New imaging techniques for liver diseases

Review

New imaging techniques for liver diseases Bernard E. Van Beers⇑, Jean-Luc Daire, Philippe Garteiser Laboratory of Imaging Biomarkers, UMR1149 INSERM-University Paris Diderot, Sorbonne Paris Cité, Department of Radiology, Beaujon University Hospital Paris Nord, Clichy, France

Summary Newly developed or advanced methods of ultrasonography and MR imaging provide combined anatomical and quantitative functional information about diffuse and focal liver diseases. Ultrasound elastography has a central role for staging liver fibrosis and an increasing role in grading portal hypertension; dynamic contrast-enhanced ultrasonography may improve tumor characterization. In clinical practice, MR imaging examinations currently include diffusion-weighted and dynamic MR imaging, enhanced with extracellular or hepatobiliary contrast agents. Moreover, quantitative parameters obtained with diffusion-weighted MR imaging, dynamic contrast-enhanced

MR imaging and MR elastography have the potential to characterize further diffuse and focal liver diseases, by adding information about tissue cellularity, perfusion, hepatocyte transport function and visco-elasticity. The multiparametric capability of ultrasonography and more markedly of MR imaging gives the opportunity for high diagnostic performance by combining imaging biomarkers. However, image acquisition and postprocessing methods should be further standardized and validated in multicenter trials. Ó 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Introduction

Keywords: Ultrasonography; Magnetic resonance imaging; Perfusion and diffusion imaging; Dynamic gadoxetate-enhanced MR imaging; Elastography; Imaging biomarkers; Liver diseases; Liver tumors. Received 18 June 2014; received in revised form 8 October 2014; accepted 11 October 2014 ⇑ Corresponding author. Address: Laboratory of Imaging Biomarkers and Department of Radiology, Beaujon University Hospital, 100 Boulevard du General Leclerc, 92110 Clichy, France. Tel.: +33 1 40 87 56 54; fax: +33 1 40 87 44 77. E-mail address: [email protected] (B.E. Van Beers). Abbreviations: AASLD, American Association for the Study of Liver Diseases; ADC, apparent diffusion coefficient; APRI, aspartate aminotransferase to platelets ratio index; ARFI, acoustic radiation force imaging; AUROC, area under the receiver operating curve; CT, computed tomography; D, pure diffusion coefficient; D⁄, perfusion-related diffusion coefficient; DCE, dynamic contrast-enhanced; DW, diffusion-weighted; EASL, European Association for the Study of the Liver; EFSUMB, European Federation of Societies for Ultrasound in Medicine and Biology; f, fraction of diffusion related to microcirculation; F, plasma flow; G⁄, shear wave modulus; Gd, storage modulus; Gl, loss modulus; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; IVIM, intravoxel incoherent motion; Ktrans, transfer constant; K1a, arterial transfer constant; K1p, portal venous transfer constant; K1t, total liver plasma transfer constant; MR, magnetic resonance; MRP, multidrug resistance protein; MTT, mean transit time; NASH, non-alcoholic steatohepatitis; OATP, organic anion transporting polypeptide; mRECIST, modified response evaluation criteria in solid tumors; RECIST, response evaluation criteria in solid tumors; STARD, standards for reporting diagnostic accuracy; vd, distribution volume; ve, volume of extravascular extracellular space; vp, plasma volume; WFUMB, World Federation for Ultrasound in Medicine and Biology.

Liver ultrasonography and magnetic resonance (MR) imaging is increasingly used for detecting, characterizing and assessing the response to treatment of focal and diffuse liver diseases [1–3]. Ultrasonography remains a first-line examination, but it has recently gained increasing capabilities due to the implementation of dynamic contrast-enhanced (DCE) studies and elastography. The quality and speed of MR imaging examinations have been substantially improved by the development of higher clinical field strengths, larger gradients, improved surface coils, and parallel imaging techniques [2]. Hepatobiliary contrast agents, such as gadoxetate, have been introduced for DCE MR imaging [4]. Relative to computed tomography (CT), MR imaging has several advantages, including lack of radiation, higher contrastto-noise ratios, and multiparametric capabilities [1]. Indeed, the pulse sequences at MR imaging can be adjusted to produce images that assess different tissue characteristics such as diffusion, perfusion, and visco-elasticity [2,3]. These functional characteristics can be assessed not only qualitatively, but also as quantitative parameters that provide useful imaging biomarkers [3].

