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"Woo Kyoung Jeong"

Review

Hepatic neoplasm

Radiomics and radiogenomics of primary liver cancers
Woo Kyoung Jeong, Neema Jamshidi, Ely Richard Felker, Steven Satish Raman, David Shinkuo Lu
Clin Mol Hepatol 2019;25(1):21-29.
Published online November 16, 2018
DOI: https://doi.org/10.3350/cmh.2018.1007
Concurrent advancements in imaging and genomic biomarkers have created opportunities to identify non-invasive imaging surrogates of molecular phenotypes. In order to develop such imaging surrogates radiomics and radiogenomics/imaging genomics will be necessary; there has been consistent progress in these fields for primary liver cancers. In this article we evaluate the current status of the field specifically with regards to hepatocellular carcinoma and intrahepatic cholangiocarcinoma, highlighting some of the up and coming results that were presented at the annual Radiological Society of North America Conference in 2017. There are an increasing number of studies in this area with a bias towards quantitative feature measurement, which is expected to benefit reproducibility of the findings and portends well for the future development of biomarkers for diagnosis, prognosis, and treatment response assessment. We review some of the advancements and look forward to some of the exciting future applications that are anticipated as the field develops.

Citations

Citations to this article as recorded by  Crossref logo
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    La radiologia medica.2025;[Epub]     CrossRef
  • Identifying potential biomarkers of microvascular invasion in hepatocellular carcinoma and predict overall survival based on multi-omics
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    Chinese Journal of Academic Radiology.2025;[Epub]     CrossRef
  • Application of artificial intelligence radiomics in the diagnosis, treatment, and prognosis of hepatocellular carcinoma
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  • Radiogenomics of Intrahepatic Cholangiocarcinoma: Correlation of Imaging Features With BAP1 and FGFR Molecular Subtypes
    Veronica Cox, Milind Javle, Jia Sun, Hyunseon Kang
    Journal of Computer Assisted Tomography.2024; 48(6): 868.     CrossRef
  • MR radiomics to predict microvascular invasion status and biological process in combined hepatocellular carcinoma-cholangiocarcinoma
    Yuyao Xiao, Fei Wu, Kai Hou, Fang Wang, Changwu Zhou, Peng Huang, Chun Yang, Mengsu Zeng
    Insights into Imaging.2024;[Epub]     CrossRef
  • Inter-reader agreement for LR-M imaging features: a premise for better imaging-based diagnosis in liver imaging
    Jaeseung Shin
    Journal of Liver Cancer.2024; 24(2): 124.     CrossRef
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    Jia-Wei Xu, Bing-Hua Li, De-Cai Yu
    Hepatoma Research.2024;[Epub]     CrossRef
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    Yanhua Huang, Hongwei Qian
    Journal of Hepatocellular Carcinoma.2024; Volume 11: 2159.     CrossRef
  • Development of a flexible feature selection framework in radiomics-based prediction modeling: Assessment with four real-world datasets
    Sungsoo Hong, Sungjun Hong, Eunsun Oh, Won Jae Lee, Woo Kyoung Jeong, Kyunga Kim
    Scientific Reports.2024;[Epub]     CrossRef
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    Liying Ren, Dong Bo Chen, Xuanzhi Yan, Shaoping She, Yao Yang, Xue Zhang, Weijia Liao, Hongsong Chen
    Journal of Hepatocellular Carcinoma.2024; Volume 11: 2359.     CrossRef
  • Machine learning radiomics to predict the early recurrence of intrahepatic cholangiocarcinoma after curative resection: A multicentre cohort study
    Zhiyuan Bo, Bo Chen, Yi Yang, Fei Yao, Yicheng Mao, Jiangqiao Yao, Jinhuan Yang, Qikuan He, Zhengxiao Zhao, Xintong Shi, Jicai Chen, Zhengping Yu, Yunjun Yang, Yi Wang, Gang Chen
    European Journal of Nuclear Medicine and Molecular Imaging.2023; 50(8): 2501.     CrossRef
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    Cody Criss, Arpit M Nagar, Mina S Makary
    World Journal of Radiology.2023; 15(3): 56.     CrossRef
  • A novel collaborative self-supervised learning method for radiomic data
    Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Nehal A. Parikh, Lili He
    NeuroImage.2023; 277: 120229.     CrossRef
  • MRI-based radiomics signature: a potential imaging biomarker for prediction of microvascular invasion in combined hepatocellular-cholangiocarcinoma
    Guofeng Zhou, Yang Zhou, Xun Xu, Jiulou Zhang, Chen Xu, Pengju Xu, Feipeng Zhu
    Abdominal Radiology.2023; 49(1): 49.     CrossRef
