Error model for reduction of cardiac and respiratory motion effects in quantitative liver DW‐MRI

Diffusion‐weighted images of the liver exhibit signal dropout from cardiac and respiratory motion, particularly in the left lobe. These artifacts cause bias and variance in derived parameters that quantify intravoxel incoherent motion. Many models of diffusion have been proposed, but few separate attenuation from diffusion or perfusion from that of bulk motion. The error model proposed here (Beta*LogNormal) is intended to accomplish that separation by modeling stochastic attenuation from bulk motion as multiplication by a Beta‐distributed random variate. Maximum likelihood estimation with this error model can be used to derive intravoxel incoherent motion parameters separate from signal dropout, and does not require a priori specification of parameters to do so. Liver intravoxel incoherent motion parameters were derived for six healthy subjects under this error model and compared with least‐squares estimates. Least‐squares estimates exhibited bias due to cardiac and respiratory gating and due to location within the liver. Bias from these factors was significantly reduced under the Beta*LogNormal model, as was within‐organ parameter variance. Similar effects were appreciable in diffusivity maps in two patients with focal liver lesions. These results suggest that, relative to least‐squares estimation, the Beta*LogNormal model accomplishes the intended reduction of bias and variance from bulk motion in liver diffusion imaging. Magn Reson Med 70:1460–1469, 2013. © 2012 Wiley Periodicals, Inc.     

On the use of bayesian probability theory for analysis of exponential decay date: An example taken from intravoxel incoherent motion experiments

Traditionally, the method of nonlinear least squares (NLLS) analysis has been used to estimate the parameters obtained from exponential decay data. In this study, we evaluated the use of Bayesian probability theory to analyze such data; specifically, that resulting from intravoxel incoherent motion NMR experiments. Analysis was done both on simulated data to which different amounts of Gaussian noise had been added and on actual data derived from rat brain. On simulated data, Bayesian analysis performed substantially better than NLLS under conditions of relatively low signal-to-noise ratio. Bayesian probability theory also offers the advantages of: a) not requiring initial parameter estimates and hence not being susceptible to errors due to incorrect starting values and b) providing a much better representation of the uncertainty in the parameter estimates in the form of the probability density function. Bayesian analysis of rat brain data was used to demonstrate the shape of the probability density function from data sets of different quality.     

Enhancing pancreatic adenocarcinoma delineation in diffusion derived intravoxel incoherent motion f‐maps through automatic vessel and duct segmentation

Diffusion‐based intravoxel incoherent motion imaging has recently gained interest as a method to detect and characterize pancreatic lesions, especially as it could provide a radiation‐ and contrast agent‐free alternative to existing diagnostic methods. However, tumor delineation on intravoxel incoherent motion‐derived parameter maps is impeded by poor lesion‐to‐pancreatic duct contrast in the f‐maps and poor lesion‐to‐vessel contrast in the D‐maps. The distribution of the diffusion and perfusion parameters within vessels, ducts, and tumors were extracted from a group of 42 patients with pancreatic adenocarcinoma. Clearly separable combinations of f and D were observed, and receiver operating characteristic analysis was used to determine the optimal cutoff values for an automated segmentation of vessels and ducts to improve lesion detection and delineation on the individual intravoxel incoherent motion‐derived maps. Receiver operating characteristic analysis identified f = 0.28 as the cutoff for vessels (Area under the curve (AUC) = 0.901) versus tumor/duct and D = 1.85 μm²/ms for separating duct from tumor tissue (AUC = 0.988). These values were incorporated in an automatic segmentation algorithm and then applied to 42 patients. This yielded clearly improved tumor delineation compared to individual intravoxel incoherent motion‐derived maps. Furthermore, previous findings that indicated that the f value in pancreatic cancer is strongly reduced compared to healthy pancreatic tissue were reconfirmed. Magn Reson Med, 2011. © 2011 Wiley Periodicals, Inc.     

Extension of the intravoxel incoherent motion model to non‐gaussian diffusion in head and neck cancer

Purpose:

To extend the intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) model to restricted diffusion and to simultaneously quantify the perfusion and restricted diffusion parameters in neck nodal metastases.

