Advertisement

New boundaries of liver imaging: from morphology to function

      Highlights

      • Modern liver imaging combines morphological and functional information to detect and characterize focal lesions.
      • Quantitative data allows tumor response assessment in oncology and monitoring of diffuse liver conditions.
      • Texture analysis (radiomics) creates new surrogate markers of liver pathology.

      Abstract

      From an invisible organ to one of the most explored non-invasively, the liver is, today, one of the cornerstones for current cross-sectional imaging techniques and minimally invasive procedures. After the achievements of US, CT and, most recently, MRI in providing highly accurate morphological and structural information about the organ, a significant scientific development has gained momentum for the last decades, coupling morphology to liver function and contributing far most to what we know today as precision medicine. In fact, dedicated tailor-made investigations are now possible in order to detect and, most of all, quantify physiopathological processes with unprecedented certitude. It is the intention of this review to provide a better insight to the reader of several functional imaging techniques applied to liver imaging. Contrast enhanced imaging, diffusion weighted imaging, elastography, spectral computed tomography and fat and iron assessment techniques are commonly performed clinically. Diffusion kurtosis imaging, magnetic resonance spectroscopy, T1 relaxometry and radiomics remain largely limited to advanced clinical research. Each of them has its own value and place on the diagnostic armamentarium and provide unique qualitative and quantitative information regarding the pathophysiology of diseases, contributing at a large scale to model therapeutic decisions and patient follow-up. Therefore, state-of-the-art liver imaging acts today as a non-invasive surrogate biomarker of many focal and diffuse liver diseases.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to European Journal of Internal Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Paefgen V.
        • Doleschel D.
        • Kiessling F
        Evolution of contrast agents for ultrasound imaging and ultrasound-mediated drug delivery.
        Front Pharmacol. 2015; https://doi.org/10.3389/fphar.2015.00197
        • Qin S.
        • Caskey C.F.
        • Ferrara K.W
        Ultrasound contrast microbubbles in imaging and therapy: physical principles and engineering.
        Phys Med Biol. 2009; https://doi.org/10.1088/0031-9155/54/6/R01
        • Piscaglia F.
        • Bolondi L.
        • Aiani L.
        • Luigi Angeli M.
        • Arienti V.
        • Barozzi L.
        • et al.
        The safety of Sonovue® in abdominal applications: retrospective analysis of 23188 investigations.
        Ultrasound Med Biol. 2006; https://doi.org/10.1016/j.ultrasmedbio.2006.05.031
        • Wilson S.R.
        • Burns P.N.
        Microbubble-enhanced US in body imaging: what role?.
        Radiology. 2010; https://doi.org/10.1148/radiol.10091210
        • Cantisani V.
        • Wilson S.R.
        CEUS: where are we in 2015?.
        Eur J Radiol. 2015; https://doi.org/10.1016/j.ejrad.2015.05.028
        • Sugimoto K.
        • Moriyasu F.
        • Saito K.
        • Taira J.
        • Saguchi T.
        • Yoshimura N.
        • et al.
        Comparison of Kupffer-phase sonazoid-enhanced sonography and hepatobiliary-phase gadoxetic acid-enhanced magnetic resonance imaging of hepatocellular carcinoma and correlation with histologic grading.
        J Ultrasound Med. 2012; https://doi.org/10.7863/jum.2012.31.4.529
        • Pang E.H.T.
        • Chan A.
        • Ho S.G.
        • Harris A.C
        Contrast-enhanced ultrasound of the liver: optimizing technique and clinical applications.
        Am J Roentgenol. 2018; https://doi.org/10.2214/AJR.17.17843
        • Claudon M.
        • Dietrich C.F.
        • Choi B.I.
        • Cosgrove D.O.
        • Kudo M.
        • Nolsøe C.P.
        • et al.
        Guidelines and good clinical practice recommendations for contrast enhanced ultrasound (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; https://doi.org/10.1016/j.ultrasmedbio.2012.09.002
        • Lassau N.
        • Chami L.
        • Koscielny S.
        • Chebil M.
        • Massard C.
        • Benatsou B.
        • et al.
        Quantitative functional imaging by dynamic contrast enhanced ultrasonography (DCE-US) in GIST patients treated with masatinib.
        Invest New Drugs. 2012; https://doi.org/10.1007/s10637-010-9592-2
        • Lassau N.
        • Koscielny S.
        • Chami L.
        • Chebil M.
        • Benatsou B.
        • Roche A.
        • et al.
        Advanced hepatocellular carcinoma: early evaluation of response to bevacizumab therapy at dynamic contrast-enhanced us with quantification- preliminary results.
        Radiology. 2011; https://doi.org/10.1148/radiol.10091870
        • Averkiou M.
        • Lampaskis M.
