Rapid measurement of intravoxel incoherent motion (IVIM) derived perfusion fraction for clinical magnetic resonance imaging

Repeatability of quantitative T1rho magnetic resonance imaging in normal brain tissues at 3.0T

PURPOSE

T1rho imaging is a promising MRI technique for imaging of brain disease. This study aimed to assess the repeatability of quantitative T1rho imaging in the normal brain grey and white matter.

METHODS

The study prospectively recruited 30 healthy volunteers without a history of neurological diseases or brain injury, and T1rho was performed and quantified from three imaging sessions. Repeat measures analysis of variance (ANOVA) and within-subject coefficients of variation (wCoV) was used to detect differences in T1rho values between the three scans.

RESULTS

The results showed low wCoVs of less than 4.3% (range 0.92-4.27%) across all the brain structures. No significant differences were observed in T1rho measurement between the three scans (p > 0.05). The amygdala and hippocampus showed the highest T1rho values of 91.79 ± 2.55 msec and 91.07 ± 2.11 msec respectively, and the palladium and putamen had the lowest values of 67.60 ± 1.84 msec and 71.83 ± 1.85 msec respectively.

CONCLUSION

T1rho shows high test-retest repeatability for whole brain imaging in serial imaging sessions, indicating it to be a reliable sequence for quantitative brain imaging.

Quantitative IVIM parameters evaluating perfusion changes in brain parenchyma in patients newly diagnosed with acute leukemia: Compared with healthy participants

Purpose

To study the value of quantitative IVIM parameters in evaluating cerebral blood perfusion changes in patients newly diagnosed with acute leukemia (AL) by comparing them with healthy participants.

Materials and methods

This prospective study consecutively recruited 49 participants with newly diagnosed AL and 40 normal controls between July 2020 and September 2022. All participants underwent an MRI of the brain using an axial T₁-weighted and an IVIM sequence. The IVIM parameters (water diffusion coefficient, sADC, pseudoperfusion fraction, f; diffusion coefficient, D, pseudodiffusion coefficient, D ^*, and perfusion-diffusion ratio, PDR) and peripheral white blood cell (WBC) counts were obtained. An unpaired t-test or the Mann-Whitney U-test was performed to compare the differences in gray matter (GM) and white matter (WM) of healthy participants and AL patients and the differences in IVIM parameters between healthy participants and patients with AL. In addition, multivariate (logistic regression) analyses were used to identify independent predictors and then, the receiver operating characteristic curve (ROC) analyses were performed.

Results

40 healthy participants and 49 patients with newly diagnosed AL were evaluated. In healthy participants, sADC, PDR, D and f values of GM were significantly higher than those of WM (t = 5.844, t = 3.838, t = 7.711, z = -2.184, respectively, all P < 0.05). In AL patients, the D, f and sADC values of GM were significantly higher than those of WM (t = 3.450, t = 6.262, t = 4.053, respectively, all P < 0.05). The sADC and f value from AL patients were significantly lower than those from healthy participants in GM (z = -2.537, P = 0.011; and z = -2.583, P = 0.010, respectively) and WM (z = -2.969, P = 0.003; z = -2.923, P = 0.003, respectively). The WBC counts of AL patients were significantly higher than those of healthy participants (t = 3.147, P = 0.002). Multivariate analyses showed that the f values of GM and WM were independent predictors of AL (P = 0.030, and 0.010, respectively), with the optimal cut-off value at 7.08% (AUC ROC curve: 0.661, specificity: 11.4%, sensitivity: 98%) and 13.77% (AUC ROC curve: 0.682, specificity: 79.5%, sensitivity: 59.2%).

Conclusion

The IVIM parameters of brain parenchyma in patients newly diagnosed with AL differed from those of the healthy participants. The changes of cerebral blood flow perfusion are expected to provide new ideas for studying central nervous system infiltration in AL.

Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain

Intravoxel incoherent motion (IVIM) is a method that can provide quantitative information about perfusion in the human body, in vivo, and without contrast agent. Unfortunately, the IVIM perfusion parameter maps are known to be relatively noisy in the brain, in particular for the pseudo-diffusion coefficient, which might hinder its potential broader use in clinical applications. Therefore, we studied the conditions to produce optimal IVIM perfusion images in the brain. IVIM imaging was performed on a 3-Tesla clinical system in four healthy volunteers, with 16 b values 0, 10, 20, 40, 80, 110, 140, 170, 200, 300, 400, 500, 600, 700, 800, 900 s/mm2, repeated 20 times. We analyzed the noise characteristics of the trace images as a function of b-value, and the homogeneity of the IVIM parameter maps across number of averages and sub-sets of the acquired b values. We found two peaks of noise of the trace images as function of b value, one due to thermal noise at high b-value, and one due to physiological noise at low b-value. The selection of b value distribution was found to have higher impact on the homogeneity of the IVIM parameter maps than the number of averages. Based on evaluations, we suggest an optimal b value acquisition scheme for a 12 min scan as 0 (7), 20 (4), 140 (19), 300 (9), 500 (19), 700 (1), 800 (4), 900 (1) s/mm2.

Understanding diffusion-weighted MRI analysis: Repeatability and performance of diffusion models in a benign breast lesion cohort

Diffusion-weighted MRI (DWI) is an important tool for oncology research, with great clinical potential for the classification and monitoring of breast lesions. The utility of parameters derived from DWI, however, is influenced by specific analysis choices. The purpose of this study was to critically evaluate repeatability and curve-fitting performance of common DWI signal representations, for a prospective cohort of patients with benign breast lesions. Twenty informed, consented patients with confirmed benign breast lesions underwent repeated DWI (3 T) using: sagittal single-shot spin-echo echo planar imaging, bipolar encoding, TR/TE: 11,600/86 ms, FOV: 180 x 180 mm, matrix: 90 x 90, slices: 60 x 2.5 mm, iPAT: GRAPPA 2, fat suppression, and 13 b-values: 0-700 s/mm² . A phase-reversed scan (b = 0 s/mm² ) was acquired for distortion correction. Voxel-wise repeat-measures coefficients of variation (CoVs) were derived for monoexponential (apparent diffusion coefficient [ADC]), biexponential (intravoxel incoherent motion: f, D, D*) and stretched exponential (α, DDC) across the parameter histograms for lesion regions of interest (ROIs). Goodness-of-fit for each representation was assessed by Bayesian information criterion. The volume of interest (VOI) definition was repeatable (CoV 13.9%). Within lesions, and across both visits and the cohort, there was no dominant best-fit model, with all representations giving the best fit for a fraction of the voxels. Diffusivity measures from the signal representations (ADC, D, DDC) all showed good repeatability (CoV < 10%), whereas parameters associated with pseudodiffusion (f, D*) performed poorly (CoV > 50%). The stretching exponent α was repeatable (CoV < 12%). This pattern of repeatability was consistent over the central part of the parameter percentiles. Assumptions often made in diffusion studies about analysis choices will influence the detectability of changes, potentially obscuring useful information. No single signal representation prevails within or across lesions, or across repeated visits; parameter robustness is therefore a critical consideration. Our results suggest that stretched exponential representation is more repeatable than biexponential, with pseudodiffusion parameters unlikely to provide clinically useful biomarkers.

Analysis of Renal Diffusion-Weighted Imaging (DWI) Using Apparent Diffusion Coefficient (ADC) and Intravoxel Incoherent Motion (IVIM) Models

Analysis of renal diffusion-weighted imaging (DWI) data to derive markers of tissue properties requires careful consideration of the type, extent, and limitations of the acquired data. Alongside data quality and general suitability for quantitative analysis, choice of diffusion model, fitting algorithm, and processing steps can have consequences for the precision, accuracy, and reliability of derived diffusion parameters. Here we introduce and discuss important steps for diffusion-weighted image processing, and in particular give example analysis protocols and pseudo-code for analysis using the apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models. Following an overview of general principles, we provide details of optional steps, and steps for validation of results. Illustrative examples are provided, together with extensive notes discussing wider context of individual steps, and notes on potential pitfalls.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.

Intravoxel incoherent motion (IVIM) modeling of diffusion MRI during chemoradiation predicts therapeutic response in IDH wildtype glioblastoma

Background:

Prediction of early progression in glioblastoma may provide an opportunity to personalize treatment. Simplified intravoxel incoherent motion (IVIM) MRI offers quantitative estimates of diffusion and perfusion metrics. We investigated whether these metrics, during chemoradiation, could predict treatment outcome.