Journal of Hepatology 2015 vol. xxx j xxx–xxx

Please cite this article in press as: Van Beers BE et al. New imaging techniques for liver diseases. J Hepatol (2015), http://dx.doi.org/10.1016/ j.jhep.2014.10.014

Review Key Points •

Dynamic contrast-enhanced ultrasonography has the potential to give similar diagnostic performance for single liver tumour assessment as dynamic contrastenhanced MR imaging and can provide quantitative perfusion information

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Dynamic ultrasound elastography has a central role in liver fibrosis staging and is increasingly used to grade portal hypertension

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Acoustic radiation force ultrasound elastography measurements are fully integrated into comprehensive ultrasound examinations of the liver

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In patients with hepatocellular carcinoma, the quantitative MR diffusion and perfusion parameters, determined one month after intra-arterial or antiangiogenic treatments, have been shown to be better predictors of patient outcome than the RECIST, mRECIST or EASL criteria

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Dynamic gadoxetate-enhanced MR imaging improves the assessment of focal and diffuse liver diseases relative to dynamic contrast-enhanced imaging with extracellular contrast agents by adding information about hepatocyte transport function during the hepatobiliary phase

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Several visco-elastic parameters including the stiffness, elasticity, viscosity and wave scattering coefficients can be obtained in whole liver and spleen with multifrequency MR elastography, potentially improving the characterization of multiple liver diseases, including fibrosis, inflammation, NASH, portal hypertension, and liver tumours

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Biomarkers obtained with diffusion imaging, perfusion - hepatocyte transport imaging and with elastography have to be further validated in multicentre studies and the methods of image acquisition and post-processing have to be standardized

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Given the multiparametric capabilities of MR imaging and ultrasonography, imaging biomarkers can be combined to further improve the detection and characterization of diffuse liver diseases and liver tumours and to assess their response to treatment

Ultrasonography Dynamic contrast-enhanced ultrasonography Method Dynamic contrast-enhanced ultrasonography is performed after intravenous injection of ultrasound contrast agents. Ultrasound contrast agents are blood agents that are composed of gas-filled microbubbles stabilized by a shell made of lipids, proteins or polymers. Because of the non-linear oscillation of the microbubbles at low to mid-high mechanical index, harmonic or non-linear imaging is used to increase the contrast-to-tissue-ratio relative to fundamental B-mode imaging [5].

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Liver tumors Dynamic contrast-enhanced ultrasonography improves the detection and characterization of focal liver lesions [5]. Technical and diagnostic guidelines for the detection, characterization, and treatment monitoring of liver lesions at contrast-enhanced ultrasonography have been published under the auspice of the World Federation for Ultrasound in Medicine and Biology (WFUMB) and the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) [6]. However, the diagnostic role of DCE ultrasonography relative to DCE-CT and MR imaging remains debated [7]. Besides DCE-CT and MR imaging, DCE ultrasonography was included in the diagnostic algorithm for suspected hepatocellular carcinoma (HCC) in liver cirrhosis in the 2005 recommendations of the American Association for the Study of Liver Diseases (AASLD) [8] and in the recommendations of the Japan society of hepatology [9]; however, it was not included in the recent updated versions of either AASLD or European Association for the Study of the Liver (EASL) guidelines [10,11]. Reasons for this change have been based on the fact that the typical hypervascularity and washout pattern of HCC may be observed in some intrahepatic cholangiocellular carcinomas at DCE ultrasonography without being observed at DCE MR imaging [12]. The different pattern observed at ultrasonography and MR imaging or CT may be explained by differences in the distribution volumes between the ultrasound microbubbles, which remain intravascular, and the small-molecular-weight CT and MR contrast materials, which instead distribute into the vascular and extravascular-extracellular spaces. Other reasons for the variable use of DCE ultrasonography are defect in standardization, dependence on the operator, variability of results related to the physical characteristics of any individual patient, and the lack in three-dimensional dynamic imaging [7]. In contrast, the real-time capability of DCE ultrasonography may be a benefit relative to CT and MR imaging for observing the transient signal intensity enhancement of hypervascular liver tumors such as HCCs [13]. A meta-analysis of sulphur hexafluoride microbubble enhanced ultrasonography reported that it could provide improved cost-effectiveness and similar diagnostic performance to DCE-CT and MR imaging for the assessment of focal liver lesions [14]. However, the authors highlighted limitations in the reporting of many studies of the review, and stressed the need for further high-quality studies, based on the standards for reporting diagnostic accuracy (STARD) criteria, which compare the performance of all three imaging modalities (DCE ultrasonography, CT, and MR imaging) in the same patients and provide standardized definitions of a positive imaging test for each target condition. Moreover, the effectiveness of DCE ultrasonography in the assessment of multiple lesions of the liver should also be considered [14]. Future perspectives in DCE ultrasonography include quantitative perfusion imaging and molecular imaging [5,15]. The in vivo feasibility of determining absolute tumor perfusion parameters at DCE ultrasonography with deconvolution of the tumor enhancement curve by the arterial input function has been shown [16]. In animal models, molecular imaging of angiogenesis and inflammation has been performed with targeted ultrasound contrast agents directed to surface receptor molecules expressed on the luminal side of activated endothelium, in response to either inflammatory or angiogenic stimuli [5]. However, the unspecific

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Please cite this article in press as: Van Beers BE et al. New imaging techniques for liver diseases. J Hepatol (2015), http://dx.doi.org/10.1016/ j.jhep.2014.10.014

