Spatially constrained incoherent motion method improves diffusion-weighted MRI signal decay analysis in the liver and spleen

Calculation of intravoxel incoherent motion parameter maps using a kernelized total difference-based method

Quantitative analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) has been explored for many clinical applications since its development. In particular, the intravoxel incoherent motion (IVIM) model for DW-MRI has been commonly utilized in various organs. However, because of the presence of excessive noise, the IVIM parameter maps obtained from pixel-wise fitting are often unreliable. In this study, we propose a kernelized total difference-based curve-fitting method to estimate the IVIM parameters. Simulated DW-MRI data at five signal-to-noise ratios (i.e., 10, 20, 30, 50, and 100) and real abdominal DW-MRI data acquired on a 1.5-T MRI scanner with nine b-values (i.e., 0, 10, 25, 50, 100, 200, 300, 400, and 500 s/mm2) and six diffusion-encoding gradient directions were used to evaluate the performance of the proposed method. The results were compared with those obtained by three existing methods: trust-region reflective (TRR) algorithm, Bayesian probability (BP), and deep neural network (DNN). Our simulation results showed that the proposed method outperformed the other three comparing methods in terms of root-mean-square error. Moreover, the proposed method could preserve small details in the estimated IVIM parameter maps. The experimental results showed that, compared with the TRR method, the proposed method as well as the BP (and DNN) method could reduce the overestimation of the pseudodiffusion coefficient and improve the quality of IVIM parameter maps. For all studied abdominal organs except the pancreas, both the proposed method and the BP method could provide IVIM parameter estimates close to the reference values; the former had higher precision. The kernelized total difference-based curve-fitting method has the potential to improve the reliability of IVIM parametric imaging.

Radiologists' Rating for Comparative Qualitative Assessment of Intravoxel Incoherent Motion Using Novel Analysis Methods

OBJECTIVE

The objective was to assess qualitative interpretability and quantitative precision and reproducibility of intravoxel incoherent motion ( IVIM) parametric images evaluated using novel IVIM analysis methods for diagnostic accuracy.

METHODS

Intravoxel incoherent motion datasets of 55 patients (male/female = 41:14; age = 17.8 ± 5.5 years) with histopathology-proven osteosarcoma were analyzed. Intravoxel incoherent motion parameters-diffusion coefficient ( D ), perfusion fraction ( f ), and perfusion coefficient ( D* )-were estimated using 5 IVIM analysis methods-(i) biexponential (BE) model, (ii) BE-segmented fitting 2-parameter (BESeg-2), (iii) BE-segmented fitting 1-parameter (BESeg-1), (iv) BE model with total variation penalty function (BE + TV), and (v) BE model with Huber penalty function (BE + HPF). Qualitative scoring in a 5-point Likert scale (uninterpretable: 1; poor: 2; fair: 3; good: 4; excellent: 5) was performed by 2 radiologists for 4 criteria: (a) tumor shape and margin, (b) morphologic correlation, (c) noise suppression, and (d) overall interpretability. Interobserver agreement was evaluated using Spearman rank-order correlation ( rs ). Precision and reproducibility were evaluated using within-subject coefficient of variation (wCV) and between-subject coefficient of variation (bCV).

RESULTS

BE + TV and BE + HPF produced significantly ( P < 10 -3 ) higher qualitative scores for D (fair-good [3.3-3.8]) than BE (poor [2.3]) and for D* (poor-fair [2.2-2.7]) and f (fair-good [3.2-3.8]) than BE, BESeg-2, and BESeg-1 ( D* : uninterpretable-poor [1.3-1.9] and f : poor-fair [1.5-3]). Interobserver agreement for qualitative scoring was rs = 0.48-0.59, P < 0.009. BE + TV and BE + HPF showed significantly ( P < 0.05) improved reproducibility in estimating D (wCV: 24%-31%, bCV: 21%-31% improvement) than the BE method and D* (wCV: 4%-19%, bCV: 5%-19% improvement) and f (wCV: 25%-49%, bCV: 25%-47% improvement) than BE, BESeg-2, and BESeg-1 methods.