Methods:

38 patients with newly diagnosed IDH-wildtype glioblastoma undergoing 6-week/30-fraction chemoradiation had standardized post-operative MRIs at baseline (radiation planning), and at the 10th and 20th fractions. Non-overlapping T1-enhancing (T1C) and non-enhancing T2-FLAIR hyperintense regions were independently segmented. Apparent diffusion coefficient (ADC_T1C, ADC_T2-FLAIR) and perfusion fraction (f_T1C, f_T2-FLAIR) maps were generated with simplified IVIM modelling. Parameters associated with progression before or after 6.9 months (early vs late progression, respectively), overall survival (OS) and progression-free survival (PFS) were investigated.

Results:

Higher ADC_T2-FLAIR at baseline [Odds Ratio (OR) = 1.06, 95% CI 1.01–1.15, p = 0.025], lower f_T2-FLAIR at fraction 10 (OR = 2.11, 95% CI 1.04–4.27, p = 0.018), and lack of increase in ADC_T2-FLAIR at fraction 20 compared to baseline (OR = 1.12, 95% CI 1.02–1.22, p = 0.02) were associated with early progression. Combining ADC_T2-FLAIR at baseline, f_T2-FLAIR at fraction 10, ECOG and MGMT promoter methylation status significantly improved AUC to 90.3% compared to a model with only ECOG and MGMT promoter methylation status (p = 0.001). Using multivariable analysis, neither IVIM metrics were associated with OS but higher f_T2-FLAIR at fraction 10 (HR = 0.72, 95% CI 0.56–0.95, p = 0.018) was associated with longer PFS.

Conclusion:

ADC_T2-FLAIR at baseline, its lack of increase from baseline to fraction 20, or f_T2-FLAIR at fraction 10 significantly predicted early progression. f_T2-FLAIR at fraction 10 was associated with PFS.

Diagnostic Utility of the Simplified Perfusion Fraction for Identifying Myocardial Injury in Patients With Reperfused ST-segment Elevation Myocardial Infarction

BACKGROUND

Acute myocardial infarction (AMI) is a disease with high morbidity and mortality worldwide and the evaluation of myocardial injury and perfusion status following myocardial ischemia and reperfusion is of clinical value.

PURPOSE

To assess the diagnostic utility of simplified perfusion fraction (SPF) in differentiating salvage and infarcted myocardium and its predictive value for left ventricular remodeling in patients with reperfusion ST-segment elevation myocardial infarction (STEMI).

STUDY TYPE

Prospective.

POPULATION

Forty-one reperfused STEMI patients and 20 healthy volunteers.

FIELD STRENGTH/SEQUENCE

3.0T MRI. The MR examination included cine, T₂ -short tau inversion recovery (T₂ -STIR), first pass perfusiong (FPP)，phase sensitive inversion recovery (PSIR), and diffusion-weighted imaging (DWI).

ASSESSMENT

SPF values among different myocardium regions (infarcted, salvaged, remote, and MVO) and stages of reperfused STEMI patients as well as normal controls were measured. The diagnostic utility of SPF values in differentiating salvaged and infarcted myocardium was assessed.

STATISTICAL ANALYSIS

Independent t-test and the Mann-Whitney U-test. Logistic regression.

RESULTS

SPF values in healthy controls were not significantly different than SPF values in the remote myocardium of patients (40.09 ± 1.47% vs. 40.28 ± 1.93%, P = 0.698). In reperfusion STEMI patients, SPF values were lower in infarcted myocardium compared to remote and salvaged myocardium (32.15 ± 2.36% vs. 40.28 ± 1.93%, P < 0.001; 32.15 ± 2.36% vs. 36.68 ± 2.71%, P < 0.001). SPF values of infarcted myocardium showed a rebound increase from acute to convalescent stages (32.15 ± 2.36% vs. 34.69 ± 3.69%, P < 0.001). When differentiating infarcted and salvaged myocardium, SPF values demonstrated an area under the curve (AUC) of 0.89 (sensitivity 85.4%, specificity 80.5%, cutoff 34.42%). Lower SPF values were associated with lower odds ratio (OR = 0.304) of left ventricular remodeling after adjusting for potential confounders with a confidence interval (CI) of 0.129-0.717, P = 0.007.

DATA CONCLUSION

SPF might be able to differentiate salvaged and infarcted myocardium and is a strong predictor of left ventricular remodeling in reperfused STEMI patients. Level of Evidence 2 Technical Efficacy Stage 2.

Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases

Traditional magnetic resonance (MR) diffusion-weighted imaging (DWI) uses a single exponential model to obtain the apparent diffusion coefficient to quantitatively reflect the diffusion motion of water molecules in living tissues, but it is affected by blood perfusion. Intravoxel incoherent motion (IVIM)-DWI utilizes a double-exponential model to obtain information on pure water molecule diffusion and microcirculatory perfusion-related diffusion, which compensates for the insufficiency of traditional DWI. In recent years, research on the application of IVIM-DWI in the diagnosis and treatment of hepatic diseases has gradually increased and has achieved considerable progress. This study mainly reviews the basic principles of IVIM-DWI and related research progress in the diagnosis and treatment of hepatic diseases.

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion-weighted MRI

In this study, we evaluate whether diffusion-weighted magnetic resonance imaging (DW-MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW-MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b-values ranging from 0 to 1000 s/mm² . DW-MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo-diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW-MRI data using the biexponential model with the same b-values. Rician noise was added to generate DW-MRI data with various signal-to-noise ratio (SNR) levels. The experimental results showed that the denoised DW-MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20-40). Simulations and experiments show that brain DW-MRI data after denoising can provide a reliable estimation of IVIM parameters.

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.

Impact of b-Value Sampling Scheme on Brain IVIM Parameter Estimation in Healthy Subjects

Purpose:

Intravoxel incoherent motion (IVIM) analysis has attracted the interest of the clinical community due to its close relationship with microperfusion. Nevertheless, there is no clear reference protocol for its implementation; one of the questions being which b-value distribution to use. This study aimed to stress the importance of the sampling scheme and to show that an optimized b-value distribution decreases the variance associated with IVIM parameters in the brain with respect to a regular distribution in healthy volunteers.

Methods:

Ten volunteers were included in this study; images were acquired on a 1.5T MR scanner. Two distributions of 16 b-values were used: one considered ‘regular’ due to its close association with that used in other studies, and the other considered ‘optimized’ according to previous studies. IVIM parameters were adjusted according to the bi-exponential model, using two-step method. Analysis was undertaken in ROI defined using in the Automated Anatomical Labeling atlas, and parameters distributions were compared in a total of 832 ROI.

Results:

Maps with fewer speckles were obtained with the ‘optimized’ distribution. Coefficients of variation did not change significantly for the estimation of the diffusion coefficient D but decreased by approximately 39% for the pseudo-diffusion coefficient estimation and by 21% for the perfusion fraction. Distributions of adjusted parameters were found significantly different in 50% of the cases for the perfusion fraction, in 80% of the cases for the pseudo-diffusion coefficient and 17% of the cases for the diffusion coefficient. Observations across brain areas show that the range of average values for IVIM parameters is smaller in the ‘optimized’ case.

Conclusion:

Using an optimized distribution, data are sampled in a way that the IVIM signal decay is better described and less variance is obtained in the fitted parameters. The increased precision gained could help to detect small variations in IVIM parameters.

Effect of intravoxel incoherent motion on diffusion parameters in normal brain

At very low diffusion weighting the diffusion MRI signal is affected by intravoxel incoherent motion (IVIM) caused by dephasing of magnetization due to incoherent blood flow in capillaries or other sources of microcirculation. While IVIM measurements at low diffusion weightings have been frequently used to investigate perfusion in the body as well as in malignant tissue, the effect and origin of IVIM in normal brain tissue is not completely established. We investigated the IVIM effect on the brain diffusion MRI signal in a cohort of 137 radiologically-normal patients (62 male; mean age = 50.2 ± 17.8, range = 18 to 94). We compared the diffusion tensor parameters estimated from a mono-exponential fit at b = 0 and 1000 s/mm² versus at b = 250 and 1000 s/mm². The asymptotic fitting method allowed for quantitative assessment of the IVIM signal fraction f* in specific brain tissue and regions. Our results show a mean (median) percent difference in the mean diffusivity of about 4.5 (4.9)% in white matter (WM), about 7.8 (8.7)% in cortical gray matter (GM), and 4.3 (4.2)% in thalamus. Corresponding perfusion fraction f* was estimated to be 0.033 (0.032) in WM, 0.066 (0.065) in cortical GM, and 0.033 (0.030) in the thalamus. The effect of f* with respect to age was found to be significant in cortical GM (Pearson correlation ρ ​= ​0.35, p ​= ​3*10^-5) and the thalamus (Pearson correlation ρ = 0.20, p = 0.022) with an average increase in f* of 5.17*10^-4/year and 3.61*10^-4/year, respectively. Significant correlations between f* and age were not observed for WM, and corollary analysis revealed no effect of gender on f*. Possible origins of the IVIM effect in normal brain tissue are discussed.

