Contribution of semiquantitative analysis with dynamic contrast enhanced magnetic resonance imaging to the differential diagnosis of focal liver lesions
DOI:
https://doi.org/10.15584/ejcem.2023.2.6Keywords:
adult liver cancer, benign hepatoma, perfusion imagingAbstract
Introduction and aim. We aimed to evaluate the usefulness of dynamic contrast-enhanced (DCE) MRI semiquantitative analysis values in focal liver lesions (FLL) to provide additional qualities that can be used in daily practice in the differential diagnosis of lesions.
Material and methods. This retrospective study included 91 patients with liver masses on DCE-MRI. The sensitivity and specificity of time intensity curves (TIC) and semiquantitative analysis values were evaluated to differentiate benign and malignant lesions.
Results. The study included 91 patients (376 lesions), aged between 28-81 years. Of the lesions, 303 were malignant and 73 were benign. In TIC semiquantitative analysis, it was found that “Tpeak” and “wash-out” rate values showed differences, especially in the differentiation of HCC, metastasis, and hemangioma. Area under curve, maximum relative enhancement, and “wash-in” and “wash-out” values of metastases and hemangiomas were different. Brevity of enhancement values of HSK, hemangiomas, and metastases were found to be different. The risk of malignancy was found to be high when the “wash-out” ratio was above 0.08 (sensitivity: 64.3%, specificity: 70.4%).
Conclusion. We think that the 0.08 threshold value we found for the washout ratio with DCE-MRI semiquantitative analysis data will be useful in daily practice in the differentiation of malignant and benign FLL.
Downloads
References
Matos AP, Velloni F, Ramalho M, AlObaidy M, Rajapaksha A, Semelka RC. Focal liver lesions: Practical magnetic resonance imaging approach. World J Hepatol. 2015;7(16):1987-2008. doi: 10.4254/wjh.v7.i16.1987
Cogley JR, Miller FH. MR imaging of benign focal liver lesions. Radiol Clin North Am. 2014;52(4):657-682. doi: 10.1016/j.rcl.2014.02.005
Watanabe A, Ramalho M, AlObaidy M, Kim HJ, Velloni FG, Semelka RC. Magnetic resonance imaging of the cirrhotic liver: An update. World J Hepatol. 2015;7(3):468-487. doi: 10.4254/wjh.v7.i3.468
Belghiti J, Cauchy F, Paradis V, Vilgrain V. Diagnosis and management of solid benign liver lesions. Nat Rev Gastroenterol Hepatol. 2014;11(12):737-749. doi: 10.1038/nrgastro.2014.151
Ronot M, Lambert S, Daire JL, et al. Can we justify not doing liver perfusion imaging in 2013?. Diagn Interv Imaging. 2013;94(12):1323-1336. doi: 10.1016/j.diii.2013.06.005
Cannella R, Sartoris R, Grégory J, et al. Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice. Br J Radiol. 2021;94(1122):20210220. doi: 10.1259/bjr.20210220
Hussain SM, Semelka RC. Hepatic imaging: comparison of modalities. Radiol Clin North Am. 2005;43(5):929-ix. doi: 10.1016/j.rcl.2005.05.006
Ronot M, Clift AK, Vilgrain V, Frilling A. Functional imaging in liver tumours. J Hepatol. 2016;65(5):1017-1030. doi: 10.1016/j.jhep.2016.06.024
Bader TR, Herneth AM, Blaicher W, et al. Hepatic perfusion after liver transplantation: noninvasive measurement with dynamic single-section CT. Radiology. 1998;209(1):129-134. doi: 10.1148/radiology.209.1.9769823
Leggett DA, Kelley BB, Bunce IH, Miles KA. Colorectal cancer: diagnostic potential of CT measurements of hepatic perfusion and implications for contrast enhancement protocols. Radiology. 1997;205(3):716-720. doi: 10.1148/radiology.205.3.9393526
Van Beers BE, Leconte I, Materne R, Smith AM, Jamart J, Horsmans Y. Hepatic perfusion parameters in chronic liver disease: dynamic CT measurements correlated with disease severity. AJR Am J Roentgenol. 2001;176(3):667-673. doi: 10.2214/ajr.176.3.1760667
