|
1
|
Wang C, Zhu SC, Liang JH. Value of Abbreviated Magnetic Resonance Sequence in Hepatocellular Carcinoma Screening: A Systematic Review and Meta-analysis. Acad Radiol 2025:S1076-6332(24)00993-0. [PMID: 39757062 DOI: 10.1016/j.acra.2024.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 12/08/2024] [Accepted: 12/11/2024] [Indexed: 01/07/2025]
Abstract
RATIONALE AND OBJECTIVES To systematically review the diagnostic efficacy of abbreviated magnetic resonance imaging sequence (AMRI) screening for hepatocellular carcinoma (HCC). MATERIALS AND METHODS Medline (via PubMed), EMbase, The Cochrane Library, Web of Science, CNKI, WanFang Data, and VIP databases were electronically searched to collect studies on the diagnostic efficacy of AMRI screening for HCC from inception to August 10th, 2024. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of included studies using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2), then, the meta-analysis with a bivariate mixed-effects regression model was performed by using Stata 14.0 software. RESULTS A total of 19 studies involving 3914 participants were included which published from 2013 to 2024. The results of meta-analysis showed that pooled sensitivity and specificity of AMRI for HCC were 0.85 (95% confidence interval (CI) 0.83 to 0.87) and 0.93 (95%CI 0.91 to 0.94). Subgroup analysis showed that the pooled sensitivity and specificity of NC (Non-Contrast) AMRI and HBP (Hepatobiliary Phase Images) AMRI were 0.84 (95%CI 0.80 to 0.87), 0.92 (95%CI 0.89 to 0.94) and 0.88 (95%CI 0.84 to 0.91), 0.93 (95%CI 0.91 to 0.95), respectively. And the T2 (T2 Weighted Imaging)+DWI (Diffusion Weighted Imaging)+HBP protocol in HBP AMRI had the highest diagnostic efficacy, its pooled sensitivity, specificity and the area under the summary receiver operating characteristic (SROC) curve (AUC) were 0.88 (95%CI 0.83 to 0.92), 0.93 (95%CI 0.91 to 0.95), and 0.96 (95%CI 0.94 to 0.98), respectively. CONCLUSION Current evidence suggests that the AMRI protocols demonstrated potential for HCC detection, which employing a limited number of sequences with the aim of achieving a diagnostic performance comparable to conventional complete contrast-enhanced MRI (CE-MRI). Among them, T2+DWI+HBP protocol shows the relatively highest diagnostic efficiency, which is perhaps the most promising application in clinical practice. Nevertheless, the results still should be carefully interpreted in the relevant context of medical history, physical examination, and biochemical indicators.
Collapse
Affiliation(s)
- Cong Wang
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, PR China (C.W., S.C.Z.).
| | - Shao-Cheng Zhu
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, PR China (C.W., S.C.Z.)
| | - Jing-Hong Liang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, PR China (J.H.L.); Department of Social medicine, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123, PR China (J.H.L.); Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, Jiangsu 215123, PR China (J.H.L.)
| |
Collapse
|
|
2
|
Maung ST, Tanpowpong N, Satja M, Treeprasertsuk S, Chaiteerakij R. MRI for hepatocellular carcinoma and the role of abbreviated MRI for surveillance of hepatocellular carcinoma. J Gastroenterol Hepatol 2024; 39:1969-1981. [PMID: 38899804 DOI: 10.1111/jgh.16643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/16/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024]
Abstract
INTRODUCTION Hepatocellular carcinoma (HCC) constitutes the majority of liver cancers and significantly impacts global cancer mortality. While ultrasound (US) with or without alpha-fetoprotein is the mainstay for HCC surveillance, its limitations highlight the necessity for more effective surveillance tools. Therefore, this review explores evolving imaging modalities and abbreviated magnetic resonance imaging (MRI) (AMRI) protocols as promising alternatives, addressing challenges in HCC surveillance. AREAS COVERED This comprehensive review delves into the evaluation and challenges of HCC surveillance tools, focusing on non-contrast abbreviated MRI (NC-AMRI) and contrast-enhanced abbreviated MRI protocols. It covers the implementation of AMRI for HCC surveillance, patient preferences, adherence, and strategies for optimizing cost-effectiveness. Additionally, the article provides insights into prospects for HCC surveillance by summarizing meta-analyses, prospective studies, and ongoing clinical trials evaluating AMRI protocols. EXPERT OPINION The opinions underscore the transformative impact of AMRI on HCC surveillance, especially in overcoming US limitations. Promising results from NC-AMRI protocols indicate its potential for high-risk patient surveillance, though prospective studies in true surveillance settings are essential for validation. Future research should prioritize risk-stratified AMRI protocols and address cost-effectiveness for broader clinical implementation, alongside comparative analyses with US for optimal surveillance strategies.
Collapse
Affiliation(s)
- Soe Thiha Maung
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Ma Har Myaing Hospital, Yangon, Myanmar
| | - Natthaporn Tanpowpong
- Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Minchanat Satja
- Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Sombat Treeprasertsuk
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Roongruedee Chaiteerakij
- Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence for Innovation and Endoscopy in Gastrointestinal Oncology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| |
Collapse
|
|
3
|
Guo P, Wang P, Zhou J, Jiang S, Patel VM. Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning. PROCEEDINGS. IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION 2021; 2021:2423-2432. [PMID: 35444379 DOI: 10.1109/cvpr46437.2021.00245] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Fast and accurate reconstruction of magnetic resonance (MR) images from under-sampled data is important in many clinical applications. In recent years, deep learning-based methods have been shown to produce superior performance on MR image reconstruction. However, these methods require large amounts of data which is difficult to collect and share due to the high cost of acquisition and medical data privacy regulations. In order to overcome this challenge, we propose a federated learning (FL) based solution in which we take advantage of the MR data available at different institutions while preserving patients' privacy. However, the generalizability of models trained with the FL setting can still be suboptimal due to domain shift, which results from the data collected at multiple institutions with different sensors, disease types, and acquisition protocols, etc. With the motivation of circumventing this challenge, we propose a cross-site modeling for MR image reconstruction in which the learned intermediate latent features among different source sites are aligned with the distribution of the latent features at the target site. Extensive experiments are conducted to provide various insights about FL for MR image reconstruction. Experimental results demonstrate that the proposed framework is a promising direction to utilize multi-institutional data without compromising patients' privacy for achieving improved MR image reconstruction. Our code is available at https://github.com/guopengf/FL-MRCM.