CONCLUSIONS

BE + TV and BE + HPF demonstrated qualitatively and quantitatively improved IVIM parameter estimation and may be considered for clinical use further.

Intravoxel incoherent motion diffusion-weighted MRI for the evaluation of early spleen involvement in acute leukemia

Background

The spleen is a frequent organ of leukemia metastasis. This study aimed to investigate the value of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (MRI) for assessing pathologic changes in the spleen and identifying early spleen involvement in patients with acute leukemia (AL).

Methods

Patients with newly diagnosed AL and healthy controls were recruited between June 2020 and November 2022. All participants underwent abdominal IVIM diffusion-weighted imaging (DWI) at our hospital. IVIM parameters [pure diffusion coefficient (D); pseudo-diffusion coefficient (D*); and pseudo-perfusion fraction (f)] of the spleen were calculated by the segmented fitting method, and perfusion-diffusion ratio (PDR) was further calculated from the values of D, D* and f. Spleen volumes (SVs) were obtained by manually segmenting the spleen layer by layer. Clinical biomarkers of AL patients were collected. Patients were divided into splenomegaly group and normal SV group according to the individualized reference intervals for SV. IVIM parameters were compared among the control group, AL with normal SV group, and AL with splenomegaly group using one-way analysis of variance, followed by pairwise post hoc comparisons. The correlations of IVIM parameters with clinical biomarkers were analyzed in AL patients. The diagnostic performances of IVIM parameters and their combinations for differentiating among the three groups were compared.

Results

Seventy-nine AL patients (AL with splenomegaly: n=54; AL with normal SV: n=25) and 55 healthy controls were evaluated. IVIM parameters were significantly different among the three groups (P<0.001 for D, D* and f; P=0.001 for PDR). D and PDR showed significant differences between the control and AL with normal SV groups in pairwise comparisons (P<0.001, and P=0.031, respectively). D was correlated with white blood cell (WBC) counts (r=-0.424; 95% CI: -0.570, -0.211; P<0.001), lactate dehydrogenase (LDH) (r=-0.285; 95% CI: -0.486, -0.011; P=0.011), and bone marrow blasts (r=-0.283; 95% CI: -0.476, -0.067; P=0.012). D* (r=-0.276; 95% CI: -0.470, -0.025; P=0.014), f (r=0.514; 95% CI: 0.342, 0.664; P<0.001) and PDR (r=0.343; 95% CI: 0.208, 0.549; P=0.002) were correlated with LDH. The combination of IVIM parameters (AUC: 0.830; 95% CI: 0.729, 0.905) demonstrated better diagnostic efficacy than the single D* (AUC: 0.721; 95% CI: 0.608, 0.816; Delong test: Z=2.012, P=0.044) and f (AUC: 0.647; 95% CI: 0.532, 0.752; Delong test: Z=2.829, P=0.005), but was not significantly different from the single D (AUC: 0.756; 95% CI: 0.647, 0.846; Delong test: Z=1.676, P=0.094) in differentiating the splenomegaly group and normal SV group.

Conclusions

IVIM diffusion-weighted MRI could be a potential alternative for assessing pathologic changes in the spleen from cellularity and angiogenesis, and D and PDR may be viable indicators to identify early spleen involvement in patients with AL.

Real-time fetal brain tracking for functional fetal MRI

PURPOSE

To improve motion robustness of functional fetal MRI scans by developing an intrinsic real-time motion correction method. MRI provides an ideal tool to characterize fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion, particularly in functional MRI experiments acquiring multiple Echo-Planar-Imaging-based repetitions, for example, diffusion MRI or blood-oxygen-level-dependency MRI.

METHODS

A 3D UNet was trained on 125 fetal datasets to track the fetal brain position in each repetition of the scan in real time. This tracking, inserted into a Gadgetron pipeline on a clinical scanner, allows updating the position of the field of view in a modified echo-planar imaging sequence. The method was evaluated in real-time in controlled-motion phantom experiments and ten fetal MR studies (17 + 4-34 + 3 gestational weeks) at 3T. The localization network was additionally tested retrospectively on 29 low-field (0.55T) datasets.