  • Review of the Application of Dual Drug Delivery Nanotheranostic Agents in the Diagnosis and Treatment of Liver Cancer
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    Molecules.2023; 28(20): 7004.     CrossRef
  • Differentiation of Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma through MRI Radiomics
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    Cancers.2023; 15(22): 5373.     CrossRef
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    Frontiers in Signal Processing.2023;[Epub]     CrossRef
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    Xiaoming Li, Lin Cheng, Chuanming Li, Xianling Hu, Xiaofei Hu, Liang Tan, Qing Li, Chen Liu, Jian Wang
    Journal of Clinical and Translational Hepatology.2022; 10(1): 63.     CrossRef
  • Longitudinal CT Imaging to Explore the Predictive Power of 3D Radiomic Tumour Heterogeneity in Precise Imaging of Mantle Cell Lymphoma (MCL)
    Catharina Silvia Lisson, Christoph Gerhard Lisson, Sherin Achilles, Marc Fabian Mezger, Daniel Wolf, Stefan Andreas Schmidt, Wolfgang M. Thaiss, Johannes Bloehdorn, Ambros J. Beer, Stephan Stilgenbauer, Meinrad Beer, Michael Götz
    Cancers.2022; 14(2): 393.     CrossRef
  • MRE-based NASH score for diagnosis of nonalcoholic steatohepatitis in patients with nonalcoholic fatty liver disease
    Young-Sun Lee, Ji Eun Lee, Hyon-Seung Yi, Young Kul Jung, Dae Won Jun, Ji Hoon Kim, Yeon Seok Seo, Hyung Joon Yim, Baek-hui Kim, Jeong Woo Kim, Chang Hee Lee, Jong Eun Yeon, Juneyoung Lee, Soon Ho Um, Kwan Soo Byun
    Hepatology International.2022; 16(2): 316.     CrossRef
  • Prediction of TACE Treatment Response in a Preoperative MRI via Analysis of Integrating Deep Learning and Radiomics Features
    Yuchi Tian, Temitope Emmanuel Komolafe, Tao Chen, Bo Zhou, Xiaodong Yang
    Journal of Medical and Biological Engineering.2022; 42(2): 169.     CrossRef
  • Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma
    Catharina Silvia Lisson, Christoph Gerhard Lisson, Marc Fabian Mezger, Daniel Wolf, Stefan Andreas Schmidt, Wolfgang M. Thaiss, Eugen Tausch, Ambros J. Beer, Stephan Stilgenbauer, Meinrad Beer, Michael Goetz
    Cancers.2022; 14(8): 2008.     CrossRef
  • Comparing Radiomics features of tumour and healthy liver tissue in a limited CT dataset: A machine learning study
    S. Lysdahlgaard
    Radiography.2022; 28(3): 718.     CrossRef
  • PET-Based Radiogenomics Supports mTOR Pathway Targeting for Hepatocellular Carcinoma
    Jihyun An, Minyoung Oh, Seog-Young Kim, Yoo-Jin Oh, Bora Oh, Ji-Hye Oh, Wonkyung Kim, Jin Hwa Jung, Ha Il Kim, Jae-Seung Kim, Chang Ohk Sung, Ju Hyun Shim
    Clinical Cancer Research.2022; 28(9): 1821.     CrossRef
  • Clinical relevance of biomarkers in cholangiocarcinoma: critical revision and future directions
    Rocio I R Macias, Vincenzo Cardinale, Timothy J Kendall, Matias A Avila, Maria Guido, Cedric Coulouarn, Chiara Braconi, Adam E Frampton, John Bridgewater, Diletta Overi, Stephen P Pereira, Marco Rengo, Jakob N Kather, Angela Lamarca, Federica Pedica, Alej
    Gut.2022; 71(8): 1669.     CrossRef
  • Diagnostic Value of Multislice Spiral Computed Tomography Combined with Serum AFP, TSGF, and GP73 Assay in the Diagnosis of Primary Liver Cancer
    Chuanwen Yu, Chuang Sun, Shangxiang Chen
    Evidence-Based Complementary and Alternative Medicine.2022; 2022: 1.     CrossRef
  • Radiomics nomogram based on multi-parametric magnetic resonance imaging for predicting early recurrence in small hepatocellular carcinoma after radiofrequency ablation
    Xiaojuan Zhang, Chuandong Wang, Dan Zheng, Yuting Liao, Xiaoyang Wang, Zhifeng Huang, Qun Zhong
    Frontiers in Oncology.2022;[Epub]     CrossRef
  • Application of texture analysis of CT and MR images to determine the histologic grade of hepatocellular cancer and it’s differential diagnosis: a review
    M. Yu. Shantarevich, G. G. Karmazanovsky
    Research and Practical Medicine Journal.2022; 9(3): 129.     CrossRef
  • Radiomics-Based Prediction of Future Portal Vein Tumor Infiltration in Patients with HCC—A Proof-of-Concept Study
    Fabian Stoehr, Roman Kloeckner, Daniel Pinto dos Santos, Mira Schnier, Lukas Müller, Aline Mähringer-Kunz, Thomas Dratsch, Sebastian Schotten, Arndt Weinmann, Peter Robert Galle, Jens Mittler, Christoph Düber, Felix Hahn
    Cancers.2022; 14(24): 6036.     CrossRef
  • CT-Based Radiomics Nomogram: A Potential Tool for Differentiating Hepatocellular Adenoma From Hepatocellular Carcinoma in the Noncirrhotic Liver
    Pei Nie, Ning Wang, Jing Pang, Guangjie Yang, Shaofeng Duan, Jingjing Chen, Wenjian Xu
    Academic Radiology.2021; 28(6): 799.     CrossRef
  • Role of artificial intelligence in hepatobiliary and pancreatic surgery