Collapse
|
|
4
|
Time to peak enhancement of malignant hypervascular hepatic tumors versus that of the aorta evaluating by test bolus sequence of magnetic resonance imaging. Eur J Radiol 2020; 131:109211. [DOI: 10.1016/j.ejrad.2020.109211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 07/12/2020] [Accepted: 08/05/2020] [Indexed: 11/21/2022]
|
|
5
|
Understanding fundamentals of hepatocellular carcinoma to design next-generation chitosan nano-formulations: Beyond chemotherapy stride. J Drug Deliv Sci Technol 2020. [DOI: 10.1016/j.jddst.2020.101723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
|
6
|
New Arterial Phase Enhancing Nodules on MRI of Cirrhotic Liver: Risk of Progression to Hepatocellular Carcinoma and Implications for LI-RADS Classification. AJR Am J Roentgenol 2020; 215:382-389. [PMID: 32432909 DOI: 10.2214/ajr.19.22033] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE. The purposes of this study were to evaluate the outcome of new arterial phase enhancing nodules at MRI of cirrhotic livers, including clinical and imaging factors that affect progression to hepatocellular carcinoma (HCC), and to assess the diagnostic performance of Liver Imaging Reporting and Data System version 2018 (LI-RADSv2018) versus version 2017 (LI-RADSv2017) in categorizing these nodules. MATERIALS AND METHODS. A database search identified 129 new arterial phase enhancing, round, solid, space-occupying nodules in 79 patients with cirrhosis who underwent surveillance MRI. Three readers assessed the nodules for LI-RADS findings and made assessments based on the 2017 and 2018 criteria. Clinical information and laboratory values were collected. Outcome data were assessed on the basis of follow-up imaging and pathology results. Interreader agreement was assessed. Logistic regression and ROC curve analyses were used to assess the utility of the features for prediction of progression to HCC. RESULTS. Of the 129 nodules, 71 (55%) progressed to HCC. LI-RADSv2017 score, LIRADSv2018 score, and mild-to-moderate T2 hyperintensity were significant independent predictors of progression to HCC in univariate analyses. Serum α-fetoprotein level, hepatitis B or C virus infection as the cause of liver disease, and presence of other HCCs were significant predictors of progression to HCC in multivariate analyses. The rates of progression of LI-RADS category 3 and 4 observations were 38.1% and 57.6%, respectively, for LI-RADSv2017 and 44.4% and 69.9%, respectively, for LI-RADSv2018. CONCLUSION. New arterial phase enhancing nodules in patients with cirrhosis frequently progress to HCC. Factors such as serum α-fetoprotein level and presence of other HCCs are strong predictors of progression to HCC.
Collapse
|
|
7
|
Al-Sharhan F, Dohan A, Barat M, Feddal A, Terris B, Pol S, Mallet V, Soyer P. MRI presentation of hepatocellular carcinoma in non-alcoholic steatohepatitis (NASH). Eur J Radiol 2019; 119:108648. [DOI: 10.1016/j.ejrad.2019.108648] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 08/11/2019] [Accepted: 08/27/2019] [Indexed: 12/12/2022]
|
|
8
|
Chou YC, Lao IH, Hsieh PL, Su YY, Mak CW, Sun DP, Sheu MJ, Kuo HT, Chen TJ, Ho CH, Kuo YT. Gadoxetic acid-enhanced magnetic resonance imaging can predict the pathologic stage of solitary hepatocellular carcinoma. World J Gastroenterol 2019; 25:2636-2649. [PMID: 31210715 PMCID: PMC6558433 DOI: 10.3748/wjg.v25.i21.2636] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/30/2019] [Accepted: 05/08/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Although important for determining long-term outcome, pathologic stage of hepatocellular carcinoma (HCC) is difficult to predict before surgery. Current state-of-the-art magnetic resonance imaging (MRI) using gadoxetic acid provides many imaging features that could potentially be used to classify single HCC as pT1 or pT2.
AIM To determine which gadoxetic acid-enhanced MRI (EOB-MRI) findings predict pathologic stage T2 in patients with solitary HCC (cT1).
METHODS Pre-operative EOB-MRI findings were reviewed in a retrospective cohort of patients with solitary HCC. The following imaging features were examined: Hyperintensity in unenhanced T2-weighted images, hypointensity in unenhanced T1-weighted images, arterial enhancement, corona enhancement, washout appearance, capsular appearance, hypointensity in the tumor tissue during the hepatobiliary (HB) phase, peritumoral hypointensity in the HB phase, hypointense rim in the HB phase, intratumoral fat, hyperintensity on diffusion-weighted imaging, hypointensity on apparent diffusion coefficient map, mosaic appearance, nodule-in-nodule appearance, and the margin (smooth or irregular). Surgical pathology was used as the reference method for tumor staging. Univariate and multivariate analyses were performed to identify predictors of microvascular invasion or satellite nodules.
