Is there evidence for more than two diffusion components in abdominal organs? - A magnetic resonance imaging study in healthy volunteers

Reproducibility of intravoxel incoherent motion quantification in the liver across field strengths and gradient hardware

PURPOSE

To evaluate reproducibility and interlobar agreement of intravoxel incoherent motion (IVIM) quantification in the liver across field strengths and MR scanners with different gradient hardware.

METHODS

Cramer-Rao lower bound optimization was performed to determine optimized monopolar and motion-robust 2D (b-value and first-order motion moment [M1]) IVIM-DWI acquisitions. Eleven healthy volunteers underwent diffusion MRI of the liver, where each optimized acquisition was obtained five times across three MRI scanners. For each data set, IVIM estimates (diffusion coefficient (D), pseudo-diffusion coefficients (d 1 * $$ {d}_1^{\ast } $$ andd 2 * $$ {d}_2^{\ast } $$ ), blood velocity SDs (Vb1 and Vb2), and perfusion fractions [f1 and f2]) were obtained in the right and left liver lobes using two signal models (pseudo-diffusion and M1-dependent physical) with and without T2 correction (fc1 and fc2) and three fitting techniques (tri-exponential region of interest-based full and segmented fitting and blood velocity SD distribution fitting). Reproducibility and interlobar agreement were compared across methods using within-subject and pairwise coefficients of variation (CVw and CVp), paired sample t-tests, and Bland-Altman analysis.

RESULTS

Using a combination of motion-robust 2D (b-M1) data acquisition, M1-dependent physical signal modeling with T2 correction, and blood velocity SD distribution fitting, multiscanner reproducibility with median CVw = 5.09%, 11.3%, 9.20%, 14.2%, and 12.6% for D, Vb1, Vb2, fc1, and fc2, respectively, and interlobar agreement with CVp = 8.14%, 11.9%, 8.50%, 49.9%, and 42.0%, respectively, was achieved.

CONCLUSION

Recently proposed advanced IVIM acquisition, signal modeling, and fitting techniques may facilitate reproducible IVIM quantification in the liver, as needed for establishment of IVIM-based quantitative biomarkers for detection, staging, and treatment monitoring of diseases.

Effect of simultaneous multislice imaging, slice properties, and repetition time on the measured magnetic resonance biexponential intravoxel incoherent motion in the liver

OBJECTIVES

This study aims to investigate the previously reported dependency of intravoxel incoherent motion (IVIM) parameters on simultaneous multislice (SMS) acquisition and repetition time (TR). This includes the influence of slice thickness, slice gaps, and slice order on measured IVIM parameters.

MATERIALS AND METHODS

Diffusion-weighted imaging (DWI) of the liver was performed on 10 healthy volunteers (aged 20-30 years) at 3T with a slice thickness of 5 mm, a slice gap of 5 mm, and a linear slice order. Diffusion-weighted images were acquired with 19 b-values (0-800 s/mm2) using both conventional slice excitation with an acceleration factor of one (AF1) and SMS excitation with an acceleration factor of three (AF3). Each of these measurements were carried out with two repetition times (TRs)- 1,300 ms (prefix s) and 4,500 ms (prefix l)-resulting in four different combinations: sAF1, sAF3, lAF1, and lAF3. Five volunteers underwent additional measurements using a 10 mm slice thickness and with AF1. Median signal values in the liver were used to determine the biexponential IVIM parameters. Statistical significances were assessed using the Kruskal-Wallis test, Wilcoxon signed-rank test, and Student's t-test. In-silico investigations were also used to interpret the data.

RESULTS

There were no significant differences between the biexponential IVIM parameters acquired from sAF1, sAF3, lAF1, and lAF3. Median values of the perfusion fraction f were as follows: 29.9% (sAF1), 26.9% (sAF3), 28.1% (lAF1), and 27.5% (lAF3). In the 10 mm-thick slices, f decreased from 31.3% (lAF1) to 27.4% (sAF1) (p = 0.141).

CONCLUSION

The slice excitation mode did not appear to have any significant influence on the biexponential IVIM parameters. However, our simulations, as well as values reported from previous publications, show that slice thickness, slice gaps, and slice order are relevant and should thus be reported in IVIM studies.

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.