JOURNAL OF HEPATOLOGY accumulation of microbubbles within Kupffer cells limits targeted imaging approaches in liver diseases [17]. Dynamic ultrasound elastography Method Dynamic elastography is based on the assessment of the propagation of shear waves within tissues to calculate the visco-elastic properties [18]. Displacements can be measured with ultrasonography or MR imaging and stress can be applied either externally or internally. In the former case, an external actuator is generally directly in contact with the skin. The latter case includes methods that apply a force internally, for example by using focused ultrasound pulses generating acoustic radiation force (ARF). Acoustic pulses are used to ‘‘push’’ tissue, as well as capture the resulting tissue motion [18]. External mechanical excitation may be either continuous or transient. With ultrasonography, transient pulses are usually used to avoid the problem of reflections caused by continuous vibration. Transient elastography (FibroscanÓ, Echosens, Paris, France) is a first-generation dynamic ultrasound elastography method. It relies on the application of a short external shear wave pulse that is tracked by using one-dimensional ultrasound imaging [19]. Second generation ultrasound elastography methods are based on ARF. ARF methods include acoustic radiation force imaging (ARFI) (Siemens Healthcare, Erlangen, Germany), supersonic shear imaging also called shear wave elastography (Supersonic Imagine, Aix en Provence, France) and shear wave dispersion ultrasound vibrometry (Philips Healthcare, Best, The Netherlands) [20–22]. Quantitative ARFI estimates shear wave speed by tracking the shear wave generated by the push at lateral offsets from the push location, whereas supersonic shear imaging uses ultrafast imaging at a frame rate up to 4000 frames per second to assess the displacements resulting from the shear wave propagation [18,23]. Because transient waves are usually used at ultrasound elastography, only the wave speed can be calculated. This speed is proportional to tissue stiffness or elasticity, if one assumes that tissues are purely elastic. In fact, biological tissues are visco-elastic because they are both liquid and solid. The viscoelasticity can be assessed with ultrasound elastography by using Voigt model fitting of the frequency-dependent wave speed dispersion [22]. However, the relevance of the Voigt model in human tissues remains controversial [24]. With the first generation transient elastography method, shear wave speed is measured in a cylindrical volume 10-mm wide, 40-mm long, located 25–65 mm below the skin surface. The Fibroscan is an ultrasound apparatus that is dedicated for assessing liver fibrosis. No conventional B-mode ultrasound image is available. The proper positioning of the elastography box within the liver can thus not be assessed, nor can transient elastography be performed in focal liver lesions. Second generation ARF-based elastography methods have advantages relative to transient elastography. First, the regions of interest for elasticity measurements are overlaid on conventional B mode images. Second, elastograms can be obtained in patients with ascites when using ARF based methods, but not with transient elastography. This is explained by the fact that focused ultrasound beams in contrast to shear waves do penetrate trough liquids. Third, as the shear waves are generated

internally with ARF methods, deeper regions of the liver can be assessed. However, the deepest regions of the liver can be difficult to evaluate, as the depth limit for ARFI and shear wave elastography has been reported to be 8 cm [25,26]. ARFI provides a single estimate of tissue stiffness in a small region of tissue (10  5 mm), whereas a whole elasticity map can be obtained within a region of interest with shear wave elastography [26]. Diffuse liver diseases Validation of dynamic elastography in liver diseases is ongoing. For liver fibrosis, transient elastography is currently the most validated method for the assessment of liver fibrosis, mainly in viral hepatitis [27]. Its diagnostic accuracy is better for cirrhosis than for significant fibrosis, with mean areas under the receiver operating characteristic curves (AUROCs) of 0.94 and 0.84 in patients with interpretable results [28]. The diagnostic accuracy of transient elastography for significant fibrosis is not high enough to recommend transient elastography as the sole examination in clinical practice [28–30]. Moreover, the main limitation of transient elastography is its limited applicability: in about 20% of the patients, examination fails or results are non-interpretable, mostly because of obesity, ascites or limited operator experience [31]. The accuracy of ARFI in liver fibrosis is reported to be similar to that of transient elastography, whereas a single center study suggests that shear wave elastography is more accurate than transient elastography for diagnosing significant fibrosis in HCV patients [32,33]. Besides the staging of liver fibrosis, ultrasound elastography is emerging as an accurate method for staging portal hypertension and detecting esophageal varices [34,35]. Liver tumors Some studies have assessed the potential role of second generation ultrasound elastography in characterizing liver tumors [25,26]. Despite the fact that significant overlap of lesion stiffness has been observed between benign and malignant lesions, ultrasound elastography might be useful for more specific clinical questions, such as the differentiation between adenoma and focal nodular hyperplasia as well as between hepatocellular and cholangiocellular carcinomas. Indeed, lesions of focal nodular hyperplasia are stiffer than adenomas (Fig. 1), and cholangiocellular carcinomas are stiffer than hepatocellular carcinomas [25,26]. Moreover, higher stiffness is observed in inflammatory than in steatotic adenomas [36]. Preliminary results suggest that combined DCE ultrasonography and ultrasound elastography might be superior to each method alone for characterizing liver tumors [37]. Tissue biomechanical parameters may thus become additional useful biomarkers to those obtained with Doppler and DCE ultrasonography [38]. Further efforts on validation and standardization of ultrasound elastography should be performed before the full clinical impact of the method can be observed. Finally, one should remind that multiple factors including hepatic fibrosis, inflammation, cholestasis, congestion, steatosis and portal hypertension can lead to overestimation of liver stiffness [39,40]. MR imaging The role of MR imaging in assessing focal and diffuse liver diseases has been reinforced these last years by the introduction of quantitative imaging methods that add functional information