RESULTS There were 39 (34.2%; 39 of 114) and 75 (65.8%; 75 of 114) pathological stage T2 and T1 HCCs, respectively. Large tumor size (≥ 2.3 cm) and two MRI findings, i.e., corona enhancement [odds ratio = 2.67; 95% confidence interval: 1.101-6.480] and peritumoral hypointensity in HB phase images (odds ratio = 2.203; 95% confidence interval: 0.961-5.049) were associated with high risk of pT2 HCC. The positive likelihood ratio was 6.25 (95% confidence interval: 1.788-21.845), and sensitivity of EOB-MRI for detecting pT2 HCC was 86.2% when two or three of these MRI features were present. Small tumor size and hypointense rim in the HB phase were regarded as benign features. Small HCCs with hypointense rim but not associated with aggressive features were mostly pT1 lesions (specificity, 100%).
CONCLUSION Imaging features on EOB-MRI could potentially be used to predict the pathologic stage of solitary HCC (cT1) as pT1 or pT2.
Collapse
Affiliation(s)
- Yi-Chen Chou
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - I-Ha Lao
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
- Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 804, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Pei-Ling Hsieh
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Ying-Ying Su
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Chee-Wai Mak
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Ding-Ping Sun
- Department of Surgery, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Food Science and Technology, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Ming-Jen Sheu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Medicinal Chemistry, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Hsing-Tao Kuo
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Senior Citizen Service Management, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Tzu-Ju Chen
- Department of Pathology, Chi-Mei Medical Center, Tainan 710, Taiwan
- Department of Optometry, Chung Hwa University of Medical Technology, Tainan 717, Taiwan
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 804, Taiwan
| | - Chung-Han Ho
- Department of Medical Research, Chi-Mei Medical Center, Tainan 710, Taiwan
- Department of Hospital and Health Care Administration, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Yu-Ting Kuo
- Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan
- Department of Radiology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| |
Collapse
|
|
9
|
Lu J, Wang J, Ling D. Surface Engineering of Nanoparticles for Targeted Delivery to Hepatocellular Carcinoma. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2018; 14:1702037. [PMID: 29251419 DOI: 10.1002/smll.201702037] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 10/24/2017] [Indexed: 05/20/2023]
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-associated deaths worldwide. There is a lack of efficient therapy for HCC; the only available first-line systemic drug, sorafenib, can merely improve the average survival by two months. Among the efforts to develop an efficient therapy for HCC, nanomedicine has drawn the most attention, owing to its unique features such as high drug-loading capacity, intrinsic anticancer activities, integrated diagnostic and therapeutic functionalities, and easy surface engineering with targeting ligands. Despite its tremendous advantages, no nanomedicine can be effective unless it successfully targets the tumor site, which is a challenging task. In this review, the features of HCC are described, and the physiological hurdles that prevent nanoparticles from targeting HCC are discussed. Then, the surface physicochemical factors of nanoparticles that can influence targeting efficiency are discussed. Finally, a thorough description of the physiological barriers that nanomedicine must conquer before uptake by HCC cells if possible is provided, as well as the surface engineering approaches to nanomedicine to achieve targeted delivery to HCC cells. The physiological hurdles and corresponding solutions summarized in this review provide a general guide for the rational design of HCC targeting nanomedicine systems.
Collapse
Affiliation(s)
- Jingxiong Lu
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, and Key Laboratory of Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310058, China
| | - Jin Wang
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, and Key Laboratory of Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310058, China
| | - Daishun Ling
- Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, and Key Laboratory of Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310058, China
| |
Collapse
|
|
10
|
Kambadakone AR, Fung A, Gupta RT, Hope TA, Fowler KJ, Lyshchik A, Ganesan K, Yaghmai V, Guimaraes AR, Sahani DV, Miller FH. LI-RADS technical requirements for CT, MRI, and contrast-enhanced ultrasound. Abdom Radiol (NY) 2018; 43:56-74. [PMID: 28940042 DOI: 10.1007/s00261-017-1325-y] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Accurate detection and characterization of liver observations to enable HCC diagnosis and staging using LI-RADS requires a technically adequate imaging exam. To help achieve this objective, LI-RADS has proposed technical requirements for CT, MR, and contrast-enhanced ultrasound of liver. This article reviews the technical requirements for liver imaging, including the description of minimum acceptable technical standards, such as the scanner hardware requirements, recommended dynamic imaging phases, and common technical challenges of liver imaging.
Collapse
Affiliation(s)
- Avinash R Kambadakone
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA.
| | - Alice Fung
- Department of Diagnostic Radiology, Oregon Health and Science University, Portland, OR, USA
| | - Rajan T Gupta
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Thomas A Hope
- Department of Radiology, University of California San Francisco, San Francisco, CA, USA
| | - Kathryn J Fowler
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrej Lyshchik
- Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, PA, USA
| | - Karthik Ganesan
- Department of Radiology, Sir HN Reliance Foundation Hospital and Research Centre, Mumbai, India
| | - Vahid Yaghmai
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Alexander R Guimaraes
- Department of Diagnostic Radiology, Oregon Health and Science University, Portland, OR, USA
| | - Dushyant V Sahani
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Frank H Miller
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| |
Collapse
|
|
11
|
Chernyak V, Tang A, Flusberg M, Papadatos D, Bijan B, Kono Y, Santillan C. LI-RADS ® ancillary features on CT and MRI. Abdom Radiol (NY) 2018. [PMID: 28647768 DOI: 10.1007/s00261-017-1220-6] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The Liver Imaging Reporting and Data System (LI-RADS) uses an algorithm to assign categories that reflect the probability of hepatocellular carcinoma (HCC), non-HCC malignancy, or benignity. Unlike other imaging algorithms, LI-RADS utilizes ancillary features (AFs) to refine the final category. AFs in LI-RADS v2017 are divided into those favoring malignancy in general, those favoring HCC specifically, and those favoring benignity. Additionally, LI-RADS v2017 provides new rules regarding application of AFs. The purpose of this review is to discuss ancillary features included in LI-RADS v2017, the rationale for their use, potential pitfalls encountered in their interpretation, and tips on their application.