        • Kyriakopoulou K.
        • Skarlos D.
        • Klouvas G.
        • Strouthos C.
        • et al.
        Quantification of tumor microvascularity with respiratory gated contrast enhanced ultrasound for monitoring therapy.
        Ultrasound Med Biol. 2010; https://doi.org/10.1016/j.ultrasmedbio.2009.07.005
        • Schirin-Sokhan R.
        Response evaluation of chemotherapy in metastatic colorectal cancer by contrast enhanced ultrasound.
        World J Gastroenterol. 2012; 18: 541https://doi.org/10.3748/wjg.v18.i6.541
        • Knieling F.
        • Waldner M.J.
        • Goertz R.S.
        • Zopf S.
        • Wildner D.
        • Neurath M.F.
        • et al.
        Early response to anti-tumoral treatment in hepatocellular carcinoma - Can quantitative contrast-enhanced ultrasound predict outcome?.
        Ultraschall Der Medizin. 2013; https://doi.org/10.1055/s-0032-1330387
        • Zocco M.A.
        • Garcovich M.
        • Lupascu A.
        • Di Stasio E.
        • Roccarina D.
        • Annicchiarico B.E.
        • et al.
        Early prediction of response to sorafenib in patients with advanced hepatocellular carcinoma: the role of dynamic contrast enhanced ultrasound.
        J Hepatol. 2013; https://doi.org/10.1016/j.jhep.2013.06.011
        • Hoyt K.
        • Sorace A.
        • Saini R
        Quantitative mapping of tumor vascularity using volumetric contrast-enhanced ultrasound.
        Invest Radiol. 2012; https://doi.org/10.1097/rli.0b013e318234e6bc
        • Gandhi S.N.
        • Brown M.A.
        • Wong J.G.
        • Aguirre D.A.
        • Sirlin C.B
        MR contrast agents for liver imaging: what, when, how.
        Radiographics. 2006; https://doi.org/10.1148/rg.266065014
        • Seale M.K.
        • Catalano O.A.
        • Saini S.
        • Hahn P.F.
        • Sahani D V
        Hepatobiliary-specific MR contrast agents: role in imaging the liver and biliary tree.
        Radiographics. 2009; https://doi.org/10.1148/rg.296095515
        • Oliver J.H.
        • Baron R.L.
        Helical biphasic contrast-enhanced CT of the liver: technique, indications, interpretation, and pitfalls.
        Radiology. 1996; https://doi.org/10.1148/radiology.201.1.8816509
        • Bin Chen B
        • TTF Shih
        DCE-MRI in hepatocellular carcinoma-clinical and therapeutic image biomarker.
        World J Gastroenterol. 2014; https://doi.org/10.3748/wjg.v20.i12.3125
        • Donato H.
        • França M.
        • Candelária I.
        • Caseiro-Alves F
        Liver MRI: from basic protocol to advanced techniques.
        Eur J Radiol. 2017; https://doi.org/10.1016/j.ejrad.2017.05.028
        • Tirkes T.
        • Hollar M.A.
        • Tann M.
        • Kohli M.D.
        • Akisik F.
        • Sandrasegaran K
        Response criteria in oncologic imaging: review of traditional and new criteria.
        Radiographics. 2013; https://doi.org/10.1148/rg.335125214
        • Rezai P.
        • Pisaneschi M.J.
        • Feng C.
        • Yaghmai V
        A radiologist's guide to treatment response criteria in oncologic imaging: functional, molecular, and disease-specific imaging biomarkers.
        Am J Roentgenol. 2013; https://doi.org/10.2214/AJR.12.9878
        • Frydrychowicz A.
        Review of hepatobiliary contrast agents: current applications and challenges.
        Clin Liver Dis. 2018; https://doi.org/10.1002/cld.688
        • Bieze M.
        • Van Den Esschert J.W.
        • Nio C.Y.
        • Verheij J.
        • Reitsma J.B.
        • Terpstra V.
        • et al.
        Diagnostic accuracy of MRI in differentiating hepatocellular adenoma from focal nodular hyperplasia: prospective study of the additional value of gadoxetate disodium.
        Am J Roentgenol. 2012; https://doi.org/10.2214/AJR.11.7750
        • Papanikolaou N.
        • Prassopoulos P.
        • Eracleous E.
        • Maris T.
        • Gogas C.
        • Gourtsoyiannis N
        Contrast-enhanced magnetic resonance cholangiography versus heavily T2-weighted magnetic resonance cholangiography.
        Invest Radiol. 2001; 36: 682-686https://doi.org/10.1097/00004424-200111000-00008
        • Prassopoulos P.
        • Papanikolaou N.
        • Maris T.
        • Gogas C.
        • Mouzas J.