Nino-Murcia M, Olcott EW, Jeffrey RB Jr, Lamm RL, Beaulieu CF, Jain KA. Focal liver lesions: pattern-based classification scheme for enhancement at arterial phase CT. Radiology. 2000;215(3):746-751. doi: 10.1148/radiology.215.3.r00jn03746
Ippolito D, Colombo M, Trattenero C, et al. Diagnostic Value of Semiquantitative Analysis of Dynamic Susceptibility Contrast Magnetic Resonance Imaging with GD-EOB-DTPA in Focal Liver Lesions Characterization: A Feasibility Study. Gastroenterol Res Pract. 2015;2015:630273. doi: 10.1155/2015/630273
Reimer P, Saini S, Kwong KK, Cohen MS, Weissleder R, Brady TJ. Dynamic gadolinium-enhanced echo-planar MR imaging of the liver: effect of pulse sequence and dose on enhancement. J Magn Reson Imaging. 1994;4(3):331-335. doi: 10.1002/jmri.1880040318
Materne R, Smith AM, Peeters F, et al. Assessment of hepatic perfusion parameters with dynamic MRI. Magn Reson Med. 2002;47(1):135-142. doi: 10.1002/mrm.10045
Van Beers BE, Materne R, Annet L, et al. Capillarization of the sinusoids in liver fibrosis: noninvasive assessment with contrast-enhanced MRI in the rabbit. Magn Reson Med. 2003;49(4):692-699. doi: 10.1002/mrm.10420
Annet L, Materne R, Danse E, Jamart J, Horsmans Y, Van Beers BE. Hepatic flow parameters measured with MR imaging and Doppler US: correlations with degree of cirrhosis and portal hypertension. Radiology. 2003;229(2):409-414. doi: 10.1148/radiol.2292021128
Alicioglu B, Guler O, Bulakbasi N, Akpinar S, Tosun O, Comunoglu C. Utility of semiquantitative parameters to differentiate benign and malignant focal hepatic lesions. Clin Imaging. 2013;37(4):692-696. doi: 10.1016/j.clinimag.2013.01.012
Chandarana H, Taouli B. Diffusion and perfusion imaging of the liver. Eur J Radiol. 2010;76(3):348-358. doi: 10.1016/j.ejrad.2010.03.016
Koh DM, Padhani AR. Functional magnetic resonance imaging of the liver: parametric assessments beyond morphology. Magn Reson Imaging Clin N Am. 2010;18(3):565-xii. doi: 10.1016/j.mric.2010.07.002
Pahwa S, Liu H, Chen Y, et al. Quantitative perfusion imaging of neoplastic liver lesions: A multi-institution study. Sci Rep. 2018;8(1):4990. doi: 10.1038/s41598-018-20726-1
Ghodasara S, Pahwa S, Dastmalchian S, Gulani V, Chen Y. Free-Breathing 3D Liver Perfusion Quantification Using a Dual-Input Two-Compartment Model. Sci Rep. 2017;7(1):17502. doi: 10.1038/s41598-017-17753-9
Totman JJ, O'gorman RL, Kane PA, Karani JB. Comparison of the hepatic perfusion index measured with gadolinium-enhanced volumetric MRI in controls and in patients with colorectal cancer. Br J Radiol. 2005;78(926):105-109. doi: 10.1259/bjr/13525061
Koh TS, Thng CH, Hartono S, et al. Dynamic contrast-enhanced MRI of neuroendocrine hepatic metastases: A feasibility study using a dual-input two-compartment model. Magn Reson Med. 2011;65(1):250-260. doi: 10.1002/mrm.22596
Taouli B, Johnson RS, Hajdu CH, et al. Hepatocellular carcinoma: perfusion quantification with dynamic contrast-enhanced MRI. AJR Am J Roentgenol. 2013;201(4):795-800. doi: 10.2214/AJR.12.9798
Ippolito D, Trattenero C, Talei Franzesi C, et al. Dynamic Contrast-Enhanced Magnetic Resonance Imaging With Gadolinium Ethoxybenzyl Diethylenetriamine Pentaacetic Acid for Quantitative Assessment of Vascular Effects on Hepatocellular-Carcinoma Lesions Treated by Transarterial Chemoembolization or Radiofrequency Ablation. J Comput Assist Tomogr. 2016;40(5):692-700. doi: 10.1097/RCT.0000000000000427
Campos M, Candelária I, Papanikolaou N, et al. Perfusion Magnetic Resonance as a Biomarker for Sorafenib-Treated Advanced Hepatocellular Carcinoma: A Pilot Study. GE Port J Gastroenterol. 2019;26(4):260-267. doi: 10.1159/000493351