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Review A

been proposed for motion compensation, including signal averaging, respiratory triggering or tracking, breath-holding, and cardiac triggering. However, the value of these methods remains debated because they have drawbacks, including increase in scan duration or decrease in signal-to-noise ratio [43]. The reproducibility of the diffusion parameters varies. High reproducibility has been observed for ADC and D, the apparent and true diffusion coefficients, but lower reproducibility for f, the fraction of diffusion related to microcirculation, and mainly for D⁄, the perfusion-related diffusion coefficient. The reported repeatability coefficients of ADC and D are 10–15% in the liver and 25–30% in malignant liver tumors [44–46]. The reproducibility and robustness of the diffusion parameter measurements can be improved by acquiring MR images during breath-holdings (Fig. 2), increasing the number of b-values, and using Bayesian analysis [47,48].

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Fig. 1. Hepatic shearwave elastograms. (A) Patient with focal nodular hyperplasia and (B) patient with steatotic adenoma Higher stiffness (30.9 ± 1.7 kPa) is observed in (A) focal nodular hyperplasia than (B) in adenoma (14.4 ± 1.7 kPa).

and can provide new imaging biomarkers. These methods include diffusion-weighted (DW) MR imaging, DCE MR imaging and MR elastography. Diffusion-weighted MR imaging Method Diffusion-weighted MR imaging probes intracellular and extracellular diffusion of water molecules by adding, in an echo-planar MR imaging sequence, two diffusion gradients that decrease the signal intensity according to tissue diffusibility and gradient strength (b value). On high b-value MR images, the signal intensity of lesions with high diffusibility such as cysts or hemangiomas will be nearly zero, whereas lesions with restricted diffusion such as highly cellular malignant tumors will have preserved high signal. The decrease of signal intensity of tissues according to increasing b-values is exponential, and the slope of this decrease on a semi-logarithmic plot corresponds to the apparent diffusion coefficient (ADC). Additional diffusion parameters can be assessed by probing signal intensity with multiple b-values. Indeed, according to the intravoxel incoherent motion (IVIM) model, signal intensity decrease on DW MR images at low b values (<100 s/mm2) is mainly caused by perfusion, whose speed is much faster than that of extravascular diffusion [41,42]. Therefore, at low b-values, the perfusion-related diffusion coefficient (D⁄) and the fraction of diffusion related to microcirculation (f) can be calculated, whereas at high b-values the pure molecular diffusion coefficient (D) can be obtained. The reproducibility and precision of the diffusion parameter measurements in the liver are limited by macroscopic motion, including respiratory and cardiac motion. Multiple methods have 4

Liver tumors Diffusion-weighted MR imaging is nowadays routinely performed in patients with focal liver diseases. It can be used to improve detection, characterization, and assessment of response to treatment of liver tumors. DW MR imaging markedly improves the detection of solid liver tumors relative to T2-weighted fast spin-echo imaging, with lower to comparable accuracy compared with DCE MR imaging [49–54]. Analyzing DW MR images with DCE MR images improves the diagnostic performance relative to the individual analysis of each imaging sequence. Diffusion-weighted MR imaging is also useful for tumor characterization. Malignant liver tumors have lower ADC than benign lesions [55]. This is generally explained by the higher cellularity in malignant tumors. In clinical practice, DW MR imaging criteria have been defined for characterizing benign and malignant lesions based on the tumor-to-liver contrast. According to these criteria, a lesion is considered benign if it appears hyperintense on DW images with a b-value of 0 s/mm2, with a strong decrease

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Fig. 2. Higher robustness of breathhold acquisition of DW-MR imaging data in calculating diffusion parameters. (A and C) Hepatic diffusion-weighted MR images and (B and D) maps of perfusion fractions (%) in patients with metastases (red contours) from colorectal cancer. Panels A and B are acquired during free breathing, whereas C and D are acquired with breathholding in the same patient. Black dots on B and D maps represent voxels with undetermined perfusion fraction because of failure of least-square algorithm to calculate perfusion fraction. More failures are observed on (B) free-breathing than (D) on corresponding breathhold image, especially in metastasis of liver segment VI (short arrow) and in upper pole of right kidney (long arrow). This figure illustrates the higher robustness of breathhold acquisition of DW- MR imaging data in calculating diffusion parameters.