Optimization of b-value schemes for estimation of the diffusion coefficient and the perfusion fraction with segmented intravoxel incoherent motion model fitting

PURPOSE

Intravoxel incoherent motion (IVIM) modeling for estimation of the diffusion coefficient (D) and perfusion fraction (f) is increasingly popular, but no consensus on standard protocols exists. This study provides a framework for optimization of b-value schemes for reduced estimation uncertainty of D and f from segmented model fitting.

THEORY

Analytical expressions for uncertainties of D and f from segmented model fitting were derived as Cramer-Rao lower bounds (CRLBs).

METHODS

Optimized b-value schemes were obtained for 3 to 12 acquisitions and in the limit of infinitely many acquisitions through constrained minimization of the CRLBs, with b-values constrained to be 0 or 200 to 800 s/mm² . The optimized b-value scheme with eight acquisitions was compared with b-values linearly distributed in the allowed range using simulations and in vivo liver data from seven healthy volunteers.

RESULTS

All optimized b-value schemes contained exactly three unique b-values regardless of the total number of acquisitions (0, 200, and 800 s/mm² ) with repeated acquisitions distributed approximately as 1:2:2. Compared with linearly distributed b-values, the variability of estimates of D and f was reduced by approximately 30% as seen both in simulations and in repeated in vivo measurements.

CONCLUSION

The uncertainty of IVIM D and f estimates can be reduced by the use of optimized b-value schemes.

Clinical efficacy of simplified intravoxel incoherent motion imaging using three b-values for differentiating high- and low-grade gliomas

In this study, we evaluated the efficacy of intravoxel incoherent motion (IVIM)-derived parameters calculated with three b-values in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs) by comparing those calculated with multiple b-values. Ten patients with LGG (ages 35.1±12.1 yrs; 4 males, 6 females) and 21 patients with HGG (ages 60.6±19.1 yrs; 10 males, 11 females) who underwent subsequent surgical resections were examined with both IVIM imaging and histopathological analysis. The IVIM diffusion-weighted imaging was conducted using a single-shot echo planar sequence with 13 b-factors (0, 10, 20, 30, 50, 80, 100, 200, 300, 400, 600, 800, and 1000 sec/mm²) at 3T. In the conventional IVIM analysis, the perfusion fraction (f) and true diffusion coefficient (D) were calculated by biexponential fitting model with 13 b-values. In the simplified method with the selected three b-values (0, 300, and 1000 sec/mm²), D simply corresponds to the slope of a straight line passing through two logarithmic signal intensities (SIs) at the b-values of 300 and 1000 s/mm², and f corresponds to the difference between the intercept of this line and SI at the b-value of 0 sec/mm². The maximum f (f-max) and minimum D (D-min) was measured in each tumor. The f-max values calculated with three b-values (12.8±5.9%) were significantly lower than those with 13 b-values (17.3±7.5%, p<0.0001), but a good correlation and agreement were observed between these sets of f-max values (r = 0.79, ICC = 0.87). In the IVIM imaging with both three and 13 b-values, the HGGs showed significantly higher f-max values compared to the LGGs (p<0.001, respectively). The D-min values calculated with three b-values (1.06±0.31 ×10⁻³ mm²/sec) was not different from those with 13 b-values (1.07±0.33 ×10⁻³ mm²/sec), and an excellent correlation and agreement were found between them (r = 0.99, ICC = 0.99). The simplified IVIM imaging using three b-values can efficiently differentiate HGGs and LGGs.

Intravoxel incoherent motion MRI in neurological and cerebrovascular diseases

Intravoxel Incoherent Motion (IVIM) is a recently rediscovered noninvasive magnetic resonance imaging (MRI) method based on diffusion-weighted imaging. It enables the separation of the intravoxel signal into diffusion due to Brownian motion and perfusion-related contributions and provides important information on microperfusion in the tissue and therefore it is a promising tool for applications in neurological and neurovascular diseases. This review focuses on the basic principles and outputs of IVIM and details it major applications in the brain, such as stroke, tumor, and cerebral small vessel disease. A bi-exponential model that considers two different compartments, namely capillaries, and medium-sized vessels, has been frequently used for the description of the IVIM signal and may be important in those clinical applications cited before. Moreover, the combination of IVIM and arterial spin labeling MRI enables the estimation of water permeability across the blood-brain barrier (BBB), suggesting a potential imaging biomarker for disrupted-BBB diseases.