RESULTS

Our method achieved real-time fetal head tracking and prospective correction of the acquisition geometry. Localization performance achieved Dice scores of 84.4% and 82.3%, respectively for both the unseen 1.5T/3T and 0.55T fetal data, with values higher for cephalic fetuses and increasing with gestational age.

CONCLUSIONS

Our technique was able to follow the fetal brain even for fetuses under 18 weeks GA in real-time at 3T and was successfully applied "offline" to new cohorts on 0.55T. Next, it will be deployed to other modalities such as fetal diffusion MRI and to cohorts of pregnant participants diagnosed with pregnancy complications, for example, pre-eclampsia and congenital heart disease.

Influence of saturation effects on biexponential liver intravoxel incoherent motion

PURPOSE

Studies on intravoxel incoherent motion (IVIM) imaging in the liver have been carried out with different acquisition protocols. The number of acquired slices and the distances between slices can influence IVIM measurements due to saturation effects, but these effects have often been disregarded. This study investigated differences in biexponential IVIM parameters between two slice settings.

METHODS

Fifteen healthy volunteers (21-30 years) were examined at a field strength of 3 T. Diffusion-weighted images of the abdomen were acquired with 16 b values (0-800 s/mm² ), with four slices for the few slices setting and 24-27 slices for the many slices setting. Regions of interest were manually drawn in the liver. The data were fitted with a monoexponential signal curve and a biexponential IVIM curve, and biexponential IVIM parameters were determined. The dependence on the slice setting was assessed with Student's t test for paired samples (normally distributed IVIM parameters) and the Wilcoxon signed-rank test (non-normally distributed parameters).

RESULTS

None of the parameters were significantly different between the settings. For few slices and many slices, respectively, the mean values (SDs) for D $$ D $$ were 1.21 μm 2 / ms $$ 1.21{\upmu \mathrm{m}}^2/\mathrm{ms} $$ ( 0.19 μm 2 / ms $$ 0.19\kern0.3em {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ) and 1.20 μm 2 / ms $$ 1.20{\upmu \mathrm{m}}^2/\mathrm{ms} $$ ( 0.11 μm 2 / ms $$ 0.11\kern0.3em {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ); for f $$ f $$ they were 29.7% (6.2%) and 27.7% (3.6%); and for D * $$ {D}^{\ast } $$ they were 8.76 ⋅ 10 - 2 mm 2 / s $$ 8.76\cdot {10}^{-2}{\mathrm{mm}}^2/\mathrm{s} $$ ( 4.54 ⋅ 10 - 2 mm 2 / s $$ 4.54\cdot {10}^{-2}\kern0.3em {\mathrm{mm}}^2/\mathrm{s} $$ ) and 8.71 ⋅ 10 - 2 mm 2 / s $$ 8.71\cdot {10}^{-2}{\mathrm{mm}}^2/\mathrm{s} $$ ( 4.06 ⋅ 10 - 2 mm 2 / s $$ 4.06\cdot {10}^{-2}\kern0.3em {\mathrm{mm}}^2/\mathrm{s} $$ ).

CONCLUSION

Biexponential IVIM parameters in the liver are comparable among IVIM studies that use different slice settings, with mostly negligible saturation effects. However, this may not hold for studies that use much shorter TR.

An unsupervised convolutional neural network method for estimation of intravoxel incoherent motion parameters

Objective. Intravoxel incoherent motion (IVIM) imaging obtained by fitting a biexponential model to multiple b-value diffusion-weighted magnetic resonance imaging (DW-MRI) has been shown to be a promising tool for different clinical applications. Recently, several deep neural network (DNN) methods were proposed to generate IVIM imaging. Approach. In this study, we proposed an unsupervised convolutional neural network (CNN) method for estimation of IVIM parameters. We used both simulated and real abdominal DW-MRI data to evaluate the performance of the proposed CNN-based method, and compared the results with those obtained from a non-linear least-squares fit (TRR, trust-region reflective algorithm) and a feed-forward backward-propagation DNN-based method. Main results. The simulation results showed that both the DNN- and CNN-based methods had lower coefficients of variation than the TRR method, but the CNN-based method provided more accurate parameter estimates. The results obtained from real DW-MRI data showed that the TRR method produced many biased IVIM parameter estimates that hit the upper and lower parameter bounds. In contrast, both the DNN- and CNN-based methods yielded less biased IVIM parameter estimates. Overall, the perfusion fraction and diffusion coefficient obtained from the DNN- and CNN-based methods were close to literature values. However, compared with the CNN-based method, both the TRR and DNN-based methods tended to yield increased pseudodiffusion coefficients (55%–180%). Significance. Our preliminary results suggest that it is feasible to estimate IVIM parameters using CNN.