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JOURNAL OF HEPATOLOGY in signal intensity with a b-value of 500 s/mm2 or higher, and if the lesion is hyperintense relative to the liver on the ADC map. A lesion is considered malignant if the lesion is mildly to moderately hyperintense on DW images with a b-value of 0 s/mm2 and remains hyperintense compared with liver parenchyma with a b-value of 500 s/mm2 or higher, and if the lesion appears hypointense on the ADC map [50]. However, the characterization of liver tumors with ADC measurements shows variable overlap between benign and malignant lesions. Benign lesions with high fluid content such as liver cysts and hemangiomas clearly have higher ADC than non-cystic malignant lesions, but the ADC of solid benign hepatocellular lesions such as focal nodular hyperplasia and adenoma does not significantly differ from that of solid malignant tumors [56]. Therefore, the DW MR criteria for tumor characterization are not useful for differentiating between benign hepatocellular and malignant liver lesions in the normal liver. One area where tumor characterization with DW MR imaging appears useful is the characterization of nodules in cirrhosis. Indeed, most HCC are hyperintense on DW MR images, whereas dysplastic nodules rarely are [57]. It has been reported that lesion hyperintensity on DW MR images is a more accurate sign of HCC than delayed hypointensity on DCE MR images enhanced with non-specific or hepatobiliary contrast agents [57–59]. The value of the IVIM-derived parameters to characterize liver lesions has been assessed in some studies. In a study of patients with 86 solid liver tumors, Doblas et al. observed that the diffusion parameters derived from the IVIM model did not improve the determination of malignancy and characterization of hepatic tumor type, when compared with the ADC [60]. In a series of 42 surgically confirmed HCC, Woo et al. observed a stronger degree of negative correlation between the pure diffusion coefficient D and tumor grade than between ADC and grade. However, the accuracy of D for differentiating between high- and low-grade HCC remained modest because of substantial overlap in the results (AUROC: 0.84) [61]. Diffusion measurements may be useful to assess the tumor response to treatment, by showing early diffusion parameter changes related to necrosis [62]. It has been recently shown that the volumetric ADC changes one month after intra-arterial treatment of HCC showed stronger association with tumor response than the size changes as assessed with the response evaluation criteria in solid tumors (RECIST), the modified response evaluation criteria in solid tumors (mRECIST) and the EASL criteria [63,64]. These results are explained not only by the use of a functional imaging biomarker (ADC) rather than structural criteria (RECIST), but also by the use of three-dimensional tumor volume analysis for the diffusivity measurements. Indeed, because of tumor heterogeneity, semi-automatic three-dimensional assessment of tumor volume ADC after trans-catheter arterial embolization has shown better interobserver agreement compared with manual two-dimensional region of interest measurements [65]. Besides their usefulness in the assessment of the response to trans-catheter embolization, ADC measurements are also potentially useful for predicting the response to radioembolization. One month after treatment of HCC with yttrium-90-labeled microspheres, increase in tumor ADC was observed, without a statistically significant change in tumor size [66]. Some results about the use of quantitative DW imaging after antivascular treatments have been reported. After sunitinib

treatment of HCC, perfusion parameters assessed with perfusion MR imaging might be more sensitive biomarkers in predicting early response than ADC [67]. After sorafenib treatment of HCC in another group of patients, it has been reported that changes of the perfusion fraction f may help differentiating between responders and non-responders [68]. Few studies report on the potential value of DW MR imaging for assessing the response of colorectal cancer metastases to chemotherapy [69,70]. Increase in ADC has been reported after treatment. It is expected that the changes of the diffusion parameters after treatment would be less pronounced in colorectal metastases than in HCC, because colorectal metastases are less vascularised and are characterized by fibrosis overgrowth rather than increase of necrosis after successful chemotherapy [71]. Fibrotic zones within tumors can be differentiated from viable tumor zones with DW MR imaging by measuring D, the pure diffusion coefficient, but differences in diffusion parameters between fibrotic and viable zones are less pronounced than between necrotic and viable zones [72]. Diffuse liver diseases Progressive decrease of ADC is seen in liver fibrosis, but large overlaps in ADC measurements between fibrosis stages are observed [73]. Currently, DW MR imaging alone is not recommended for staging liver fibrosis because its accuracy is not higher than that of plasma biomarkers measurements and transient ultrasound elastography, which are more easily-available methods [73]. Moreover, both animal and human studies have shown that the decrease of ADC in liver fibrosis may be influenced by other factors than fibrosis. These factors, including inflammation, steatosis and decreased perfusion, may have a predominant role in ADC decrease [74–76]. Finally, it has been shown that MR elastography is more accurate than DW MR imaging to stage liver fibrosis [77]. Dynamic contrast-enhanced MR imaging Method Dynamic contrast-enhanced MR imaging is an integral part of liver MR imaging for the detection and characterization of liver tumors. At least one image acquisition of the whole liver is performed during the arterial, portal venous, and delayed phases (3–5 min after the start of the injection) after bolus injection of an extracellular gadolinium chelate. When a hepatocyte-specific contrast agent is used, such as gadoxetate (PrimovistÓ, Bayer, Berlin, Germany), a hepatobiliary phase (20 min) is added to the dynamic phase for the assessment of intracellular retention of the contrast agent. In humans, gadoxetate is taken up within hepatocytes by the organic anion transporting polypeptides OATP1 B1/B3. It is excreted into bile through the multidrug resistance protein MRP2 transporters. Backflow to the sinusoids occurs through MRP3 and the bidirectional OATP1B1/B3 transporters [4,78,79]. In chronic liver diseases and HCC, expression and function of the hepatocyte transporters change, leading to changes of gadoxetate enhancement during the hepatobiliary phase. The transporter changes consist mainly in decreased OATP1 B1/B3 and MRP2, as well as increased MRP3 expression [80–82], which causes decreased lesion signal intensity on gadoxetate-enhanced MR images. In contrast, some HCC appear hyperintense on gadoxetateenhanced MR images during the hepatobiliary phase. Increase