Collapse
Affiliation(s)
| | - An Tang
- Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, QC, Canada
| | | | - Demetri Papadatos
- Department of Diagnostic Imaging, The Ottawa Hospital, Ottawa, ON, Canada
| | - Bijan Bijan
- Sutter Imaging (SMG)/University of California Davis (UCD), Sacramento, CA, USA
| | - Yuko Kono
- Department of Medicine, Gastroenterology and Hepatology, University of California, San Diego, CA, USA
| | - Cynthia Santillan
- Liver Imaging Group, Department of Radiology, University of California, San Diego, CA, USA
| |
Collapse
|
|
12
|
Santillan C, Fowler K, Kono Y, Chernyak V. LI-RADS major features: CT, MRI with extracellular agents, and MRI with hepatobiliary agents. Abdom Radiol (NY) 2018; 43:75-81. [PMID: 28828680 DOI: 10.1007/s00261-017-1291-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The Liver Imaging Reporting and Data System (LI-RADS) was designed to standardize the interpretation and reporting of observations seen on studies performed in patients at risk for development of hepatocellular carcinoma (HCC). The LI-RADS algorithm guides radiologists through the process of categorizing observations on a spectrum from definitely benign to definitely HCC. Major features are the imaging features used to categorize observations as LI-RADS 3 (intermediate probability of malignancy), LIRADS 4 (probably HCC), and LI-RADS 5 (definite HCC). Major features include arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, size, and threshold growth. Observations that have few major criteria are assigned lower categories than those that have several, with the goal of preserving high specificity for the LR-5 category of Definite HCC. The goal of this paper is to discuss LI-RADS major features, including definitions, rationale for selection as major features, and imaging examples.
Collapse
|
|
13
|
Fowler KJ, Tang A, Santillan C, Bhargavan-Chatfield M, Heiken J, Jha RC, Weinreb J, Hussain H, Mitchell DG, Bashir MR, Costa EAC, Cunha GM, Coombs L, Wolfson T, Gamst AC, Brancatelli G, Yeh B, Sirlin CB. Interreader Reliability of LI-RADS Version 2014 Algorithm and Imaging Features for Diagnosis of Hepatocellular Carcinoma: A Large International Multireader Study. Radiology 2017; 286:173-185. [PMID: 29091751 DOI: 10.1148/radiol.2017170376] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Purpose To determine in a large multicenter multireader setting the interreader reliability of Liver Imaging Reporting and Data System (LI-RADS) version 2014 categories, the major imaging features seen with computed tomography (CT) and magnetic resonance (MR) imaging, and the potential effect of reader demographics on agreement with a preselected nonconsecutive image set. Materials and Methods Institutional review board approval was obtained, and patient consent was waived for this retrospective study. Ten image sets, comprising 38-40 unique studies (equal number of CT and MR imaging studies, uniformly distributed LI-RADS categories), were randomly allocated to readers. Images were acquired in unenhanced and standard contrast material-enhanced phases, with observation diameter and growth data provided. Readers completed a demographic survey, assigned LI-RADS version 2014 categories, and assessed major features. Intraclass correlation coefficient (ICC) assessed with mixed-model regression analyses was the metric for interreader reliability of assigning categories and major features. Results A total of 113 readers evaluated 380 image sets. ICC of final LI-RADS category assignment was 0.67 (95% confidence interval [CI]: 0.61, 0.71) for CT and 0.73 (95% CI: 0.68, 0.77) for MR imaging. ICC was 0.87 (95% CI: 0.84, 0.90) for arterial phase hyperenhancement, 0.85 (95% CI: 0.81, 0.88) for washout appearance, and 0.84 (95% CI: 0.80, 0.87) for capsule appearance. ICC was not significantly affected by liver expertise, LI-RADS familiarity, or years of postresidency practice (ICC range, 0.69-0.70; ICC difference, 0.003-0.01 [95% CI: -0.003 to -0.01, 0.004-0.02]. ICC was borderline higher for private practice readers than for academic readers (ICC difference, 0.009; 95% CI: 0.000, 0.021). Conclusion ICC is good for final LI-RADS categorization and high for major feature characterization, with minimal reader demographic effect. Of note, our results using selected image sets from nonconsecutive examinations are not necessarily comparable with those of prior studies that used consecutive examination series. © RSNA, 2017.
Collapse
Affiliation(s)
- Kathryn J Fowler
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - An Tang
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Cynthia Santillan
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Mythreyi Bhargavan-Chatfield
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Jay Heiken
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Reena C Jha
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Jeffrey Weinreb
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Hero Hussain
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Donald G Mitchell
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Mustafa R Bashir
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Eduardo A C Costa
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Guilherme M Cunha
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Laura Coombs
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Tanya Wolfson
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Anthony C Gamst
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Giuseppe Brancatelli
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Benjamin Yeh
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Claude B Sirlin
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| |
Collapse
|
|
14
|
Alexander LF, Harri P, Little B, Moreno CC, Mittal PK. Magnetic Resonance Imaging of Primary Hepatic Malignancies in Patients With and Without Chronic Liver Disease: A Pictorial Review. Cureus 2017; 9:e1539. [PMID: 28989828 PMCID: PMC5628780 DOI: 10.7759/cureus.1539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Primary hepatic malignancies are less common than metastatic diseases, but a recognition of these lesions is important for diagnosis and treatment planning. Magnetic resonance imaging (MRI) provides the most imaging information to diagnose lesions noninvasively and to narrow differential diagnoses. This paper reviews the imaging findings of chronic liver disease and primary hepatic malignancies, including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (CCA), epithelioid hemangioendothelioma, hepatic angiosarcoma, and primary hepatic lymphoma. Clinical and MRI features are reviewed to improve the readers’ recognition of these tumors, allowing for a narrower differential diagnosis when liver masses are encountered on abdominal imaging.