Image denoising and model-independent parameterization for IVIM MRI

Objective. To improve intravoxel incoherent motion imaging (IVIM) magnetic resonance Imaging quality using a new image denoising technique and model-independent parameterization of the signal versusb-value curve.Approach. IVIM images were acquired for 13 head-and-neck patients prior to radiotherapy. Post-radiotherapy scans were also acquired for five of these patients. Images were denoised prior to parameter fitting using neural blind deconvolution, a method of solving the ill-posed mathematical problem of blind deconvolution using neural networks. The signal decay curve was then quantified in terms of several area under the curve (AUC) parameters. Improvements in image quality were assessed using blind image quality metrics, total variation (TV), and the correlations between parameter changes in parotid glands with radiotherapy dose levels. The validity of blur kernel predictions was assessed by the testing the method's ability to recover artificial 'pseudokernels'. AUC parameters were compared with monoexponential, biexponential, and triexponential model parameters in terms of their correlations with dose, contrast-to-noise (CNR) around parotid glands, and relative importance via principal component analysis.Main results. Image denoising improved blind image quality metrics, smoothed the signal versusb-value curve, and strengthened correlations between IVIM parameters and dose levels. Image TV was reduced and parameter CNRs generally increased following denoising.AUCparameters were more correlated with dose and had higher relative importance than exponential model parameters.Significance. IVIM parameters have high variability in the literature and perfusion-related parameters are difficult to interpret. Describing the signal versusb-value curve with model-independent parameters like theAUCand preprocessing images with denoising techniques could potentially benefit IVIM image parameterization in terms of reproducibility and functional utility.

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.

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.

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.

Quantitative abdominal magnetic resonance imaging in children-special considerations

The use of quantitative MRI methods for assessment of the abdomen in children has become commonplace over the past decade. Increasingly employed methods include MR elastography, chemical shift encoded (CSE) MR imaging for determination of proton density fat fraction, diffusion-weighted imaging, and a variety of relaxometry techniques, such as T1 and T2* mapping. These techniques can be used in a variety of settings to distinguish normal from abnormal tissue as well as determine the severity of disease. The performance of quantitative MRI methods in the pediatric population presents unique challenges as compared to adult populations. These challenges relate to multiple factors, including patient size, pediatric physiology, inability to breath hold, and greater physical motion during the examination. The purpose of this review article is to review quantitative MRI methods that may be used in clinical practice to assess the pediatric abdomen and to discuss special considerations when performing these techniques in children.

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.

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.

Age and gender dependence of liver diffusion parameters and the possibility that intravoxel incoherent motion modeling of the perfusion component is constrained by the diffusion component

The aim of this study was to establish reference values for middle-aged subjects and to investigate the age and gender dependence of liver diffusion MRI parameters. The IVIM type of liver diffusion scan was based on a single-shot spin-echo-type echo-planar sequence using a 1.5 T magnet with 16 b-values. Diffusion-derived vessel density (DDVD)(b0b2) or DDVD(b0b10) was the signal difference between b = 0 and b = 2 (or b = 10) s/mm² images after removing visible vessels. IVIM analysis was performed with full fitting and segmented fitting, and with a threshold b-value of 60 or 200 s/mm² , and fitting started from b = 2 s/mm² . Thirty-one men (age range: 25-71 years) and 26 men (age: 22-69 years) had DDVD and IVIM analysis, respectively, while 37 women (age: 20-71 years) and 36 women (age: 20-71 years) had DDVD and IVIM analysis, respectively. DDVD results showed a significant age-related reduction for women. IVIM results for full fitting showed excellent agreement with those for segmented fitting using a threshold b of 60 s/mm² , but this was less good for results with a threshold b of 200 s/mm² . As age increased, female subjects' D_slow measure showed a significant reduction, while their PF and D_fast measures showed a significant increase. For the age group of 40-55 years, DDVD(b0b2), DDVD(b0b10), D_slow , PF and D_fast were 12.26 ± 3.90 au/pixel, 16.95 ± 5.45 au/pixel, 1.072 ± 0.067 (10^-3 mm² /s), 0.141 ± 0.025 and 61.0 ± 14.0 (10^-3 mm² /s) for men, and 13.35 ± 3.6 au/pixel, 17.20 ± 3.62 au/pixel, 1.069 ± 0.074 (10^-3 mm² /s), 0.119 ± 0.014 and 57.1 ± 13.2 (10^-3 mm² /s) for women, respectively. DDVD measure of this study suggest that aging is associated with a reduction in liver perfusion. There is a possibility that a lower D_slow measure is associated with artificially higher PF and D_fast measures, and that IVIM modeling of the perfusion component is constrained by the diffusion component.

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.

Advanced diffusion imaging of abdominal organs in different hydration states of the human body: stability of biomarkers

BACKGROUND

MR diffusion weighted imaging (DWI) may provide important information regarding the pathophysiology of parenchymal abdominal organs. The purpose of our study was to investigate the stability of imaging biomarkers of diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in abdominal parenchymal organs regarding two body hydration states.