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Review rather than decrease in OATP1 B3 expression has been found in these tumors [83]. To perform quantitative perfusion MR imaging, high temporal resolution at DCE MR imaging is needed, and three-dimensional MR images of the whole liver should be obtained with a time resolution <3 s. Simple parameters of lesion enhancement vs. time curve, such as peak enhancement, time to peak, steepest slope or area under the enhancement curve are only semiquantitative because the shape of the enhancement curve depends on the shape of the arterial input function. Therefore, the arterial input function has to be measured in addition to the tissue enhancement curve, and pharmacokinetic modeling should be performed to obtain physiological parameters such as perfusion or extravascular space volume [84]. For liver perfusion assessment, the dynamic curves should be analyzed with a dual-input model, because the liver has two vascular inputs through the hepatic artery and the portal vein. The dual-input compartmental model as validated by Materne et al. is often used [85]. With this model the arterial, portal venous, and total liver plasma transfer constants K1a, K1p, and K1t, respectively, (ml min1 100 ml1) can be assessed, as well as the distribution volume vd (%) and the mean transit time MTT (s). K1 is a lumped representation of perfusion and permeability (K1 = F  E with F the plasma perfusion and E the extravascular extraction fraction). When the permeability is high as in the normal liver, which has sinusoids containing fenestrae with 100 nm diameter, the extraction fraction equals one and K1 represents perfusion. If the permeability is low, K1 approximates the permeability-surface area product [86]. Because of the large portal venous input into the liver, hepatic perfusion imaging should be performed in fasting patients to obtain reproducible results. In contrast to the liver parenchyma, primary and secondary tumors of the liver, except at their early stage, have only an arterial and no portal venous input [87,88]. Therefore, the perfusion of hepatic tumors, except for early HCC, can be analyzed with single input rather than dual-input models. The most used single input models are the Kety and the extended Kety models. The Kety model, also called the Tofts model, is a simple dual-compartmental model, in which Ktrans (=K1) and the extravascular extracellular volume (ve = vd) are calculated. In the extended Kety model, Ktrans, ve, and the plasma volume (vp) are assessed. The use of more complex distributed-parameter models has been proposed, but these models are less precise than the compartmental models because of the interdependency of the multiple free parameters and their sensitivity to initial values [89,90]. In perfusion measurements, both the transfer constant Ktrans and the extravascular extracellular volume ve should be measured [91]. The reported coefficients of repeatability of Ktrans in liver tumors are in the range of 20–40% [92]. It has been reported that ve has a better reproducibility than Ktrans, and ve measurements allow the assessment of the vascular permeability by looking at the volume accessible to contrast agents of different molecular weights [90,93]. Because the reproducibility of the perfusion measurements depends on the organ, the image acquisition and data analysis methods, it has been recommended to assess the reproducibility before starting clinical trials that aim at assessing treatment response with DCE MR imaging [91]. It should be noted that there is currently no post-processing standard among the commercially available perfusion analysis solutions, and this causes large variations in the measured