Self-supervised IVIM DWI parameter estimation with a physics based forward model

PURPOSE

To assess the robustness and repeatability of intravoxel incoherent motion model (IVIM) parameter estimation for the diffusion-weighted MRI in the abdominal organs under the constraints of noisy diffusion signal using a novel neural network method.

METHODS

Clinically acquired abdominal scans of Crohn's disease patients were retrospectively analyzed with regions segmented in the kidney cortex, spleen, liver, and bowel. A novel IVIM parameter fitting method based on the principle of a physics guided self-supervised convolutional neural network that does not require reference parameter estimates for training was compared to a conventional non-linear least squares (NNLS) algorithm, and a voxelwise trained artificial neural network (ANN).

RESULTS

Results showed substantial increase in parameter robustness to the noise corrupted signal. In an intra-session repeatability experiment, the proposed method showed reduced coefficient of variation (CoV) over multiple acquisitions in comparison to conventional NLLS method and comparable performance to ANN. The use of D and f estimates from the proposed method led to the smallest misclassification error in linear discriminant analysis for characterization between normal and abnormal Crohn's disease bowel tissue. The fitting of D∗ parameter remains to be challenging.

CONCLUSION

The proposed method yields robust estimates of D and f IVIM parameters under the constraints of noisy diffusion signal. This indicates a potential for the use of the proposed method in conjunction with accelerated DW-MRI acquisition strategies, which would typically result in lower signal to noise ratio.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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).

A general-threshold filtering method for improving intravoxel incoherent motion parameter estimates

In this study, we present an image denoising method for diffusion-weighted magnetic resonance imaging (DW-MRI) data. Our aim is to improve the estimation of intravoxel incoherent motion (IVIM) parameters using denoised DW-MRI data. A general-threshold filtering (GTF) reconstruction via total variation minimization has been proposed to improve image quality in few-view computed tomography. Here, we applied the combination of GTF and total difference to image denoising. Voxel-wise IVIM analysis was performed using both real and simulated DW-MRI data. Using an institutional review board-approved protocol with written informed consent, DW-MRI imaging was performed at a 3 T hybrid PET/MR system in 10 patients with Hodgkin lymphoma lesions. A simulated phantom consisting of four organs (liver, pancreas, spleen and kidney) was used to generate noisy DW-MRI data according to the IVIM model at different noise levels. DW-MRI data were denoised before IVIM parameter estimation. The proposed image denoising method was compared with the image denoising method using joint rank and edge constraints (JREC). The results of simulated data show that at the lower signal-to-noise ratios the proposed image denoising method outperformed the JREC method in terms of the accuracy and precision of the IVIM parameter estimates. The experimental results also show that the proposed image denoising method could yield better parametric images than the JREC method in terms of noise reduction and edge preservation.

Relative enhanced diffusivity: noise sensitivity, protocol optimization, and the relation to intravoxel incoherent motion

OBJECTIVE

To explore the relationship between relative enhanced diffusivity (RED) and intravoxel incoherent motion (IVIM), as well as the impact of noise and the choice of intermediate diffusion weighting (b value) on the RED parameter.

MATERIALS AND METHODS

A mathematical derivation was performed to cast RED in terms of the IVIM parameters. Noise analysis and b value optimization was conducted by using Monte Carlo calculations to generate diffusion-weighted imaging data appropriate to breast and liver tissue at three different signal-to-noise ratios.

RESULTS

RED was shown to be approximately linearly proportional to the IVIM parameter f, inversely proportional to D and to follow an inverse exponential decay with respect to D*. The choice of intermediate b value was shown to be important in minimizing the impact of noise on RED and in maximizing its discriminatory power. RED was shown to be essentially a reparameterization of the IVIM estimates for f and D obtained with three b values.