Collapse
Affiliation(s)
- Lauren F Alexander
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
| | - Peter Harri
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
| | - Brent Little
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
| | - Courtney C Moreno
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
| | - Pardeep K Mittal
- Department of Radiology and Imaging Sciences, Emory University School of Medicine
| |
Collapse
|
|
15
|
Critical analysis of the major and ancillary imaging features of LI-RADS on 127 proven HCCs evaluated with functional and morphological MRI: Lights and shadows. Oncotarget 2017; 8:51224-51237. [PMID: 28881643 PMCID: PMC5584244 DOI: 10.18632/oncotarget.17227] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 03/22/2017] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To report a critical analysis of major and ancillary MR imaging features in assessment of HCC. METHODS Retrospectively we evaluated 70 cirrhotic patients with 173 nodules, which were subjected to MR study at 0 time (MR0), after 3 (MR3) and 6 months (MR6) using two different contrast media. EOB-GD-DTPA was injected at MR0 and MR6, while Gd-BT-DO3A at MR3. Three expert hepatic radiologists reviewed all images, recording, according to LI-RADS, the size, the presence and quality of arterial-phase hyperenhancement, washout and capsule appearance, threshold growth. Additionally, we recorded signal intensity (SI) on T2-W images, on DWI, on apparent diffusion coefficient (ADC) maps and SI on T1-W images of EOB-GD-BPTA hepatospecific phase. Median value of ADC and of Intravoxel incoherent motion related parameters were assessed. RESULTS 127 HCCs and 24 dysplastic nodules were assessed. Hypervascular on arterial phase was found in 84 HCCs, washout appearance in 124, capsule appearance in 111, hypointensity on hepatospecific phase in 127, hyperintensity on T2-W sequences and restricted diffusion in 107. Hyper vascular on arterial phase was found in 17 dysplastic nodules, wash-out appearance in 2, hypointensity on hepatospecific phase in 7 while no dysplastic nodules showed capsule appearance, hyperintensity on T2-W and restricted diffusion. Highest accuracy was obtained by washout appearance and hypointense signal on hepatospecific phase (97% and 95%). CONCLUSIONS Hypointensity on hepatospecific phase and washout appearance are the most relevant diagnostic sign for differentiating low-risk from high-risk HCC nodules. The capsule appearance, T2-W hyperintensity and restricted diffusion have high positive predictive value.
Collapse
|
|
16
|
Ramalho M, Matos AP, AlObaidy M, Velloni F, Altun E, Semelka RC. Magnetic resonance imaging of the cirrhotic liver: diagnosis of hepatocellular carcinoma and evaluation of response to treatment - Part 1. Radiol Bras 2017; 50:38-47. [PMID: 28298731 PMCID: PMC5347502 DOI: 10.1590/0100-3984.2015.0132] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Magnetic resonance imaging (MRI) is the modern gold standard for the noninvasive evaluation of the cirrhotic liver. The combination of arterial phase hyperenhancement and delayed wash-out allows a definitive diagnosis of hepatocellular carcinoma (HCC) in patients with liver cirrhosis or chronic liver disease, without the requirement for confirmatory biopsy. That pattern is highly specific and has been endorsed in Western and Asian diagnostic guidelines. However, the sensitivity of the combination is relatively low for small HCCs. In this two-part review paper, we will address MRI of the cirrhotic liver. In this first part, we provide a brief background on liver cirrhosis and HCC, followed by descriptions of imaging surveillance of liver cirrhosis and the diagnostic performance of the different imaging modalities used in clinical settings. We then describe some of the requirements for the basic MRI technique, as well as the standard MRI protocol, and provide a detailed description of the appearance of various types of hepatocellular nodules encountered in the setting of the carcinogenic pathway in the cirrhotic liver, ranging from regenerative nodules to HCC.
Collapse
Affiliation(s)
- Miguel Ramalho
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, and Hospital Garcia de Orta, Almada, Portugal
| | - António P Matos
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, and Hospital Garcia de Orta, Almada, Portugal
| | - Mamdoh AlObaidy
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, and King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Fernanda Velloni
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ersan Altun
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Richard C Semelka
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|
|
17
|
Shankar S, Kalra N, Bhatia A, Srinivasan R, Singh P, Dhiman RK, Khandelwal N, Chawla Y. Role of Diffusion Weighted Imaging (DWI) for Hepatocellular Carcinoma (HCC) Detection and its Grading on 3T MRI: A Prospective Study. J Clin Exp Hepatol 2016; 6:303-310. [PMID: 28003720 PMCID: PMC5157886 DOI: 10.1016/j.jceh.2016.08.012] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2016] [Accepted: 08/25/2016] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Limited studies have evaluated the role of diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) for histologically grading the hepatocellular carcinoma (HCC). OBJECTIVE To compare the efficacy of DWI with dynamic contrast enhanced magnetic resonance (DCEMR) in detection of HCC in cirrhosis, and to evaluate whether DWI can be used instead of DCEMR. METHODS 20 patients of either sex with cirrhosis and suspected of having HCC on screening USG were included in this prospective study approved by the Institutional Ethics Committee. All patients underwent DCEMR of the abdomen on 3T scanner and fine needle aspiration of the lesions. MR protocol included T1WI, T2WI, DWI, and dynamic CEMR. The results of diffusion weighted imaging were compared with DCEMR to find the efficacy of DWI vis-à-vis CEMR. RESULTS DWI had a sensitivity and specificity of 100%, for diagnosis of lesions in cases having single lesion on CEMR, and sensitivity of 75% and specificity of 100% for diagnosis of lesions in cases having multiple lesions. There was a decreasing trend of ADC values with increasing grade of the tumor; however, the decreasing trend was not statistically significant. A cut-off ADC value of 0.8705 resulted in a sensitivity of 75% and specificity of 50% for differentiating between well-differentiated and other grades of HCC. CONCLUSION DWI can be used as an alternative for the detection and characterization of HCC, especially in patients with impaired renal function or contrast allergies precluding the use of contrast. In addition, DWI with ADC measurement may be helpful for non-invasive and preoperative prediction of the degree of differentiation of HCC.
