure and microcirculation in acute kidney injury, with the potential to evaluate renal function. Moreover, the sensitivity of diffusion MRI to acute kidney injury appears to be superior to that of serum ET-1.

Renal Functional MRI and Its Application

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

LEVEL OF EVIDENCE

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

Placenta microstructure and microcirculation imaging with diffusion MRI

PURPOSE

To assess which microstructural models best explain the diffusion-weighted MRI signal in the human placenta.

METHODS

The placentas of nine healthy pregnant subjects were scanned with a multishell, multidirectional diffusion protocol at 3T. A range of multicompartment biophysical models were fit to the data, and ranked using the Bayesian information criterion.

RESULTS

Anisotropic extensions to the intravoxel incoherent motion model, which consider the effect of coherent orientation in both microvascular structure and tissue microstructure, consistently had the lowest Bayesian information criterion values. Model parameter maps and model selection results were consistent with the physiology of the placenta and surrounding tissue.

CONCLUSION

Anisotropic intravoxel incoherent motion models explain the placental diffusion signal better than apparent diffusion coefficient, intravoxel incoherent motion, and diffusion tensor models, in information theoretic terms, when using this protocol. Future work will aim to determine if model-derived parameters are sensitive to placental pathologies associated with disorders, such as fetal growth restriction and early-onset pre-eclampsia. Magn Reson Med 80:756-766, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning

The diffusion-weighted (DW) MR signal sampled over a wide range of b-values potentially allows for tissue differentiation in terms of cellularity, microstructure, perfusion, and T₂ relaxivity. This study aimed to implement a machine learning algorithm for automatic brain tissue segmentation from DW-MRI datasets, and to determine the optimal sub-set of features for accurate segmentation. DWI was performed at 3 T in eight healthy volunteers using 15 b-values and 20 diffusion-encoding directions. The pixel-wise signal attenuation, as well as the trace and fractional anisotropy (FA) of the diffusion tensor, were used as features to train a support vector machine classifier for gray matter, white matter, and cerebrospinal fluid classes. The datasets of two volunteers were used for validation. For each subject, tissue classification was also performed on 3D T₁ -weighted data sets with a probabilistic framework. Confusion matrices were generated for quantitative assessment of image classification accuracy in comparison with the reference method. DWI-based tissue segmentation resulted in an accuracy of 82.1% on the validation dataset and of 82.2% on the training dataset, excluding relevant model over-fitting. A mean Dice coefficient (DSC) of 0.79 ± 0.08 was found. About 50% of the classification performance was attributable to five features (i.e. signal measured at b-values of 5/10/500/1200 s/mm² and the FA). This reduced set of features led to almost identical performances for the validation (82.2%) and the training (81.4%) datasets (DSC = 0.79 ± 0.08). Machine learning techniques applied to DWI data allow for accurate brain tissue segmentation based on both morphological and functional 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.

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.

Intravoxel incoherent motion magnetic resonance imaging of the knee joint in children with juvenile idiopathic arthritis

BACKGROUND

MRI of synovitis relies on use of a gadolinium-based contrast agent. Diffusion-weighted MRI (DWI) visualises thickened synovium but is of limited use in the presence of joint effusion.

OBJECTIVE

To investigate the feasibility and diagnostic accuracy of diffusion-weighted MRI with intravoxel incoherent motion (IVIM) for diagnosing synovitis in the knee joint of children with juvenile idiopathic arthritis.

MATERIALS AND METHODS

Twelve consecutive children with confirmed or suspected juvenile idiopathic arthritis (10 girls, median age 11 years) underwent MRI with contrast-enhanced T1-weighted imaging and DWI at 1.5 T. Read-out segmented multi-shot DWI was acquired at b values of 0 s/mm², 200 s/mm², 400 s/mm² and 800 s/mm². We calculated the IVIM parameters perfusion fraction (f) and tissue diffusion coefficient (D). Diffusion-weighted images at b=800 s/mm², f parameter maps and post-contrast T1-weighted images were retrospectively assessed by two independent readers for synovitis using the Juvenile Arthritis MRI Scoring system.

RESULTS

Seven (58%) children showed synovial hypertrophy on contrast-enhanced imaging. Diagnostic ratings for synovitis on DWI and on f maps were fully consistent with contrast-enhanced imaging, the diagnostic reference. Two children had equivocal low-confidence assessments on DWI. Median f was 6.7±2.0% for synovitis, 2.1±1.2% for effusion, 5.0±1.0% for muscle and 10.6±5.7% for popliteal lymph nodes. Diagnostic confidence was higher based on f maps in three (25%) children and lower in one child (8%), as compared to DWI.

CONCLUSION

DWI with IVIM reliably visualises synovitis of the knee joint. Perfusion fraction maps differentiate thickened synovium from joint effusion and hence increase diagnostic confidence.