Materials and Methods:

The non‐Gaussian (NG)‐IVIM model was developed and tested on diffusion‐weighted MRI data collected on a 1.5‐Tesla MRI scanner from eight patients with head and neck cancer. Voxel‐wise parameter quantification was performed by using a noise‐rectified least‐square fitting method. The NG‐IVIM, IVIM, Kurtosis, and ADC (apparent diffusion coefficient) models were used for comparison. For each voxel, within the metastatic node, the optimal model was determined using the Bayesian Information Criterion. The voxel percentage preferred by each model was calculated and the optimal model map was generated. Monte Carlo simulations were performed to evaluate the accuracy and precision dependency of the new model.

Results:

For the eight neck nodes, the range of voxel percentage preferred by the NG‐IVIM model was 2.3–79.3%. The optimal modal maps showed heterogeneities within the tumors. The Monte Carlo simulations demonstrated that the accuracy and precision of the NG‐IVIM model improved by increasing signal‐to‐noise ratio and b value.

Conclusion:

The NG‐IVIM model characterizes perfusion and restricted diffusion simultaneously in neck nodal metastases. J. Magn. Reson. Imaging 2012;36:1088–1096. © 2012 Wiley Periodicals, Inc.     

Comprehensive framework for accurate diffusion MRI parameter estimation

During the last decade, many approaches have been proposed for improving the estimation of diffusion measures. These techniques have already shown an increase in accuracy based on theoretical considerations, such as incorporating prior knowledge of the data distribution. The increased accuracy of diffusion metric estimators is typically observed in well‐defined simulations, where the assumptions regarding properties of the data distribution are known to be valid. In practice, however, correcting for subject motion and geometric eddy current deformations alters the data distribution tremendously such that it can no longer be expressed in a closed form. The image processing steps that precede the model fitting will render several assumptions on the data distribution invalid, potentially nullifying the benefit of applying more advanced diffusion estimators. In this work, we present a generic diffusion model fitting framework that considers some statistics of diffusion MRI data. A central role in the framework is played by the conditional least squares estimator. We demonstrate that the accuracy of that particular estimator can generally be preserved, regardless the applied preprocessing steps, if the noise parameter is known a priori. To fulfill that condition, we also propose an approach for the estimation of spatially varying noise levels. Magn Reson Med, 70:972–984, 2013. © 2012 Wiley Periodicals, Inc.     

Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges

OBJECTIVE: Diffusion-weighted MRI is increasingly applied in the body. It has been recognized for some time, on the basis of scientific experiments and studies in the brain, that the calculation of apparent diffusion coefficient by simple monoexponential relationship between MRI signal and b value does not fully account for tissue behavior. However, appreciation of this fact in body diffusion MRI is relatively new, because technologic advancements have only recently enabled high-quality body diffusion-weighted images to be acquired using multiple b values. There is now increasing interest in the radiologic community to apply more sophisticated analytic approaches, such as those based on the principles of intravoxel incoherent motion, which allows quantitative parameters that reflect tissue microcapillary perfusion and tissue diffusivity to be derived. CONCLUSION: In this review, we discuss the principles of intravoxel incoherent motion as applied to body diffusion-weighted MRI. The evidence for the technique in measuring tissue perfusion is presented and the emerging clinical utility surveyed. The requisites and challenges of quantitative evaluation beyond simple monoexponential relationships are highlighted.     

Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer

Diffusion‐weighted imaging plays important roles in cancer diagnosis, monitoring, and treatment. Although most applications measure restricted diffusion by tumor cellularity, diffusion‐weighted imaging is also sensitive to vascularity through the intravoxel incoherent motion effect. Hypervascularity can confound apparent diffusion coefficient measurements in breast cancer. We acquired multiple b‐value diffusion‐weighted imaging at 3 T in a cohort of breast cancer patients and performed biexponential intravoxel incoherent motion analysis to extract tissue diffusivity (D_t), perfusion fraction (f_p), and pseudodiffusivity (D_p). Results indicated significant differences between normal fibroglandular tissue and malignant lesions in apparent diffusion coefficient mean (±standard deviation) values (2.44 ± 0.30 vs. 1.34 ± 0.39 μm²/msec, P < 0.01) and D_t (2.36 ± 0.38 vs. 1.15 ± 0.35 μm²/msec, P < 0.01). Lesion diffusion‐weighted imaging signals demonstrated biexponential character in comparison to monoexponential normal tissue. There is some differentiation of lesion subtypes (invasive ductal carcinoma vs. other malignant lesions) with f_p (10.5 ± 5.0% vs. 6.9 ± 2.9%, P = 0.06), but less so with D_t (1.14 ± 0.32 μm²/msec vs. 1.18 ± 0.52 μm²/msec, P = 0.88) and D_p (14.9 ± 11.4 μm²/msec vs. 16.1 ± 5.7 μm²/msec, P = 0.75). Comparison of intravoxel incoherent motion biomarkers with contrast enhancement suggests moderate correlations. These results suggest the potential of intravoxel incoherent motion vascular and cellular biomarkers for initial grading, progression monitoring, or treatment assessment of breast tumors. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