    Hassaan Bari, Sharan Wadhwani, Bobby V M Dasari
    World Journal of Gastrointestinal Surgery.2021; 13(1): 7.     CrossRef
  • An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer
    Tiancheng He, Joy Nolte Fong, Linda W. Moore, Chika F. Ezeana, David Victor, Mukul Divatia, Matthew Vasquez, R. Mark Ghobrial, Stephen T.C. Wong
    Computerized Medical Imaging and Graphics.2021; 89: 101894.     CrossRef
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    H.M.C. Cheung, D. Rubin
    Clinical Radiology.2021; 76(10): 728.     CrossRef
  • A Clinical-Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Gallbladder Cancer
    Xingyu Liu, Xiaoyuan Liang, Lingxiang Ruan, Sheng Yan
    Frontiers in Oncology.2021;[Epub]     CrossRef
  • Pharmacological Inhibition of Sonic Hedgehog Signaling Suppresses Tumor Development in a Murine Model of Intrahepatic Cholangiocarcinoma
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  • Radiomics: a primer on high-throughput image phenotyping
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    Abdominal Radiology.2021; 47(9): 2986.     CrossRef
  • Evaluation of Angiogenesis and Pathological Classification of Extrahepatic Cholangiocarcinoma by Dynamic MR Imaging for E-Healthcare
    Jinyun Tan, Xijun Sun, Shaoyu Wang, Baoqin Ma, Zhaohui Chen, Yaowei Shi, Li Zhang, Mohd Asif Shah, Malik Alazzam
    Journal of Healthcare Engineering.2021; 2021: 1.     CrossRef
  • Determination of optimized set of b-values for Apparent Diffusion Coefficient mapping in liver Diffusion-Weighted MRI
    Óscar Peña-Nogales, Diego Hernando, Santiago Aja-Fernández, Rodrigo de Luis-Garcia
    Journal of Magnetic Resonance.2020; 310: 106634.     CrossRef
  • A Comparison of the Efficiency of Using a Deep CNN Approach with Other Common Regression Methods for the Prediction of EGFR Expression in Glioblastoma Patients
    Mohammadreza Hedyehzadeh, Keivan Maghooli, Mohammad MomenGharibvand, Stephen Pistorius
    Journal of Digital Imaging.2020; 33(2): 391.     CrossRef
  • A CT-based radiomics nomogram for differentiation of focal nodular hyperplasia from hepatocellular carcinoma in the non-cirrhotic liver
    Pei Nie, Guangjie Yang, Jian Guo, Jingjing Chen, Xiaoli Li, Qinglian Ji, Jie Wu, Jingjing Cui, Wenjian Xu
    Cancer Imaging.2020;[Epub]     CrossRef
  • Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: Initial Application of a Radiomic Algorithm Based on Grayscale Ultrasound Images
    Yi Dong, Liu Zhou, Wei Xia, Xing-Yu Zhao, Qi Zhang, Jun-Ming Jian, Xin Gao, Wen-Ping Wang
    Frontiers in Oncology.2020;[Epub]     CrossRef
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    Hongxi Wang, Yi Zhou, Li Li, Wenxiu Hou, Xuelei Ma, Rong Tian
    European Radiology.2020; 30(11): 6228.     CrossRef
  • Radiographic imaging assessment of prognosis of intrahepatic cholangiocarcinoma
    Xiaoqing Lin, Jinyuan Liao
    Chinese Journal of Academic Radiology.2020; 3(2): 94.     CrossRef
  • Assessing prognosis in cholangiocarcinoma: a review of promising genetic markers and imaging approaches
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    Expert Opinion on Orphan Drugs.2020; 8(9): 357.     CrossRef
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  • Risk Factors for Hepatocellular Carcinoma Recurrence and Survival after Liver Transplantation in Patients with HCV‐Related Cirrhosis
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  • Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks
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    International Journal of Computer Assisted Radiology and Surgery.2019; 14(8): 1275.     CrossRef
  • Radiomics in hepatocellular carcinoma: a quantitative review
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    Hepatology International.2019; 13(5): 546.     CrossRef
  • Development and validation of a prognostic model for patients with hepatocellular carcinoma undergoing radiofrequency ablation
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    Cancer Medicine.2019; 8(11): 5023.     CrossRef
  • Radiomics models for diagnosing microvascular invasion in hepatocellular carcinoma: which model is the best model?
    Ming Ni, Xiaoming Zhou, Qian Lv, Zhiming Li, Yuanxiang Gao, Yongqi Tan, Jihua Liu, Fang Liu, Haiyang Yu, Linlin Jiao, Gang Wang
    Cancer Imaging.2019;[Epub]     CrossRef
  • Radiogenomics of Oncology
    Jason Chiang, Neema Jamshidi
    Advances in Clinical Radiology.2019; 1: 71.     CrossRef
  • The Many Facets of Tumor Heterogeneity: Is Metabolism Lagging Behind?
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    Cancers.2019; 11(10): 1574.     CrossRef
  • 17,659 View
  • 439 Download
  • 56 Web of Science
  • Crossref