Collapse
Affiliation(s)
- Shiva Shankar
- Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| | - Naveen Kalra
- Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
- Address for correspondence: Dr. Naveen Kalra, Professor, Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India. Fax: +91 172 2744401.Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and ResearchSector-12Chandigarh160012India
| | - Anmol Bhatia
- Department of Gastroenterology, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| | - Radhika Srinivasan
- Department of Cytology and Gynaecological Pathology, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| | - Paramjeet Singh
- Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| | - Radha K. Dhiman
- Department of Hepatology, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| | - Niranjan Khandelwal
- Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| | - Yogesh Chawla
- Department of Hepatology, Post Graduate Institute of Medical Education and Research, Sector-12, Chandigarh 160012, India
| |
Collapse
|
|
18
|
Hoogenboom TC, Thursz M, Aboagye EO, Sharma R. Functional imaging of hepatocellular carcinoma. Hepat Oncol 2016; 3:137-153. [PMID: 30191034 DOI: 10.2217/hep-2015-0005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Accepted: 01/20/2016] [Indexed: 02/06/2023] Open
Abstract
Imaging plays a key role in the clinical management of hepatocellular carcinoma (HCC), but conventional imaging techniques have limited sensitivity in visualizing small tumors and assessing response to locoregional treatments and sorafenib. Functional imaging techniques allow visualization of organ and tumor physiology. Assessment of functional characteristics of tissue, such as metabolism, proliferation and stiffness, may overcome some of the limitations of structural imaging. In particular, novel molecular imaging agents offer a potential tool for early diagnosis of HCC, and radiomics may aid in response assessment and generate prognostic models. Further prospective research is warranted to evaluate emerging techniques and their cost-effectiveness in the context of HCC in order to improve detection and response assessment.
Collapse
Affiliation(s)
- Tim Ch Hoogenboom
- Department of Experimental Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK.,Department of Experimental Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK
| | - Mark Thursz
- Department of Hepatology, Imperial College NHS Trust, 10th Floor, Norfolk Place, St Mary's Hospital, London, UK.,Department of Hepatology, Imperial College NHS Trust, 10th Floor, Norfolk Place, St Mary's Hospital, London, UK
| | - Eric O Aboagye
- Comprehensive Cancer Imaging Centre at Imperial College, Faculty of Medicine, Imperial College London, GN1, Ground Floor, Commonwealth building, Hammersmith Campus, London, UK.,Comprehensive Cancer Imaging Centre at Imperial College, Faculty of Medicine, Imperial College London, GN1, Ground Floor, Commonwealth building, Hammersmith Campus, London, UK
| | - Rohini Sharma
- Department of Experimental Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK.,Department of Experimental Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK
| |
Collapse
|
|
19
|
Kim R, Lee JM, Joo I, Lee DH, Woo S, Han JK, Choi BI. Differentiation of lipid poor angiomyolipoma from hepatocellular carcinoma on gadoxetic acid-enhanced liver MR imaging. ACTA ACUST UNITED AC 2015; 40:531-41. [PMID: 25231411 DOI: 10.1007/s00261-014-0244-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
PURPOSE To investigate magnetic resonance (MR) findings of angiomyolipoma (AML) on gadoxetic acid-enhanced MR imaging, and to identify features that differentiate AML from hepatocellular carcinoma (HCC) in patients with a low risk of HCC development. METHODS This retrospective study was institutional review board approved, and the requirement for informed consent was waived. Twelve patients with hepatic AML who underwent gadoxetic acid-enhanced MRI with no risk factors for HCC development were recruited. Twenty-seven patients with HCC under the same inclusion criteria were recruited as control. Two radiologists analyzed the images in consensus for morphologic features, enhancement patterns, and hepatobiliary phase (HBP) findings. All results were analyzed using the Mann-Whitney test, two-tailed Fisher exact test, and chi-square test. RESULTS Patients with AML were younger than those with HCC (48.8 ± 15 years for AML vs. 62.7 ± 14.2 years for HCC, p = 0.008) with female predominance, while most HCC patients were male (75% (9/12) vs. 15% (4/27), p < 0.001). The most prevalent enhancement pattern was arterial enhancement followed by hypointensity at portal or transitional phases for both AMLs (58% (7/12)) and HCCs (74% (20/27)) (p = 0.455). However, during the HBP, AMLs frequently showed more homogeneous hypointensity than HCCs (83% (10/12) vs. 41% (11/27), p = 0.018). When compared with the signal intensity of the spleen, the mean relative signal intensity of the AML was 91.2 ± 15.4%, while in HCCs, it was 128.7 ± 40% (p < 0.001). CONCLUSIONS Although AMLs showed similar enhancement patterns to HCCs during the dynamic phases of gadoxetic acid-enhanced MRI, using characteristic MR features of AML during the HBP and demographic differences, one can better differentiate AML from HCC.