        • Gourtsoyiannis N
        Development of contrast-enhanced virtual MR cholangioscopy: a feasibility study.
        Eur Radiol. 2002; https://doi.org/10.1007/s00330-001-1276-z
        • Qayyum A.
        Diffusion-weighted imaging in the abdomen and pelvis: concepts and applications.
        Radiographics. 2009; https://doi.org/10.1148/rg.296095521
        • Baliyan V.
        • Das C.J.
        • Sharma R.
        • Gupta A.K
        Diffusion weighted imaging: technique and applications.
        World J Radiol. 2016; https://doi.org/10.4329/wjr.v8.i9.785
        • Koh D.M.
        • Padhani A.R.
        Functional magnetic resonance imaging of the liver: parametric assessments beyond morphology.
        Magn Reson Imaging Clin N Am. 2010; https://doi.org/10.1016/j.mric.2010.07.002
        • Ichikawa T.
        • Haradome H.
        • Hachiya J.
        • Nitatori T.
        • Araki T
        Diffusion-weighted MR imaging with a single-shot echoplanar sequence: detection and characterization of focal hepatic lesions.
        Am J Roentgenol. 1998; https://doi.org/10.2214/ajr.170.2.9456953
        • Parikh T.
        • Drew S.J.
        • Lee V.S.
        • Wong S.
        • Hecht E.M.
        • Babb J.S.
        • et al.
        Focal liver lesion detection and characterization with diffusion-weighted MR imaging: comparison with standard breath-hold T2-weighted imaging.
        Radiology. 2008; https://doi.org/10.1148/radiol.2463070432
        • Koh D.M.
        • Collins D.J.
        • Wallace T.
        • Chau I.
        • Riddell A.M
        Combining diffusion-weighted MRI with Gd-EOB-DTPA-enhanced MRI improves the detection of colorectal liver metastases.
        Br J Radiol. 2012; https://doi.org/10.1259/bjr/91771639
        • Koh D.M.
        • Brown G.
        • Riddell A.M.
        • Scurr E.
        • Collins D.J.
        • Allen S.D.
        • et al.
        Detection of colorectal hepatic metastases using MnDPDP MR imaging and diffusion-weighted imaging (DWI) alone and in combination.
        Eur Radiol. 2008; https://doi.org/10.1007/s00330-007-0847-z
        • Namimoto T.
        • Yamashita Y.
        • Sumi S.
        • Tang Y.
        • Takahashi M
        Focal liver masses: characterization with diffusion-weighted echo- planar MR imaging.
        Radiology. 1997; https://doi.org/10.1148/radiology.204.3.9280252
        • Bruegel M.
        • Holzapfel K.
        • Gaa J.
        • Woertler K.
        • Waldt S.
        • Kiefer B.
        • et al.
        Characterization of focal liver lesions by ADC measurements using a respiratory triggered diffusion-weighted single-shot echo-planar MR imaging technique.
        Eur Radiol. 2008; https://doi.org/10.1007/s00330-007-0785-9
        • Taouli B.
        • Vilgrain V.
        • Dumont E.
        • Daire J.L.
        • Fan B.
        • Menu Y
        Evaluation of liver diffusion isotropy and characterization of focal hepatic lesions with two single-shot echo-planar MR imaging sequences: prospective study in 66 patients.
        Radiology. 2003; https://doi.org/10.1148/radiol.2261011904
        • Gourtsoyianni S.
        • Papanikolaou N.
        • Yarmenitis S.
        • Maris T.
        • Karantanas A.
        • Gourtsoyiannis N
        Respiratory gated diffusion-weighted imaging of the liver: value of apparent diffusion coefficient measurements in the differentiation between most commonly encountered benign and malignant focal liver lesions.
        Eur Radiol. 2008; 18: 486-492https://doi.org/10.1007/s00330-007-0798-4
        • Papanikolaou N.
        • Gourtsoyianni S.
        • Yarmenitis S.
        • Maris T.
        • Gourtsoyiannis N
        Comparison between two-point and four-point methods for quantification of apparent diffusion coefficient of normal liver parenchyma and focal lesions. Value of normalization with spleen.
        Eur J Radiol. 2010; 73: 305-309https://doi.org/10.1016/j.ejrad.2008.10.023
        • Drevelegas K.
        • Nikiforaki K.
        • Constantinides M.
        • Papanikolaou N.
        • Papalavrentios L.
        • Stoikou I.
        • et al.
        Apparent diffusion coefficient quantification in determining the histological diagnosis of malignant liver lesions.
        J Cancer. 2016; 7: 730-735https://doi.org/10.7150/jca.14197
        • Renzulli M.
        • Biselli M.
        • Brocchi S.
        • Granito A.
        • Vasuri F.
        • Tovoli F.
        • et al.