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perfusion parameters (reported coefficients of repeatability >130%) [94]. This variability is mainly explained by the use of different population-based arterial input functions. It underscores the need for standardizing the perfusion measurements and using patient-based rather than population-based arterial input functions. Moreover, the interobserver reproducibility of the perfusion measurements can be improved with semi-automatic registration and histogram analysis [95]. With pharmacokinetic analysis of dynamic gadoxetateenhanced MR images, liver perfusion and hepatocyte transport function can be assessed separately using deconvolution or compartmental analysis (Fig. 3) [96,97]. Diffuse liver diseases Dynamic contrast-enhanced MR imaging can be used to assess the microcirculatory changes in liver fibrosis and cirrhosis. Decrease of portal and total hepatic perfusion is observed, as well as increases of arterial perfusion and mean transit time, with preserved or increased distribution volume. These perfusion changes occur already at intermediate stages of liver fibrosis, but are more marked in cirrhosis, where they correlate with the degree of liver dysfunction and portal hypertension [86,98]. Decrease of the hepatobiliary excretion of organic anions through the OATP/ MRP route in liver fibrosis, cirrhosis and non-alcoholic steatohepatitis (NASH) can be assessed with gadoxetate-enhanced MR imaging [82,99–101]. Moreover, gadoxetate-enhanced MR imaging appears promising for the assessment of the risk for liver failure after major liver resection [102]. Liver tumors Dynamic contrast-enhanced MR imaging during the arterial, portal venous and delayed phases is routinely performed for tumor detection, characterization, and assessment of tumor response to treatment. For these purposes, gadoxetate is increasingly used rather than extracellular contrast agents. Indeed, numerous studies have shown that the detection and characterization of focal liver lesions, including HCC, adenomas, focal nodular hyperplasias and liver metastases, is improved during the hepatobiliary phase of gadoxetate-enhanced MR imaging [103–105].

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Fig. 3. Parametric perfusion and hepatocyte uptake extraction fraction maps. (A and B) Patient with normal liver, and (C and D) patient with liver cirrhosis, obtained with dynamic gadoxetate-enhanced MR imaging. Liver perfusion (ml min1 g1) is more heterogeneous in liver cirrhosis than in normal liver (C vs. A), and uptake extraction fraction (%) is decreased (D vs. B).

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JOURNAL OF HEPATOLOGY Particularly, some early hypovascular HCC are only observed as hypointense nodules during the hepatobiliary phase at gadoxetate-enhanced MR imaging, without being readily seen during dynamic imaging. The subgroup of lesions showing both absence of enhancement during the arterial phase and hypointensity during the hepatobiliary phase is challenging because not all of these lesions correspond to HCC or will evolve into HCC [106,107]. In this setting, hyperintensity on DW MR images increases the likelihood of early HCC or progression to hypervascular HCC [107,108]. In contrast to the qualitative assessment of liver tumors with DCE MR imaging, quantitative perfusion MR imaging of liver tumors is not often obtained in clinical practice. The main indication of perfusion MR imaging is the assessment of tumor response to antiangiogenic or local treatments [109]. In patients with HCC who received sorafenib plus metronomic tegafur/uracil therapy, Ktrans measured with DCE-MR imaging correlated well with tumor response and survival [110]. In patients with HCC treated with sunitinib, it was found that the perfusion parameters were more sensitive biomarkers in predicting early response and progression free survival than RECIST and mRECIST [67]. In another study of HCC treated with sunitinib, it was observed that the extent of decrease in Ktrans in patients who experienced partial response or stable disease according to RECIST was significantly greater (twofold on average) compared with patients with progressive disease or who died during the first two cycles of therapy [111]. Similar results were reported in patients with potentially resectable metastatic colorectal cancer treated with chemotherapy and bevacizumab. In these patients, progression-free survival benefit was shown for patients with >40% reduction in Ktrans [112]. Dynamic contrast-enhanced MR imaging and DW MR imaging may bring complementary predictive information. In patients with HCC, Bonekamp et al. performed volumetric DCE MR imaging and DW MR imaging one month after intraarterial therapy and observed that there were significant differences in overall survival between patients who were dual-parameter responders (namely patients having decrease in venous enhancement of more than 65% and increase in ADC of more than 25%) and single-parameter responders, as well as between singleparameter responders and those with stable disease [64]. These results show the usefulness of multiparametric functional MR imaging in the assessment of treatment response.

Breathhold MR elastography has a reported repeatability coefficient of 22% for elasticity and 26% for viscosity in the liver [115]. The reproducibility of MR elastography for liver fibrosis has been reported to be better than that of FibroscanÓ [116]. Diffuse liver diseases Single center studies have shown that MR elastography is a robust, reproducible, and accurate method to detect and stage liver fibrosis [116–119]. MR elastography outperforms transient ultrasound elastography and aspartate aminotransferase to platelets ratio index (APRI) for hepatic fibrosis staging [116]. In animal studies, it has been shown that the visco-elastic properties of the liver correlate with the percentage of hepatic fibrosis determined at morphometry [120]. As already mentioned, several conditions in addition to fibrosis may increase the mechanical properties of the liver, including inflammation, cholestasis, congestion and portal hypertension [121]. The various visco-elastic parameters determined at multifrequency MR elastography may help in disease characterization. Indeed, studies suggest that liver fibrosis stage mainly correlates with tissue elasticity, whereas inflammation grade mainly correlates with wave scattering coefficient (Fig. 4) and portal hypertension degree with liver and spleen viscosity [122–124]. Studies in animals and humans have shown that MR elastography may be useful for the early diagnosis of NASH, by showing early increase in elasticity explained by inflammation and activation of stellate cells [125,126]. If the high diagnostic performance of MR elastography is further shown in multicenter trials, it may be particularly relevant to use this method to complement ultrasound elastography and avoid liver biopsy in intermediate stages of fibrosis, to stage portal hypertension and to assess the response to antifibrotic treatments [27]. Liver tumors MR elastography may help in the characterization of liver tumors and the assessment of response to treatment. In a preliminary study, it has been shown that malignant tumors have a higher