Estimation of tensors and tensor‐derived measures in diffusional kurtosis imaging

This article presents two related advancements to the diffusional kurtosis imaging estimation framework to increase its robustness to noise, motion, and imaging artifacts. The first advancement substantially improves the estimation of diffusion and kurtosis tensors parameterizing the diffusional kurtosis imaging model. Rather than utilizing conventional unconstrained least squares methods, the tensor estimation problem is formulated as linearly constrained linear least squares, where the constraints ensure physically and/or biologically plausible tensor estimates. The exact solution to the constrained problem is found via convex quadratic programming methods or, alternatively, an approximate solution is determined through a fast heuristic algorithm. The computationally more demanding quadratic programming‐based method is more flexible, allowing for an arbitrary number of diffusion weightings and different gradient sets for each diffusion weighting. The heuristic algorithm is suitable for real‐time settings such as on clinical scanners, where run time is crucial. The advantage offered by the proposed constrained algorithms is demonstrated using in vivo human brain images. The proposed constrained methods allow for shorter scan times and/or higher spatial resolution for a given fidelity of the diffusional kurtosis imaging parametric maps. The second advancement increases the efficiency and accuracy of the estimation of mean and radial kurtoses by applying exact closed‐form formulae. Magn Reson Med, 2011. © 2010 Wiley‐Liss, Inc.     

IVIM-DWI技术在肝脏弥漫性病变中的研究进展

在生物组织中体素内不相干运动(IVIM)包括体素内水分子扩散和微循环灌注,IVIM双指数模型可以精确描述DWI信号衰减与b值的关系,分别获取反映组织水分子扩散和微循环灌注的参数。近年来,IVIM成像在肝脏弥漫性病变的检测与分级中应用越来越多。主要阐述肝脏IVIM成像的原理、影响因素及可重复性以及在弥漫性病变中的诊断价值。     

Utility of Intravoxel Incoherent Motion MR Imaging for Distinguishing Recurrent Metastatic Tumor from Treatment Effect following Gamma Knife Radiosurgery: Initial Experience

BACKGROUND AND PURPOSE:Intravoxel incoherent motion MR imaging can simultaneously measure the diffusion and perfusion characteristics of brain tumors. Our aim was to determine the utility of intravoxel incoherent motion–derived perfusion and diffusion parameters for assessing the treatment response of metastatic brain tumor following gamma knife radiosurgery.MATERIALS AND METHODS:Ninety-one consecutive patients with metastatic brain tumor treated with gamma knife radiosurgery were assessed by using intravoxel incoherent motion imaging. Two readers independently calculated the 90th percentile and the 10th percentile histogram cutoffs for perfusion, normalized CBV, diffusion, and ADC. Areas under the receiver operating characteristic curve and interreader agreement were assessed.RESULTS:With the combination of the 90th percentile histogram cutoff for perfusion and the 10th percentile histogram cutoff for diffusion, the sensitivity and specificity for differentiating recurrent tumor and treatment were 79.5% and 92.3% for reader 1 and 84.6% and 94.2% for reader 2, respectively. With the combination of the 90th percentile histogram cutoff for normalized CBV and the 10th percentile histogram cutoff for ADC, the sensitivity and specificity for differentiating recurrent tumor and treatment were 69.2% and 100.0% for reader 1 and 74.3% and 100.0% for reader 2, respectively. Compared with the combination of 90th percentile histogram cutoff for normalized CBV and the 10th percentile histogram cutoff for ADC, adding intravoxel incoherent motion to 90th percentile histogram cutoff for normalized CBV substantially improved the diagnostic accuracy for differentiating recurrent tumor and treatment from 86.8% to 92.3% for reader 1 and from 89.0% to 93.4% for reader 2, respectively. The intraclass correlation coefficients between readers were higher for perfusion parameters (intraclass correlation coefficient range, 0.84–0.89) than for diffusion parameters (intraclass correlation coefficient range, 0.68–0.79).CONCLUSIONS:Following gamma knife radiosurgery, intravoxel incoherent motion MR imaging can be used as a noninvasive imaging biomarker for differentiating recurrent tumor from treatment effect in patients with metastatic brain tumor.