        New hallmark of hepatocellular carcinoma, early hepatocellular carcinoma and high-grade dysplastic nodules on Gd-EOB-DTPA MRI in patients with cirrhosis: a new diagnostic algorithm.
        Gut. 2018; https://doi.org/10.1136/gutjnl-2017-315384
        • Kim T.-.H.
        • Kim S.Y.
        • Tang A.
        • Lee J.M
        Comparison of international guidelines for noninvasive diagnosis of hepatocellular carcinoma: 2018 update.
        Clin Mol Hepatol. 2019; 25: 245-263https://doi.org/10.3350/cmh.2018.0090
        • Cui Y.
        • Zhang X.P.
        • Sun Y.S.
        • Tang L.
        • Shen L
        Apparent diffusion coefficient: potential imaging biomarker for prediction and early detection of response to chemotherapy in hepatic metastases.
        Radiology. 2008; https://doi.org/10.1148/radiol.2483071407
        • Koh D.M.
        • Scurr E.
        • Collins D.
        • Kanber B.
        • Norman A.
        • Leach M.O.
        • et al.
        Predicting response of colorectal hepatic metastasis: value of pretreatment apparent diffusion coefficients.
        Am J Roentgenol. 2007; https://doi.org/10.2214/AJR.06.0601
        • Jensen J.H.
        • Helpern J.A.
        • Ramani A.
        • Lu H.
        • Kaczynski K
        Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging.
        Magn Reson Med. 2005; https://doi.org/10.1002/mrm.20508
        • Steven A.J.
        • Zhuo J.
        • Melhem E.R
        Diffusion kurtosis imaging: an emerging technique for evaluating the microstructural environment of the brain.
        Am J Roentgenol. 2014; https://doi.org/10.2214/AJR.13.11365
        • Rosenkrantz A.B.
        • Sigmund E.E.
        • Winnick A.
        • Niver B.E.
        • Spieler B.
        • Morgan G.R.
        • et al.
        Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants.
        Magn Reson Imag. 2012; https://doi.org/10.1016/j.mri.2012.04.020
        • Goshima S.
        • Kanematsu M.
        • Noda Y.
        • Kondo H.
        • Watanabe H.
        • Bae K.T
        Diffusion kurtosis imaging to assess response to treatment in hypervascular hepatocellular carcinoma.
        Am J Roentgenol. 2015; https://doi.org/10.2214/AJR.14.13235
        • Wang W.T.
        • Yang L.
        • Yang Z.X.
        • Hu X.X.
        • Ding Y.
        • Yan X.
        • et al.
        Assessment of microvascular invasion of hepatocellular carcinoma with diffusion kurtosis imaging.
        Radiology. 2018; https://doi.org/10.1148/radiol.2017170515
        • Cowin G.J.
        • Jonsson J.R.
        • Bauer J.D.
        • Ash S.
        • Ali A.
        • Osland E.J.
        • et al.
        Magnetic resonance imaging and spectroscopy for monitoring liver steatosis.
        J Magn Reson Imag. 2008; https://doi.org/10.1002/jmri.21542
        • Szczepaniak L.S.
        • Nurenberg P.
        • Leonard D.
        • Browning J.D.
        • Reingold J.S.
        • Grundy S.
        • et al.
        Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population.
        Am J Physiol - Endocrinol Metab. 2005; https://doi.org/10.1152/ajpendo.00064.2004
        • Qayyum A.
        MR spectroscopy of the liver: principles and clinical applications.
        Radiographics. 2009; https://doi.org/10.1148/rg.296095520
        • Idilman I.S.
        • Aniktar H.
        • Idilman R.
        • Kabacam G.
        • Savas B.
        • Elhan A.
        • et al.
        Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy.
        Radiology. 2013; https://doi.org/10.1148/radiol.13121360
        • Ryan J.D.
        • Armitage A.E.
        • Cobbold J.F.
        • Banerjee R.
        • Borsani O.
        • Dongiovanni P.
        • et al.
        Hepatic iron is the major determinant of serum ferritin in NAFLD patients.
        Liver Int. 2018; 38: 164-173https://doi.org/10.1111/liv.13513
        • Charatcharoenwitthaya P.
        • Lindor K.D.
        Role of radiologic modalities in the management of Non-alcoholic steatohepatitis.
        Clin Liver Dis. 2007; https://doi.org/10.1016/j.cld.2007.02.014
        • Mishra P.
        • Younossi Z.M.
        Abdominal ultrasound for diagnosis of nonalcoholic fatty liver disease (NAFLD).
        Am J Gastroenterol. 2007; https://doi.org/10.1111/j.1572-0241.2007.01520.x
        • Graif M.
        • Yanuka M.
        • Baraz M.
        • Blank A.
        • Moshkovitz M.
        • Kessler A.