CONCLUSION

RED imaging in the breast and liver should be performed with intermediate b values of 100 and 50 s/mm², respectively. Future clinical studies involving RED should also estimate the IVIM parameters f and D using three b values for comparison.

Liver intravoxel incoherent motion (IVIM) magnetic resonance imaging: a comprehensive review of published data on normal values and applications for fibrosis and tumor evaluation

A comprehensive literature review was performed on liver intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique and its applications. Heterogeneous data have been reported. IVIM parameters are magnetic field strength dependent to a mild extent. A lower Dslow (D) value at 3 T than at 1.5 T and higher perfusion fraction (PF) value at 3 T than at 1.5 T were noted. An increased number of b values are associated with increased IVIM parameter measurement accuracy. With the current status of art, IVIM technique is not yet capable of detecting early stage liver fibrosis and diagnosing liver fibrosis grades, nor can it differentiate liver tumors. Though IVIM parameters show promise for tumor treatment monitoring, till now how PF and Dfast (D*) add diagnostic value to Dslow or apparent diffusion coefficient (ADC) remains unclear. This paper shows the state-of-art IVIM MR technique is still not able to offer reliable measurement for liver. More works on the measurement robustness are warranted as they are essential to justify follow-up clinical studies on patients.

Technical advancements and protocol optimization of diffusion-weighted imaging (DWI) in liver

An area of rapid advancement in abdominal MRI is diffusion-weighted imaging (DWI). By measuring diffusion properties of water molecules, DWI is capable of non-invasively probing tissue properties and physiology at cellular and macromolecular level. The integration of DWI as part of abdominal MRI exam allows better lesion characterization and therefore more accurate initial diagnosis and treatment monitoring. One of the most technical challenging, but also most useful abdominal DWI applications is in liver and therefore requires special attention and careful optimization. In this article, the latest technical developments of DWI and its liver applications are reviewed with the explanations of the technical principles, recommendations of the imaging parameters, and examples of clinical applications. More advanced DWI techniques, including Intra-Voxel Incoherent Motion (IVIM) diffusion imaging, anomalous diffusion imaging, and Diffusion Kurtosis Imaging (DKI) are discussed.

Relationship between diffusion parameters derived from intravoxel incoherent motion MRI and perfusion measured by dynamic contrast-enhanced MRI of soft tissue tumors

Our aim was to evaluate the link between diffusion parameters measured by intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and the perfusion metrics obtained with dynamic contrast-enhanced (DCE) MRI in soft tissue tumors (STTs). Twenty-eight patients affected by histopathologically confirmed STT were included in a prospective study. All patients underwent both DCE MRI and IVIM DWI. The perfusion fraction f, diffusion coefficient D and perfusion-related diffusion coefficient D* were estimated using a bi-exponential function to fit the DWI data. DCE MRI was acquired with a temporal resolution of 3-5 s. Maps of the initial area under the gadolinium concentration curve (IAUGC), time to peak (TTP) and maximum slope of increase (MSI) were derived using commercial software. The relationships between the DCE MRI and IVIM DWI measurements were assessed by Spearman's test. To exclude false positive results under multiple testing, the false discovery rate (FDR) procedure was applied. The Mann-Whitney test was used to evaluate the differences between all variables in patients with non-myxoid and myxoid STT. No significant relationship was found between IVIM parameters and any DCE MRI parameters. Higher f and D*f values were found in non-myxoid tumors compared with myxoid tumors (p = 0.004 and p = 0.003, respectively). MSI was significantly higher in non-myxoid tumors than in myxoid tumors (p = 0.029). From the visual assessments of single clinical cases, both f and D*f maps were in satisfactory agreement with DCE maps in the extreme cases of an avascular mass and a highly vascularized mass, whereas, for tumors with slight vascularity or with a highly heterogeneous perfusion pattern, this association was not straightforward. Although IVIM DWI was demonstrated to be feasible in STT, our data did not support evident relationships between perfusion-related IVIM parameters and perfusion measured by DCE MRI.