Perfusion MR imaging techniques have significantly advanced and can now provide information regarding tumor physiology. There are several reports suggesting the usefulness of dynamic susceptibility contrast-enhanced perfusion MR imaging for differentiating recurrent metastatic brain tumor from stereotactic radiosurgery–induced radiation necrosis.^1–3 However, quantitative brain perfusion measurement remains a challenge for currently available MR perfusion methods. DSC and dynamic contrast-enhanced MR imaging are inhibited by their signal nonlinearity, and arterial spin-labeling exhibits, in addition to a low signal-to-noise ratio, a strong dependence on the transit time.Le Bihan et al⁴ defined intravoxel incoherent motion (IVIM) as the microscopic translational motion occurring in each image voxel in MR imaging. In biologic tissue, this incoherent motion includes molecular diffusion of water and microcirculation of blood in the capillary network, referred to as “perfusion.” These 2 phenomena account for the biexponential decay of the signal intensity on DWI when different diffusion b-values are applied. With the IVIM theory, both true molecular diffusion and water molecule motion in the capillary network can be estimated by using a single diffusion imaging-acquisition technique. As opposed to DSC, dynamic contrast-enhanced imaging, and arterial spin-labeling, IVIM has a unique capillary dependence that is not sensitive to the coherent laminar flow of arteries and veins. The measurement of IVIM is intrinsically local (ie, the encoding and readout are performed at the same location).⁵In our clinical experience, the major advantage of IVIM MR imaging is that because it allows the simultaneous acquisition of diffusion and perfusion parameters, it can provide both measures within corresponding solid lesions without the requirement for a further coregistration processing step. In the current study, we attempted to validate the IVIM-derived perfusion and diffusion parameters by using the clinicoradiologic correlation in patients with post-gamma knife radiosurgery (GKRS) metastatic brain tumor. We also assessed the diagnostic accuracy and added value of the IVIM method for differentiating recurrent tumor from treatment effect, compared with the combination of DSC perfusion MR imaging and DWI, which has commonly been used as a parameter for brain tumor imaging.Our hypothesis was that the difference in vascularity between recurrent tumor and the treatment effect can be assessed by using an IVIM-derived perfusion fraction (f); and the combination of f and the true diffusion parameter (D) would show diagnostic performance comparable with the combination of normalized CBV (nCBV) and the ADC. The purpose of this study was to determine the utility of IVIM-derived perfusion and diffusion parameters for assessing the treatment response of metastatic brain tumor following GKRS.     

Magnetic resonance: perfusion and diffusion imaging

Summary The use of magnetic resonance imaging to detect normal and pathological problems of perfusion and diffusion is reviewed. Motion sensitised spin-echo images can be used to detect changes in slow flow velocity within a voxel (intravoxel coherent motion (IVCM) as well as intravoxel incoherent motion (IVIM) effects attributable to both diffusion and perfusion. Changes have been identified in a variety of brain diseases in the absence of changes in conventional images but the techniques are very vulnerable to motion artefact of all types. More rapid and more sensitive approaches using steady state free precision and echo-planer imaging are being investigated. Anisotropic diffusion imaging enables white matter tracts to be demonstrated within the brain and spinal cord as a function of their direction because diffusion of water across axons is much more restricted than it is along them. This technique provides a unique method for localisation of lesions and displays obvious changes in disease in which diffusion becomes less restricted.     

MRI在肝外胆管癌诊断中的应用

胆管癌是一种少见的恶性肿瘤,预后不良,大多数发生于肝外胆管。肝外胆管癌（EHCC）的定位诊断常依赖于影像检查,MRI为目前诊断EHCC常用的影像检查方法之一。随着MR技术的发展,越来越多的序列如扩散加权成像（DWI）、体素内不相干运动（IVIM）、扩散峰度成像（DKI）等应用于EHCC的诊断,并且可以对肿瘤的病理级别进行预测和评估,对判断病人的预后及肿瘤的复发具有重要意义。就不同MR成像序列在EHCC诊断中的应用予以综述。     