Collapse
Affiliation(s)
- Rihyeon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-Gu, Seoul, 110-744, Korea
| | | | | | | | | | | | | |
Collapse
|
|
20
|
|
|
21
|
Arif-Tiwari H, Kalb B, Chundru S, Sharma P, Costello J, Guessner RW, Martin DR. MRI of hepatocellular carcinoma: an update of current practices. Diagn Interv Radiol 2015; 20:209-21. [PMID: 24808419 DOI: 10.5152/dir.2014.13370] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and liver transplantation is the optimal treatment for selected patients with HCC and chronic liver disease (CLD). Accurate selection of patients for transplantation is essential to maximize patient outcomes and ensure optimized allocation of donor organs. Magnetic resonance imaging (MRI) is a powerful tool for the detection, characterization, and staging of HCC. In patients with CLD, the MRI findings of an arterial-enhancing mass with subsequent washout and enhancing capsule on delayed interstitial phase images are diagnostic for HCC. Major organizations with oversight for organ donor distribution, such as The Organ Procurement and Transplantation Network (OPTN), accept an imaging diagnosis of HCC, no longer requiring tissue biopsy. In patients that are awaiting transplantation, or are not candidates for liver transplantation, localized therapies such as transarterial chemoembolization and radiofrequency ablation may be offered. MRI can be used to monitor treatment response. The purpose of this review article is to describe the role of imaging methods in the diagnosis, staging, and follow-up of HCC, with particular emphasis on established and evolving MRI techniques employing nonspecific gadolinium chelates, hepatobiliary contrast agents, and diffusion weighted imaging. We also briefly review the recently developed Liver Imaging Reporting and Data System (LI-RADS) formulating a standardized terminology and reporting structure for evaluation of lesions detected in patients with CLD.
Collapse
Affiliation(s)
- Hina Arif-Tiwari
- From the Departments of Medical Imaging University of Arizona College of Medicine, Tucson, Arizona, USA.
| | | | | | | | | | | | | |
Collapse
|
|
22
|
Cho ES, Choi JY. MRI features of hepatocellular carcinoma related to biologic behavior. Korean J Radiol 2015; 16:449-64. [PMID: 25995679 PMCID: PMC4435980 DOI: 10.3348/kjr.2015.16.3.449] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2014] [Accepted: 02/23/2015] [Indexed: 12/12/2022] Open
Abstract
Imaging studies including magnetic resonance imaging (MRI) play a crucial role in the diagnosis and staging of hepatocellular carcinoma (HCC). Several recent studies reveal a large number of MRI features related to the prognosis of HCC. In this review, we discuss various MRI features of HCC and their implications for the diagnosis and prognosis as imaging biomarkers. As a whole, the favorable MRI findings of HCC are small size, encapsulation, intralesional fat, high apparent diffusion coefficient (ADC) value, and smooth margins or hyperintensity on the hepatobiliary phase of gadoxetic acid-enhanced MRI. Unfavorable findings include large size, multifocality, low ADC value, non-smooth margins or hypointensity on hepatobiliary phase images. MRI findings are potential imaging biomarkers in patients with HCC.
Collapse
Affiliation(s)
- Eun-Suk Cho
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 135-720, Korea
| | - Jin-Young Choi
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul 120-752, Korea
| |
Collapse
|
|
23
|
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; 7:468-487. [PMID: 25848471 PMCID: PMC4381170 DOI: 10.4254/wjh.v7.i3.468] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2014] [Revised: 10/10/2014] [Accepted: 12/10/2014] [Indexed: 02/06/2023] Open
Abstract
Noninvasive imaging has become the standard for hepatocellular carcinoma (HCC) diagnosis in cirrhotic livers. In this review paper, we go over the basics of MR imaging in cirrhotic livers and describe the imaging appearance of a spectrum of hepatic nodules marking the progression from regenerative nodules to low- and high-grade dysplastic nodules, and ultimately to HCCs. We detail and illustrate the typical imaging appearances of different types of HCC including focal, multi-focal, massive, diffuse/infiltrative, and intra-hepatic metastases; with emphasis on the diagnostic value of MR in imaging these lesions. We also shed some light on liver imaging reporting and data system, and the role of different magnetic resonance imaging (MRI) contrast agents and future MRI techniques including the use of advanced MR pulse sequences and utilization of hepatocyte-specific MRI contrast agents, and how they might contribute to improving the diagnostic performance of MRI in early stage HCC diagnosis.