Braren R, Altomonte J, Settles M, et al. Validation of preclinical multiparametric imaging for prediction of necrosis in hepatocellular carcinoma after embolization. J Hepatol. 2011;55(5):1034-1040. doi: 10.1016/j.jhep.2011.01.049
Michielsen K, De Keyzer F, Verslype C, Dymarkowski S, van Malenstein H, Oyen R, Maleux G, et al. Pretreatment DCE-MRI for prediction of pfs in patients with inoperable HCC treated with TACE. Cancer Imaging 2011;11(1A):114. doi: 10.1102/1470-7330.2011.9058
Hsu CY, Shen YC, Yu CW, et al. Dynamic contrast-enhanced magnetic resonance imaging biomarkers predict survival and response in hepatocellular carcinoma patients treated with sorafenib and metronomic tegafur/uracil. J Hepatol. 2011;55(4):858-865. doi: 10.1016/j.jhep.2011.01.032
Kim KA, Park MS, Ji HJ, et al. Diffusion and perfusion MRI prediction of progression-free survival in patients with hepatocellular carcinoma treated with concurrent chemoradiotherapy. J Magn Reson Imaging. 2014;39(2):286-292. doi: 10.1002/jmri.24161
Chen BB, Hsu CY, Yu CW, et al. Early perfusion changes within 1 week of systemic treatment measured by dynamic contrast-enhanced MRI may predict survival in patients with advanced hepatocellular carcinoma. Eur Radiol. 2017;27(7):3069-3079. doi: 10.1007/s00330-016-4670-2
Coenegrachts K, Bols A, Haspeslagh M, Rigauts H. Prediction and monitoring of treatment effect using T1-weighted dynamic contrast-enhanced magnetic resonance imaging in colorectal liver metastases: potential of whole tumour ROI and selective ROI analysis. Eur J Radiol. 2012;81(12):3870-3876. doi: 10.1016/j.ejrad.2012.07.022
De Bruyne S, Van Damme N, Smeets P, et al. Value of DCE-MRI and FDG-PET/CT in the prediction of response to preoperative chemotherapy with bevacizumab for colorectal liver metastases. Br J Cancer. 2012;106(12):1926-1933. doi: 10.1038/bjc.2012.184
Hirashima Y, Yamada Y, Tateishi U, et al. Pharmacokinetic parameters from 3-Tesla DCE-MRI as surrogate biomarkers of antitumor effects of bevacizumab plus FOLFIRI in colorectal cancer with liver metastasis. Int J Cancer. 2012;130(10):2359-2365. doi: 10.1002/ijc.26282
Galbraith SM, Lodge MA, Taylor NJ, et al. Reproducibility of dynamic contrast-enhanced MRI in human muscle and tumours: comparison of quantitative and semi-quantitative analysis. NMR Biomed. 2002;15(2):132-142. doi: 10.1002/nbm.731
Chen J, Si Y, Zhao K, et al. Evaluation of quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging in qualitative diagnosis of hepatic masses. BMC Med Imaging. 2018;18(1):56. doi: 10.1186/s12880-018-0299-8
Ippolito D, Colombo M, Trattenero C, et al. Diagnostic Value of Semiquantitative Analysis of Dynamic Susceptibility Contrast Magnetic Resonance Imaging with GD-EOB-DTPA in Focal Liver Lesions Characterization: A Feasibility Study. Gastroenterol Res Pract. 2015;2015:630273. doi: 10.1155/2015/630273
Goh V, Padhani AR. Imaging tumor angiogenesis: functional assessment using MDCT or MRI?. Abdom Imaging. 2006;31(2):194-199. doi: 10.1007/s00261-005-0387-4
Leach MO, Brindle KM, Evelhoch JL, et al. Assessment of antiangiogenic and antivascular therapeutics using MRI: recommendations for appropriate methodology for clinical trials. Br J Radiol. 2003;76 Spec No 1:S87-S91. doi: 10.1259/bjr/15917261
Thng CH, Koh TS, Collins DJ, Koh DM. Perfusion magnetic resonance imaging of the liver. World J Gastroenterol. 2010;16(13):1598-1609. doi: 10.3748/wjg.v16.i13.1598
Materne R, Van Beers BE, Smith AM, et al. Non-invasive quantification of liver perfusion with dynamic computed tomography and a dual-input one-compartmental model. Clin Sci (Lond). 2000;99(6):517-525.