A

MR elastography Method For MR elastography, external vibrators are used to generate shear or compression waves. When using compression waves, the shear waves needed for calculating the visco-elastic parameters are obtained by mode conversion at interfaces within the tissue. The advantage of using compression waves is that they penetrate within tissues better than shear waves [113]. With three-dimensional MR elastography, the full visco-elastic properties of the tissue can be evaluated by measuring shear wave propagation and attenuation. These visco-elastic properties include the shear modulus G⁄, the storage modulus Gd reflecting elasticity, and the loss modulus Gl reflecting viscosity. Moreover, with multifrequency MR elastography, the wave scattering coefficient corresponding to the slope of the visco-elasticity vs. frequency curve can be obtained [24,114].

C

5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0

B

2.1 1.9 1.7 1.5

D

1.3 1.1 0.9

Fig. 4. Multifrequency MR elastography parametric maps of elasticity and wave dispersion coefficient. Patients with chronic hepatitis C infection classified as (A and B) F2 fibrosis, A1 inflammation and (C and D) F2 fibrosis, A3 inflammation according to METAVIR. Storage modulus values (elasticity in kPa) are similar in patient with F2, A1 (A) and patient with F2, A3 (C), whereas wave dispersion coefficients (arbitrary units) are lower in patients with higher inflammation grade (D vs. B). This figure illustrates the superiority of wave dispersion coefficient measurements at multifrequency MR elastography relative to elasticity measurements in discriminating between patients with different grades of hepatic inflammation.

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Review stiffness than benign ones [127]. In a more recent study, it has been observed that malignant liver tumors are mainly characterized by increased viscosity [128]. Small animal studies have shown that MR elastography is useful for assessing the early tumor response to vascular disrupting agents and to chemotherapy [129–131]. Further human trials are needed to clarify the role of multi-frequency MR elastography in characterizing liver tumors and assessing their response to treatment.

Conclusions Ultrasonography and MR imaging of liver diseases evolve from qualitative anatomical imaging methods to combined quantitative anatomical and functional imaging methods. Imaging biomarkers obtained with diffusion and perfusion – hepatocyte transport imaging, as well as with elastography, have an increasing role in the detection and characterization of diffuse liver diseases and liver tumors, and in the assessment of response to treatment. The multiparametric capability of ultrasonography and more markedly of MR imaging gives the opportunity of improved diagnostic performance by combining imaging biomarkers. For widespread clinical use in liver disease, imaging biomarkers should be further validated in large multicenter trials. The image acquisition and post-processing methods should be further improved and standardized to increase diagnostic accuracy and reproducibility.

Conflict of interest The authors declared that they do not have anything to disclose regarding funding or conflict of interest with respect to this manuscript. Acknowledgements The authors thank Dr. Maxime Ronot and Benjamin Leporq from Laboratory of Imaging Biomarkers, UMR1149 INSERM-University Paris Diderot for providing Figs. 1 and 3, respectively. References [1] Galea N, Cantisani V, Taouli B. Liver lesion detection and characterization: role of diffusion-weighted imaging. J Magn Reson Imaging 2013;37: 1260–1276. [2] Low RN. Abdominal MRI advances in the detection of liver tumours and characterisation. Lancet Oncol 2007;8:525–535. [3] Van Beers BE, Doblas S, Sinkus R. New acquisition techniques: fields of application. Abdom Imaging 2011;37:155–163. [4] Van Beers BE, Pastor CM, Hussain HK. Primovist, Eovist: what to expect? J Hepatol 2012;57:421–429. [5] Kiessling F, Fokong S, Bzyl J, Lederle W, Palmowski M, Lammers T. Recent advances in molecular, multimodal and theranostic ultrasound imaging. Adv Drug Deliv Rev 2014;72:15–27. [6] Claudon M, Dietrich CF, Choi BI, Cosgrove DO, Kudo M, Nolsoe CP, et al. Guidelines and good clinical practice recommendations for contrast enhanced utrasound (CEUS) in the liver – update 2012: A WFUMB-EFSUMB initiative in cooperation with representatives of AFSUMB, AIUM, ASUM, FLAUS and ICUS. Ultrasound Med Biol 2013;39:187–210. [7] Bolondi L. The appropriate allocation of CEUS in the diagnostic algorithm of liver lesions: a debated issue. Ultrasound Med Biol 2013;39:183–185. [8] Bruix J, Sherman M. Management of hepatocellular carcinoma. Hepatology 2005;42:1208–1236.

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Please cite this article in press as: Van Beers BE et al. New imaging techniques for liver diseases. J Hepatol (2015), http://dx.doi.org/10.1016/ j.jhep.2014.10.014