Inferring multiple maxima in intravoxel white matter fiber distribution

A new methodology is introduced that characterizes the intravoxel orientation distribution function (ODF) based on a single‐fiber model of the diffusion MRI signal. Using a Bayesian framework the probability of finding a fiber in a specific orientation is obtained. The proposed ODF estimation relies on a cigar‐like diffusion tensor model, the methodology is thus denominated Bayesian cigar‐like diffusion tensor (BCDT). This work makes two major contributions: 1) the study of single‐fiber models in detecting fibers with different volume fractions in a voxel, and 2) the introduction of the Nth‐root correction to improve the detection of fibers with smaller volume fractions, where N is the number of diffusion MRI measurements. It is demonstrated that the incomplete signal modeling fails to reconstruct the relative fiber volume fractions, especially when the intravoxel diffusion profiles have dissimilar contributions to the diffusion MRI signal. In this situation the fibers with smaller contributions are hardly detectable. The BCDT method proposed here reduces this effect by introducing the Nth‐root correction, making multiple fibers estimable. The performance of the new methodology is illustrated using synthetic and real data, as well as the data from a phantom of intersecting capillaries. Magn Reson Med 60:616–630, 2008. © 2008 Wiley‐Liss, Inc.     

Measurement reproducibility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases

Objective

To determine the measurement reproducibility of perfusion fraction f, pseudodiffusion coefficient D ^* and diffusion coefficient D in colorectal liver metastases and normal liver.

Methods

Fourteen patients with known colorectal liver metastases were examined twice using respiratory-triggered echo-planar DW-MRI with eight b values (0 to 900 s/mm²) 1 h apart. Regions of interests were drawn around target metastasis and normal liver in each patient to derive ADC (all b values), ADC_high (b values ≥100 s/mm²) and intravoxel incoherent motion (IVIM) parameters f, D ^* and D by least squares data fitting. Short-term measurement reproducibility of median ADC, ADC_high, f, D ^* and D values were derived from Bland–Altman analysis.

Results

The measurement reproducibility for ADC, ADC_high and D was worst in colorectal liver metastases (?21 % to +25 %) compared with liver parenchyma (?6 % to +8 %). Poor measurement reproducibility was observed for the perfusion-sensitive parameters of f (?75 % to +241 %) and D ^* (?89 % to +2,120 %) in metastases, and to a lesser extent the f (?24 % to +25 %) and D* (?31 % to +59 %) of liver.

Conclusions

Estimates of f and D ^* derived from the widely used least squares IVIM fitting showed poor measurement reproducibility. Efforts should be made to improve the measurement reproducibility of perfusion-sensitive IVIM parameters.

Key Points

? Quantitative diffusion-weighted MRI parameters are increasingly used for clinical management decisions. ? However perfusion-sensitive intravoxel incoherent motion (IVIM) parameters showed poor measurement reproducibility. ? Measurement reproducibility of IVIM parameters was worse in metastases than normal liver. ? Efforts to improve measurement reproducibility of IVIM parameters should be explored.     

Intravoxel partially coherent motion technique: Characterization of the anisotropy of skeletal muscle microvasculature

Purpose:

To propose a reformulation of the intravoxel incoherent motion (IVIM) technique exploiting the low b‐value diffusion‐weighted imaging regime that can characterize microcirculation of tissues perfused with partially coherent blood flow.

Materials and Methods:

The new methodology, termed intravoxel partially coherent motion (IVPCM) technique, is suitable for probing microcirculation in tissues with ordered microvasculature, such as skeletal muscle. We employ a subvoxel model utilizing a randomly oriented bundle of straight vessels whose orientation statistics are characterized by a Fisher axial distribution with concentration parameter K quantifying the anisotropy of the distribution (K = 0 indicates isotropic capillary orientation). The methodology is first validated with a proof‐of‐principle phantom experiment and is then applied to analyze the microvasculature of human calf muscle at rest.

Results:

The microcirculatory part of the diffusion‐weighted signal at b < 200 s/mm² is anisotropic. The variation of the diffusion‐weighted signal with b‐value exhibits stronger deviation from the expected monoexponential decay when the diffusion encoding gradient is applied parallel to the mean myofiber direction in the calf muscle of three healthy volunteers. The application of the model to data from the medial gastrocnemius and the soleus of the three volunteers gives results within the expected range for the mean microvascular volume fraction, the mean microflow velocity, and the parameter K.

Conclusion:

The proposed methodology has the capability of characterizing the anisotropy of the capillary network in vivo in a manner analogous to the capability of high b‐value diffusion to characterize the anisotropy of muscle fibers. J. Magn. Reson. Imaging 2010;31:942–953. ©2010 Wiley‐Liss, Inc.     