Abdullah SS, Pialat JB, Wiart M, et al. Characterization of hepatocellular carcinoma and colorectal liver metastasis by means of perfusion MRI. J Magn Reson Imaging. 2008;28(2):390-395. doi: 10.1002/jmri.21429
Ito K. Hepatocellular carcinoma: conventional MRI findings including gadolinium-enhanced dynamic imaging. Eur J Radiol. 2006;58(2):186-199. doi:10.1016/j.ejrad.2005.11.039
Donati F, Boraschi P, Gigoni R, Salemi S, Falaschi F, Bartolozzi C. Focal nodular hyperplasia of the liver: diffusion and perfusion MRI characteristics. Magn Reson Imaging. 2013;31(1):10-16. doi: 10.1016/j.mri.2012.06.031
Yu JS, Rofsky NM. Hepatic metastases: perilesional enhancement on dynamic MRI. AJR Am J Roentgenol. 2006;186(4):1051-1058. doi: 10.2214/AJR.04.169
Taouli B. Diffusion-weighted MR, imaging for liver lesion characterization: a critical look. Radiology. 2012;262:378-380.
Soyer P, Corno L, Boudiaf M, et al. Differentiation between cavernous hemangiomas and untreated malignant neoplasms of the liver with free-breathing diffusion-weighted MR imaging: comparison with T2-weighted fast spin-echo MR imaging. Eur J Radiol. 2011;80:316–24.
Wagner M, Doblas S, Daire JL, et al. Diffusion-weighted MR imaging for the regional characterization of liver tumors. Radiology. 2012;264:464-472.
Donato H, França M, Candelária I, Caseiro-Alves F. Liver MRI: From basic protocol to advanced techniques. Eur J Radiol. 2017;93:30-39. doi: 10.1016/j.ejrad.2017.05.028
Quantitative Imaging Biomarkers Alliance. 2021. Available from: https://www.rsna. org/en/research/quantitative-imaging- biomarkers-alliance. Accessed February 1, 2021.
Biomarker Inventory. Available from: https://www.myesr.org/research/biomarkers-inventory. Accessed February 1, 2021.
Weiss J, Ruff C, Grosse U, Grözinger G, Horger M, Nikolaou K, et al. Assessment of hepatic perfusion using GRASP MRI: bringing liver MRI on a new level. Invest Radiol. 2019; 54:737-743. doi: 10.1097/RLI.0000000000000586
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 European Journal of Clinical and Experimental Medicine
This work is licensed under a Creative Commons Attribution 4.0 International License.
Our open access policy is in accordance with the Budapest Open Access Initiative (BOAI) definition: this means that articles have free availability on the public Internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from having access to the Internet itself.
All articles are published with free open access under the CC-BY Creative Commons attribution license (the current version is CC-BY, version 4.0). If you submit your paper for publication by the Eur J Clin Exp Med, you agree to have the CC-BY license applied to your work. Under this Open Access license, you, as the author, agree that anyone may download and read the paper for free. In addition, the article may be reused and quoted provided that the original published version is cited. This facilitates freedom in re-use and also ensures that Eur J Clin Exp Med content can be mined without barriers for the research needs.