        • et al.
        Quantitative estimation of attenuation in ultrasound video images: correlation with histology in diffuse liver disease.
        Invest Radiol. 2000; https://doi.org/10.1097/00004424-200005000-00006
        • Pickhardt P.J.
        • Park S.H.
        • Hahn L.
        • Lee S.G.
        • Bae K.T.
        • Yu E.S
        Specificity of unenhanced CT for non-invasive diagnosis of hepatic steatosis: implications for the investigation of the natural history of incidental steatosis.
        Eur Radiol. 2012; https://doi.org/10.1007/s00330-011-2349-2
        • Rofsky N.M.
        • Fleishaker H.
        CT and MRI of diffuse liver disease.
        Semin Ultrasound, CT, MRI. 1995; https://doi.org/10.1016/0887-2171(95)90012-8
        • Limanond P.
        • Raman S.S.
        • Lassman C.
        • Sayre J.
        • Ghobrial R.M.
        • Busuttil R.W.
        • et al.
        Macrovesicular hepatic steatosis in living related liver donors: correlation between CT and histologic findings.
        Radiology. 2004; https://doi.org/10.1148/radiol.2301021176
        • Stern C.
        • Castera L.
        Non-invasive diagnosis of hepatic steatosis.
        Hepatol Int. 2017; https://doi.org/10.1007/s12072-016-9772-z
        • Wells S.A.
        Quantification of hepatic fat and iron with magnetic resonance imaging.
        Magn Reson Imag Clin N Am. 2014; https://doi.org/10.1016/j.mric.2014.04.010
        • Ma X.
        • Holalkere N.S.
        • Avinash K.R.
        • Mino-Kenudson M.
        • Hahn P.F.
        • Sahani D V
        Imaging-based quantification of hepatic fat: methods and clinical applications.
        Radiographics. 2009; https://doi.org/10.1148/rg.295085186
        • Dixon W.T
        Simple proton spectroscopic imaging.
        Radiology. 1984; https://doi.org/10.1148/radiology.153.1.6089263
        • Yu H.
        • McKenzie C.A.
        • Shimakawa A.
        • Vu A.T.
        • Brau A.C.S.
        • Beatty P.J.
        • et al.
        Multiecho reconstruction for simultaneous water-fat decomposition and T2* estimation.
        J Magn Reson Imag. 2007; https://doi.org/10.1002/jmri.21090
        • Permutt Z.
        • Le T.A.
        • Peterson M.R.
        • Seki E.
        • Brenner D.A.
        • Sirlin C.
        • et al.
        Correlation between liver histology and novel magnetic resonance imaging in adult patients with non-alcoholic fatty liver disease - MRI accurately quantifies hepatic steatosis in NAFLD.
        Aliment Pharmacol Ther. 2012; https://doi.org/10.1111/j.1365-2036.2012.05121.x
        • Reeder S.B.
        • Cruite I.
        • Hamilton G.
        • Sirlin C.B
        Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy.
        J Magn Reson Imag. 2011; https://doi.org/10.1002/jmri.22580
        • Kim H.
        • Taksali S.E.
        • Dufour S.
        • Befroy D.
        • Goodman T.R.
        • Petersen K.F.
        • et al.
        Comparative MR study of hepatic fat quantification using single-voxel proton spectroscopy, two-point Dixon and three-point IDEAL.
        Magn Reson Med. 2008; https://doi.org/10.1002/mrm.21561
        • Yokoo T.
        • Bydder M.
        • Hamilton G.
        • Middleton M.S.
        • Gamst A.C.
        • Wolfson T.
        • et al.
        Nonalcoholic fatty liver disease: diagnostic and fat-grading accuracy of low-flip-angle multiecho gradient-recalled-echo MR imaging at 1.5 T.
        Radiology. 2009; https://doi.org/10.1148/radiol.2511080666
        • Wilman H.R.
        • Kelly M.
        • Garratt S.
        • Matthews P.M.
        • Milanesi M.
        • Herlihy A.
        • et al.
        Characterisation of liver fat in the UK Biobank cohort.
        PLoS ONE. 2017; 12e0172921https://doi.org/10.1371/journal.pone.0172921
        • Caussy C.
        • Reeder S.B.
        • Sirlin C.B.
        • Loomba R
        Noninvasive, quantitative assessment of liver fat by MRI-PDFF as an endpoint in NASH trials.
        Hepatology. 2018; 68: 763-772https://doi.org/10.1002/hep.29797
        • Harrison S.A.
        • Rossi S.J.
        • Paredes A.H.
        • Trotter J.F.
        • Bashir M.R.
        • Guy C.D.
        • et al.
        NGM282 improves liver fibrosis and histology in 12 weeks in patients with nonalcoholic steatohepatitis.