Editorials

Liver Transplantation

Clinical implication of hepatic volumetry for living donor liver transplantation
Woo Kyoung Jeong
Clin Mol Hepatol 2018;24(1):51-53.
Published online March 22, 2018
DOI: https://doi.org/10.3350/cmh.2018.1003

Citations

Citations to this article as recorded by  Crossref logo
  • The Effect of Portal Vein Variants on the Margin of Error in Graft Volume Calculation in Living Donor Right Lobe Liver Transplantation
    Feyza Sönmez Topcu, Veysel Ersan, Emrah Şahin, Adem Tunçer, Hasret Ayyıldız Civan, Abuzer Dirican, Bülent Ünal
    Transplantation Proceedings.2025; 57(9): 1773.     CrossRef
  • Multivariable linear model for predicting graft weight based on 3-dimensional volumetry in regards to body weight change of living liver donor: an observational cohort study
    Seungwook Han, Jinsoo Rhu, Soyoung Lim, Gyu-seong Choi, Jong Man Kim, Jae-Won Joh
    Annals of Surgical Treatment and Research.2024; 107(2): 91.     CrossRef
  • Accuracy and Efficiency of Right-Lobe Graft Weight Estimation Using Deep-Learning-Assisted CT Volumetry for Living-Donor Liver Transplantation
    Rohee Park, Seungsoo Lee, Yusub Sung, Jeeseok Yoon, Heung-Il Suk, Hyoungjung Kim, Sanghyun Choi
    Diagnostics.2022; 12(3): 590.     CrossRef
  • 11,236 View
  • 96 Download
  • 3 Web of Science
  • Crossref

Hepatic neoplasm

Surveillance of hepatocellular carcinoma: is only ultrasound enough?
Woo Kyoung Jeong
Clin Mol Hepatol 2017;23(3):222-223.
Published online September 19, 2017
DOI: https://doi.org/10.3350/cmh.2017.0046

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    Narendra Singh Choudhary, Neeraj Saraf, Sanjiv Saigal, Arvinder S. Soin
    Journal of Hepatology.2020; 73(1): 212.     CrossRef
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  • 169 Download
  • 7 Web of Science
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Liver Imagings

Hepatic neoplasm

Intraductal malignant tumors in the liver mimicking cholangiocarcinoma: Imaging features for differential diagnosis
Ah Yeong Kim, Woo Kyoung Jeong
Clin Mol Hepatol 2016;22(1):192-197.
Published online March 28, 2016
DOI: https://doi.org/10.3350/cmh.2016.22.1.192