同时多层成像技术联合肝脏MR扩散成像的应用及展望

同时多层（SMS）成像技术与多种MRI序列联合应用可明显缩短成像时间。MR扩散成像,如常规扩散加权成像（DWI）、体素内不相干运动成像（IVIM）、扩散张量成像（DTI）和扩散峰度成像（DKI）能反映组织内水分子扩散、血流灌注、组织结构复杂性等微观特征,在肝脏病变检测和辅助定性中有重要价值。SMS与MR扩散成像联合后可明显缩短成像时间,利于各种MR扩散成像在肝脏中的广泛应用。综述SMS对肝脏扩散成像扫描速度的提升效率、对影像质量和定量参数的影响,以期推动SMS成像技术在临床中的广泛应用。     

Renal artery stenosis: in vivo perfusion MR imaging

The intravoxel incoherent motion (IVIM) model of perfusion and diffusion imaging was applied to an in vivo canine model of unilateral renal artery stenosis and was compared with relative renal blood flow determination with radioactive microspheres. The percentage relative renal blood flow as determined with radioactive microspheres correlated closely with the percentage apparent diffusion coefficient. If this method can be adapted to human imaging, it may provide a noninvasive means for detecting renal artery stenosis.     

扩散加权成像在卵巢肿瘤中的应用

扩散加权成像(DWI)是目前唯一能够检测生物组织内水分子扩散运动的无创方法 ,该种扩散运动可以通过表观扩散系数(ADC)来量化分析。扩散峰度成像(DKI)、体素内不相干运动(IVIM)成像、背景抑制扩散加权全身成像(DWIBS)等DWI新技术用于卵巢肿瘤的评估提高了卵巢肿瘤影像诊断的准确性。综述DWI及其新技术在卵巢肿瘤定性诊断、分期、疗效评估、预后判断中的作用及其潜在缺陷。     

DWI技术在肝外胆管细胞癌诊断、分期和 疗效评估中的研究进展

肝外胆管细胞癌（EHCC）是第二大原发性肝胆系统肿瘤,其恶性程度高,预后不良。扩散加权成像（DWI）是反映组织水分子扩散运动的常用无创性成像方法。近年来,DWI及体素内不相干运动（IVIM）、扩散张量成像（DTI）及扩散峰度成像（DKI）等衍生技术已广泛应用于EHCC的诊断、病理分期预测和监测以及疗效评估。就DWI及其衍生序列对EHCC应用的研究进展以及局限性和应用前景予以综述。     

Intravoxel incoherent motion diffusion imaging of the liver: Optimal b-value subsampling and impact on parameter precision and reproducibility

PurposeTo increase diffusion sampling efficiency in intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) of the liver by reducing the number of diffusion weightings (b-values).Materials and methodsIn this IRB approved HIPAA compliant prospective study, 53 subjects (M/F 38/15, mean age 52 ± 13 y) underwent IVIM DWI at 1.5 T using 16 b-values (0–800 s/mm²), with 14 subjects having repeat exams to assess IVIM parameter reproducibility. A biexponential diffusion model was used to quantify IVIM hepatic parameters (PF: perfusion fraction, D: true diffusion and D*: pseudo diffusion). All possible subsets of the 16 b-values were probed, with number of b values ranging from 4 to 15, and corresponding parameters were quantified for each subset. For each b-value subset, global parameter estimation error was computed against the parameters obtained with all 16 b-values and the subsets providing the lowest error were selected. Interscan estimation error was also evaluated between repeat exams to assess reproducibility of the IVIM technique in the liver. The optimal b-values distribution was selected such that the number of b-values was minimal while keeping parameter estimation error below interscan reproducibility error.ResultsAs the number of b-values decreased, the estimation error increased for all parameters, reflecting decreased precision of IVIM metrics. Using an optimal set of 4 b-values (0, 15, 150 and 800 s/mm²), the errors were 6.5, 22.8 and 66.1% for D, PF and D* respectively. These values lie within the range of test–retest reproducibility for the corresponding parameters, with errors of 12.0, 32.3 and 193.8% for D, PF and D* respectively.ConclusionA set of 4 optimized b-values can be used to estimate IVIM parameters in the liver with significantly shorter acquisition time (up to 75%), without substantial degradation of IVIM parameter precision and reproducibility compared to the 16 b-value acquisition used as the reference.