        Hepatology. 2019; 30590 (hep.)https://doi.org/10.1002/hep.30590
        • Hutton C.
        • Gyngell M.L.
        • Milanesi M.
        • Bagur A.
        • Brady M
        Validation of a standardized MRI method for liver fat and T2* quantification.
        PLoS ONE. 2018; 13e0204175https://doi.org/10.1371/journal.pone.0204175
        • Hernando D.
        • Sharma S.D.
        • Aliyari Ghasabeh M.
        • Alvis B.D.
        • Arora S.S.
        • Hamilton G.
        • et al.
        Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom.
        Magn Reson Med. 2017; 77: 1516-1524https://doi.org/10.1002/mrm.26228
        • Yokoo T.
        • Serai S.D.
        • Pirasteh A.
        • Bashir M.R.
        • Hamilton G.
        • Hernando D.
        • et al.
        Linearity, bias, and precision of hepatic proton density fat fraction measurements by using mr imaging: a meta-analysis.
        Radiology. 2018; 286: 486-498https://doi.org/10.1148/radiol.2017170550
        • Labranche R.
        • Gilbert G.
        • Cerny M.
        • Vu K.N.
        • Soulières D.
        • Olivié D.
        • et al.
        Liver iron quantification with MR imaging: a primer for radiologists.
        Radiographics. 2018; https://doi.org/10.1148/rg.2018170079
        • Alexopoulou E.
        • Stripeli F.
        • Baras P.
        • Seimenis I.
        • Kattamis A.
        • Ladis V.
        • et al.
        R2 relaxometry with MRI for the quantification of tissue iron overload in β-thalassemic patients.
        J Magn Reson Imag. 2006; https://doi.org/10.1002/jmri.20489
        • Wood J.C.
        MRI R2 and R2* mapping accurately estimates hepatic iron concentration in transfusion-dependent thalassemia and sickle cell disease patients.
        Blood. 2005; 106: 1460-1465https://doi.org/10.1182/blood-2004-10-3982
        • McKay A.
        • Wilman H.R.
        • Dennis A.
        • Kelly M.
        • Gyngell M.L.
        • Neubauer S.
        • et al.
        Measurement of liver iron by magnetic resonance imaging in the UK Biobank population.
        PLoS ONE. 2018; 13e0209340https://doi.org/10.1371/journal.pone.0209340
        • Wang Y.
        • Liu T
        Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker.
        Magn Reson Med. 2015; https://doi.org/10.1002/mrm.25358
        • Messroghli D.R.
        • Radjenovic A.
        • Kozerke S.
        • Higgins D.M.
        • Sivananthan M.U.
        • Ridgway J.P
        Modified Look-Locker inversion recovery (MOLLI) for high-resolutionT1 mapping of the heart.
        Magn Reson Med. 2004; 52: 141-146https://doi.org/10.1002/mrm.20110
        • Bieri O.
        • Scheffler K.
        Fundamentals of balanced steady state free precession MRI.
        J Magn Reson Imag. 2013; 38: 2-11https://doi.org/10.1002/jmri.24163
        • Piechnik S.K.
        • Ferreira V.M.
        • Dall'Armellina E.
        • Cochlin L.E.
        • Greiser A.
        • Neubauer S.
        • et al.
        Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold.
        J Cardiovasc Magn Reson. 2010; 12: 69https://doi.org/10.1186/1532-429X-12-69
        • Bradley C.R.
        • Cox E.F.
        • Scott R.A.
        • James M.W.
        • Kaye P.
        • Aithal G.P.
        • et al.
        Multi-organ assessment of compensated cirrhosis patients using quantitative magnetic resonance imaging.
        J Hepatol. 2018; 69: 1015-1024https://doi.org/10.1016/j.jhep.2018.05.037
        • Tunnicliffe E.M.
        • Banerjee R.
        • Pavlides M.
        • Neubauer S.
        • Robson M.D
        A model for hepatic fibrosis: the competing effects of cell loss and iron on shortened modified Look-Locker inversion recovery T 1 (shMOLLI- T 1) in the liver.
        J Magn Reson Imag. 2017; 45: 450-462https://doi.org/10.1002/jmri.25392
        • Banerjee R.
        • Pavlides M.
        • Tunnicliffe E.M.
        • Piechnik S.K.
        • Sarania N.
        • Philips R.
        • et al.
        Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease.
        J Hepatol. 2014; 60: 69-77https://doi.org/10.1016/j.jhep.2013.09.002
        • Pavlides M.
        • Banerjee R.
        • Sellwood J.
        • Kelly C.J.
        • Robson M.D.
        • Booth J.C.
        • et al.
        Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease.
        J Hepatol. 2016; 64: 308-315https://doi.org/10.1016/j.jhep.2015.10.009
        • Pavlides M.