METHODS

Ten healthy volunteers twice underwent DWI of abdominal organs using a double-refocused spin-echo echo-planar imaging sequences with 11 different b-values (ranging from 0 to 1,500 s/mm2): after 4 h of fluid deprivation; 45 min following 1000 ml of water intake. Four different diffusion models were evaluated and compared: standard DWI, DKI with mono-exponential fitting, multistep algorithm with variable b-value threshold for IVIM, combined IVIM-Kurtosis; in four abdominal organs: kidneys, liver, spleen and psoas muscle.

RESULTS

Diffusion parameters from all four models remained similar for the renal parenchyma before and after the water challenge. Significant differences were found for the liver, spleen, and psoas muscle. The largest effects were seen for: the liver parenchyma after the water challenge by means of IVIM model's true diffusion (p < 0.02); the spleen, for IVIM's perfusion fraction (p < 0.03), the psoas muscle for the ADC value (p < 0.02).

CONCLUSIONS

Herein, we showed that diffusion parameters of the kidney remain remarkably stable regarding the hydration status. This may be attributed to the kidney-specific compensatory mechanisms. For the liver, spleen and psoas muscle the diffusion parameters were sensitive to changes of the hydration. This phenomenon needs to be considered when evaluating diffusion data of these organs.

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.

B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer

Objective

This study aimed to find the optimal number of b-values for intravoxel incoherent motion (IVIM) imaging analysis, using simulated and in vivo data from cervical cancer patients.

Materials and Methods

Simulated data were generated using literature pooled means, which served as reference values for simulations. In vivo data from 100 treatment-naïve cervical cancer patients with IVIM imaging (13 b-values, scan time, 436 seconds) were retrospectively reviewed. A stepwise b-value fitting algorithm calculated optimal thresholds. Feed forward selection determined the optimal subsampled b-value distribution for biexponential IVIM fitting, and simplified IVIM modeling using monoexponential fitting was attempted. IVIM parameters computed using all b-values served as reference values for in vivo data.

Results

In simulations, parameters were accurately estimated with six b-values, or three b-values for simplified IVIM, respectively. In vivo data showed that the optimal threshold was 40 s/mm² for patients with squamous cell carcinoma and a subsampled acquisition of six b-values (scan time, 198 seconds) estimated parameters were not significantly different from reference parameters (individual parameter error rates of less than 5%). In patients with adenocarcinoma, the optimal threshold was 100 s/mm², but an optimal subsample could not be identified. Irrespective of the histological subtype, only three b-values were needed for simplified IVIM, but these parameters did not retain their discriminative ability.

Conclusion

Subsampling of six b-values halved the IVIM scan time without significant losses in accuracy and discriminative ability. Simplified IVIM is possible with only three b-values, at the risk of losing diagnostic information.

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.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

Comparison of tri-exponential decay versus bi-exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

OBJECTIVES

To determine whether bi- or tri-exponential models, and full or segmented fittings, better fit the intravoxel incoherent motion (IVIM) imaging signal of healthy livers.

METHODS

Diffusion-weighted images were acquired with a 3 T scanner using a respiratory-triggered echo-planar sequence and 16 b-values (0-800 s/mm² ). Eighteen healthy volunteers had their livers scanned twice in the same session, and then once in another session. Liver parenchyma region-of-interest-based measurements were processed with bi-exponential and tri-exponential models, with both full fitting and segmented fitting (threshold b-value = 200 s/mm² ).

RESULTS

With the signal of all scans averaged, bi-exponential model full fitting showed D_slow  = 1.14 × 10^-3  mm² /s, D_fast  = 193.6 × 10^-3  mm² /s, and perfusion fraction (PF) = 16.9%, and segmented fitting showed D_slow  = 0.98 × 10^-3  mm² /s, D_fast  = 42.2 × 10^-3  mm² /s, and PF = 23.3%. IVIM parameters derived from the tri-exponential model were similar for full fitting and segmented fitting, with slow (D'_slow  = 0.98 × 10^-3  mm² /s; F'_slow  = 76.4 or 76.6%), fast (D'_fast  = 15.1 or 15.4 × 10^-3  mm² /s; F'_fast  = 11.8 or 11.7%) and very fast (D'_Vfast  = 445.0 or 448.8 × 10^-3  mm² /s; F'_Vfast  = 11.8 or 11.7%) diffusion compartments. The tri-exponential model provided an overall better fit than the bi-exponential model. For the bi-exponential model, full fitting provided a better fit at very low and low b-values compared with segmented fitting, with the latter tending to underestimate D_fast ; however, the segmented method demonstrated lower error in signal prediction for high b-values. Compared with full fitting, tri-exponential segmented fitting offered better scan-rescan reproducibility.

CONCLUSION

For healthy liver, tri-exponential modeling is preferred to bi-exponential modeling. For the bi-exponential model, segmented fitting underestimates D_fast , but offers a more accurate estimation of D_slow .