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Citations to this article as recorded by  Crossref logo
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    Hyo Jung Park, So Yeon Kim, Hyoung Jung Kim, Seung Soo Lee, Gil Sun Hong, Jae Ho Byun, Seung-Mo Hong, Moon-Gyu Lee
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  • 14,854 View
  • 247 Download
  • 13 Web of Science
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Benign liver tumors and cystic disease of liver

Benign nodules mimicking hepatocellular carcinoma on gadoxetic acid-enhanced liver MRI
Kyoung Doo Song, Woo Kyoung Jeong
Clin Mol Hepatol 2015;21(2):187-191.
Published online June 26, 2015
DOI: https://doi.org/10.3350/cmh.2015.21.2.187

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  • Magnetic resonance findings of hepatic epithelioid hemangioendothelioma: emphasis on hepatobiliary phase using Gd-EOB-DTPA
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    Abdominal Radiology.2017; 42(9): 2261.     CrossRef
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Original Article

Hepatic neoplasm

Alteration of laboratory findings after radiofrequency ablation of hepatocellular carcinoma: relationship to severity of the underlying liver disease and the ablation volume
Sang-Wook Shin, Woo Kyoung Jeong, Sanghyeok Lim, Yongsoo Kim, Jinoo Kim
Clin Mol Hepatol 2015;21(1):71-79.
Published online March 25, 2015
DOI: https://doi.org/10.3350/cmh.2015.21.1.71
Background/Aims

To investigate sequential changes in laboratory markers after radiofrequency ablation (RFA) of hepatocellular carcinoma (HCC) and the relationship of these changes to the severity of the underlying liver disease.

Methods

This retrospective analysis included 65 patients (44 males, 21 females) who underwent RFA of HCC. Hematologic and biochemical markers were assessed at the pre-RFA period and 1 day, 2-3 days, and 1-2 weeks after RFA. We classified the subjects into two groups: Child-Pugh A (n=41) and Child-Pugh B (n=24). The ablative margin volume (AMV) of each patient was measured. We analyzed the changes in laboratory profiles from the baseline, and investigated whether these laboratory changes were correlated with the AMV and the Child-Pugh classification.

Results

Most of the laboratory values peaked at 2-3 days after RFA. AMV was significantly correlated with changes in WBC count, hemoglobin level, and serum total bilirubin level (Pearson's correlation coefficient, 0.324-0.453; P<0.05). The alanine aminotransferase (ALT) level varied significantly over time (P=0.023).

Conclusions

Most of the measured laboratory markers changed from baseline, peaking at 2-3 days. The ALT level was the only parameter for which there was a significant difference after RFA between Child-Pugh A and B patients: it increased significantly more in the Child-Pugh A patients.

Citations

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    S. V. Vertyankin, O. M. Konopatskova
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Review

Hepatic neoplasm

The MR imaging diagnosis of liver diseases using gadoxetic acid: Emphasis on hepatobiliary phase
Woo Kyoung Jeong, Young Kon Kim, Kyoung Doo Song, Dongil Choi, Hyo Keun Lim
Clin Mol Hepatol 2013;19(4):360-366.
Published online December 28, 2013
DOI: https://doi.org/10.3350/cmh.2013.19.4.360

Hepatocyte specific contrast agents including gadoxetic acid and gadobenate dimeglumine are very useful to diagnose various benign and malignant focal hepatic lesions and even helpful to estimate hepatic functional reservoir. The far delayed phase image referred to as the hepatobiliary phase makes the sensitivity of detection for malignant focal hepatic lesions increased, but specificity of malignant diseases, including hepatocellular carcinoma, metastasis and cholangiocarcinoma, characterization remained to be undetermined.

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Liver Imagings

Hepatic neoplasm

Primary hepatic lymphoma mimicking acute hepatitis
Jeong-Ah Lee, Woo Kyoung Jeong, Ji Hye Min, Jinoo Kim
Clin Mol Hepatol 2013;19(3):320-323.
Published online September 30, 2013
DOI: https://doi.org/10.3350/cmh.2013.19.3.320

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Hepatic neoplasm

Pseudocirrhosis as a complication after chemotherapy for hepatic metastasis from breast cancer
Woo Kyoung Jeong, Seo-Youn Choi, Jinoo Kim
Clin Mol Hepatol 2013;19(2):190-194.
Published online June 27, 2013
DOI: https://doi.org/10.3350/cmh.2013.19.2.190

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