        • Banerjee R.
        • Tunnicliffe E.M.
        • Kelly C.
        • Collier J.
        • Wang L.M.
        • et al.
        Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity.
        Liver Int. 2017; 37: 1065-1073https://doi.org/10.1111/liv.13284
        • Harrison S.A.
        • Dennis A.
        • Fiore M.M.
        • Kelly M.D.
        • Kelly C.J.
        • Paredes A.H.
        • et al.
        Utility and variability of three non-invasive liver fibrosis imaging modalities to evaluate efficacy of GR-MD-02 in subjects with NASH and bridging fibrosis during a phase-2 randomized clinical trial.
        PLoS ONE. 2018; 13e0203054https://doi.org/10.1371/journal.pone.0203054
        • Mojtahed A.
        • Kelly C.J.
        • Herlihy A.H.
        • Kin S.
        • Wilman H.R.
        • McKay A.
        • et al.
        Reference range of liver corrected T1 values in a population at low risk for fatty liver disease—A UK Biobank sub-study, with an appendix of interesting cases.
        Abdom Radiol. 2019; 44: 72-84https://doi.org/10.1007/s00261-018-1701-2
        • Tang A.
        • Cloutier G.
        • Szeverenyi N.M.
        • Sirlin C.B
        Ultrasound elastography and MR elastography for assessing liver fibrosis: part 1, principles and techniques.
        Am J Roentgenol. 2015; https://doi.org/10.2214/AJR.15.14552
        • Sandrin L.
        • Fourquet B.
        • Hasquenoph J.M.
        • Yon S.
        • Fournier C.
        • Mal F.
        • et al.
        Transient elastography: a new noninvasive method for assessment of hepatic fibrosis.
        Ultrasound Med Biol. 2003; https://doi.org/10.1016/j.ultrasmedbio.2003.07.001
        • Şirli R.
        • Sporea I.
        • Popescu A.
        • Danila M
        Ultrasound-based elastography for the diagnosis of portal hypertension in cirrhotics.
        World J Gastroenterol. 2015; https://doi.org/10.3748/wjg.v21.i41.11542
        • Gennisson J.L.
        • Deffieux T.
        • Fink M.
        • Tanter M
        Ultrasound elastography: principles and techniques.
        Diagn Interv Imag. 2013; https://doi.org/10.1016/j.diii.2013.01.022
        • Babu A.S.
        • Wells M.L.
        • Teytelboym O.M.
        • Mackey J.E.
        • Miller F.H.
        • Yeh B.M.
        • et al.
        Elastography in chronic liver disease: modalities, techniques, limitations, and future directions.
        Radiographics. 2016; https://doi.org/10.1148/rg.2016160042
        • Sigrist R.M.S.
        • Liau J.
        • Kaffas A El
        • Chammas M.C.
        • Willmann J.K
        Ultrasound elastography: review of techniques and clinical applications.
        Theranostics. 2017; https://doi.org/10.7150/thno.18650
        • Smith A.D.
        • Porter K.K.
        • Elkassem A.A.
        • Sanyal R.
        • Lockhart M.E
        Current imaging techniques for noninvasive staging of hepatic fibrosis.
        Am J Roentgenol. 2019; https://doi.org/10.2214/AJR.19.21144
        • Piscaglia F.
        • Salvatore V.
        • Mulazzani L.
        • Cantisani V.
        • Colecchia A.
        • Di Donato R.
        • et al.
        Differences in liver stiffness values obtained with new ultrasound elastography machines and Fibroscan: a comparative study.
        Dig Liver Dis. 2017; https://doi.org/10.1016/j.dld.2017.03.001
        • Sugimoto Katsutoshi
        • F Moriyasu
        • Oshiro H.
        • Takeuchi H.
        • Yoshimasu Y.
        • Kasai Y.
        • et al.
        Clinical utilization of shear wave dispersion imaging in diffuse liver disease.
        Ultrasonography. 2019; https://doi.org/10.14366/usg.19031
        • Venkatesh S.K.
        • Ehman R.L.
        Magnetic resonance elastography of abdomen.
        Abdom Imag. 2015; https://doi.org/10.1007/s00261-014-0315-6
        • Singh S.
        • Venkatesh S.K.
        • Wang Z.
        • Miller F.H.
        • Motosugi U.
        • Low R.N.
        • et al.
        Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data.
        Clin Gastroenterol Hepatol. 2015; https://doi.org/10.1016/j.cgh.2014.09.046
        • Ehman R.L.
        • Glaser K.J.
        • Manduca A
        Review of MR elastography applications and recent developments.
        J Magn Reson Imag. 2012; https://doi.org/10.1002/jmri.23597
        • Venkatesh S.K.
        • Yin M.
        • Ehman R.L
        Magnetic resonance elastography of liver: technique, analysis, and clinical applications.
        J Magn Reson Imag. 2013; https://doi.org/10.1002/jmri.23731
        • Godfrey E.M.
        • Mannelli L.
        • Griffin N.
        • Lomas D.J
        Magnetic resonance Elastography in the diagnosis of hepatic fibrosis.
        Semin Ultrasound, CT MRI. 2013; https://doi.org/10.1053/j.sult.2012.11.007
        • Venkatesh S.K.
        • Wang G.
        • Lim S.G.
        • Wee A
        Magnetic resonance Elastography for the detection and staging of liver fibrosis in chronic hepatitis B.
        Eur Radiol. 2014; https://doi.org/10.1007/s00330-013-2978-8
        • Wang Q.B.
        • Zhu H.
        • Liu H.L.
        • Zhang B
        Performance of magnetic resonance elastography and diffusion-weighted imaging for the staging of hepatic fibrosis: a meta-analysis.
        Hepatology. 2012; https://doi.org/10.1002/hep.25610
        • Venkatesh S.K.
        • Xu S.
        • Tai D.
        • Yu H.
        • Wee A
        Correlation of MR elastography with morphometric quantification of liver fibrosis (fibro-C-index) in chronic hepatitis B.
        Magn Reson Med. 2014; https://doi.org/10.1002/mrm.25002
        • Venkatesh S.
        • Takahashi N.
        • Glockner J.
        • Yin M.
        • Talwalkar J.
        • Grimm R.
        • et al.
        Non-invasive diagnosis of liver fibrosis: conventional MR imaging findings versus MR elastography.
        Proc 16th Sci Meet Int Soc Magn Reson Med. 2008;
        • Forghani R.
        • De Man B.
        • Gupta R
        Dual-energy computed tomography: physical principles, approaches to scanning, usage, and implementation: part 2.
        Neuroimag Clin N Am. 2017; https://doi.org/10.1016/j.nic.2017.03.003
        • Shuman W.P.
        • Green D.E.
        • Busey J.M.
        • Mitsumori L.M.
        • Choi E.
        • Koprowicz K.M.
        • et al.
        Dual-energy liver CT: effect of monochromatic imaging on lesion detection, conspicuity, and contrast-to-noise ratio of hypervascular lesions on late arterial phase.
        Am J Roentgenol. 2014; https://doi.org/10.2214/AJR.13.11337
        • Dai X.
        • Schlemmer H.P.
        • Schmidt B.
        • Höh K.
        • Xu K.
        • Ganten T.M.
        • et al.
        Quantitative therapy response assessment by volumetric iodine-uptake measurement: initial experience in patients with advanced hepatocellular carcinoma treated with sorafenib.
        Eur J Radiol. 2013; https://doi.org/10.1016/j.ejrad.2012.11.013
        • Apfaltrer P.
        • Meyer M.
        • Meier C.
        • Henzler T.
        • Barraza J.M.
        • Dinter D.J.
        • et al.
        Contrast-enhanced dual-energy ct of gastrointestinal stromal tumors: is iodine-related attenuation a potential indicator of tumor response?.
        Invest Radiol. 2012; https://doi.org/10.1097/RLI.0b013e31823003d2
        • Sun T.
        • Lin X.
        • Chen K
        Evaluation of hepatic steatosis using dual-energy CT with MR comparison.
        Front Biosci - Landmark. 2014; https://doi.org/10.2741/4288
        • Lamb P.
        • Sahani D.V.
        • Fuentes-Orrego J.M.
        • Patino M.
        • Ghosh A.
        • Mendonҫa P.R.S.
        Stratification of patients with liver fibrosis using dual-energy CT.
        IEEE Trans Med Imag. 2015; https://doi.org/10.1109/TMI.2014.2353044
        • Gillies R.J.
        • Kinahan P.E.
        • Hricak H
        Radiomics: images are more than pictures, they are data.
        Radiology. 2016; https://doi.org/10.1148/radiol.2015151169
        • Rizzo S.
        • Botta F.
        • Raimondi S.
        • Origgi D.
        • Fanciullo C.
        • Morganti A.G.
        • et al.
        Radiomics: the facts and the challenges of image analysis.
        Eur Radiol Exp. 2018; https://doi.org/10.1186/s41747-018-0068-z
        • Varghese B.A.
        • Cen S.Y.
        • Hwang D.H.
        • Duddalwar V.A
        Texture analysis of imaging: what radiologists need to know.
        Am J Roentgenol. 2019; 212: 520-528https://doi.org/10.2214/AJR.18.20624
        • Papanikolaou N.
        • Santinha J
        An Introduction to Radiomics : capturing tumour biology in space and time.
        Oncol Imag. 2018;