Collapse
|
|
24
|
Hwang J, Kim YK, Jeong WK, Choi D, Rhim H, Lee WJ. Nonhypervascular Hypointense Nodules at Gadoxetic Acid-enhanced MR Imaging in Chronic Liver Disease: Diffusion-weighted Imaging for Characterization. Radiology 2015; 276:137-46. [PMID: 25734551 DOI: 10.1148/radiol.15141350] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
PURPOSE To compare the diagnostic performance of magnetic resonance (MR) imaging features, including those on diffusion-weighted (DW) and T2-weighted images, in differentiating between hypovascular hepatocellular carcinoma (HCC) and dysplastic nodules seen as hypointense nodules at hepatobiliary phase gadoxetic acid-enhanced MR imaging. MATERIALS AND METHODS The institutional review board approved this retrospective study and waived the need to obtain informed patient consent. There were 53 patients (39 men and 14 women; age range, 32-75 years) with histologically proven hypovascular HCCs (n = 25) and/or dysplastic nodules (n = 31) who underwent gadoxetic acid-enhanced MR imaging at 3.0-T between March 2011 and January 2014. Images of 25 HCCs and 31 dysplastic nodules were analyzed for nodule size; signal intensity on T1- and T2-weighted, portal venous phase, and DW (b value = 800 sec/mm(2)) images; and intralesional fat. Correlations between the hyperintensity grade of lesions and the liver-to-lesion signal intensity ratio at T2-weighted and DW imaging were determined by means of analysis with generalized estimating equations. RESULTS Hyperintensity at T2-weighted and DW imaging and hypointensity in the portal venous phase were significant features for differentiating hypovascular HCCs from dysplastic nodules (P < .05). The sensitivity of DW imaging tended to be higher than that of T2-weighted imaging (72.0% [18 of 25] vs 40.0% [10 of 25]; P = .008 for grade 2 and 3 hyperintensity). Use of the parameter of hyperintensity similar to or slightly lower than the signal intensity of the spleen on DW images (b value = 800 sec/mm(2)) yielded a specificity of 100% (31 of 31) for the diagnosis of hypovascular HCC by differentiating it from a dysplastic nodule. CONCLUSION Hyperintensity at DW imaging could be a useful MR imaging feature for differentiating hypovascular HCCs from dysplastic nodules seen as hypointense nodules at gadoxetic acid-enhanced MR imaging.
Collapse
Affiliation(s)
- Jiyoung Hwang
- From the Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea (J.H.); and Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea (Y.K.K., W.K.J., D.C., H.R., W.J.L.)
| | - Young Kon Kim
- From the Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea (J.H.); and Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea (Y.K.K., W.K.J., D.C., H.R., W.J.L.)
| | - Woo Kyoung Jeong
- From the Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea (J.H.); and Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea (Y.K.K., W.K.J., D.C., H.R., W.J.L.)
| | - Dongil Choi
- From the Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea (J.H.); and Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea (Y.K.K., W.K.J., D.C., H.R., W.J.L.)
| | - Hyunchul Rhim
- From the Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea (J.H.); and Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea (Y.K.K., W.K.J., D.C., H.R., W.J.L.)
| | - Won Jae Lee
- From the Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea (J.H.); and Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea (Y.K.K., W.K.J., D.C., H.R., W.J.L.)
| |
Collapse
|
|
25
|
Lamba R, Fananazapir G, Corwin MT, Khatri VP. Diagnostic Imaging of Hepatic Lesions in Adults. Surg Oncol Clin N Am 2014; 23:789-820. [DOI: 10.1016/j.soc.2014.07.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
|
|
26
|
Abstract
Cirrhosis is the main risk factor for the development of hepatocellular carcinoma (HCC). The major causative factors of cirrhosis in the United States and Europe are chronic hepatitis C infection and excessive alcohol consumption with nonalcoholic steatohepatitis emerging as another important risk factor. Magnetic resonance imaging is the most sensitive imaging technique for the diagnosis of HCC, and the sensitivity can be further improved with the use of diffusion-weighted imaging and hepatocyte-specific contrast agents. The combination of arterial phase hyperenhancement, venous or delayed phase hypointensity "washout feature," and capsular enhancement are features highly specific for HCC with reported specificities of 96% and higher. When these features are present in a mass in the cirrhotic liver, confirmatory biopsy to establish the diagnosis of HCC is not necessary. Other tumors, such as cholangiocarcinoma, sometimes occur in the cirrhotic at a much lower rate than HCC and can mimic HCC, as do other benign lesions such as perfusion abnormalities. In this article, we discuss the imaging features of cirrhosis and HCC, the role of magnetic resonance imaging in the diagnosis of HCC and other benign and malignant lesions that occur in the cirrhotic liver, and the issue of nonspecific arterially hyperenhancing nodules often seen in cirrhosis.
Collapse
Affiliation(s)
- Daniel C Barr
- From the Department of Radiology/MRI, University of Michigan Health System, Ann Arbor, MI
| | | |
Collapse
|
|
27
|
Diffusion-weighted MRI of hepatocellular carcinoma in cirrhosis. Clin Radiol 2013; 69:1-10. [PMID: 24034549 DOI: 10.1016/j.crad.2013.07.022] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2013] [Revised: 07/16/2013] [Accepted: 07/18/2013] [Indexed: 12/17/2022]
Abstract
The internationally accepted diagnostic criteria for hepatocellular carcinoma (HCC) in cirrhosis are highly accurate for large tumours, but offer relatively low sensitivity for small (<2 cm) tumours. Diffusion-weighted imaging (DWI) is a functional magnetic resonance imaging (MRI) technique that has been studied extensively as an aid to visualize various abdominal malignancies, including HCC in cirrhosis. DWI maps water diffusivity, which in HCC may be restricted as a result of changes ensuing from hepatocarcinogenesis. The present review is based on up-to-date evidence and describes the strengths and weaknesses of DWI, both as a standalone technique and as an adjunct sequence to conventional protocols, in the diagnosis, staging, prognostication, and assessment of treatment response of HCC in cirrhosis.
Collapse
|
|
28
|
Detection and characterization of focal hepatic lesions with diffusion-weighted MR imaging: a pictorial review. ACTA ACUST UNITED AC 2013; 38:297-308. [PMID: 22842549 DOI: 10.1007/s00261-012-9940-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The purpose of this pictorial review is to discuss the usefulness and limitations of diffusion-weighted (DW) MR imaging of the liver, demonstrating DW images of a variety of focal hepatic diseases. We include hepatocellular carcinoma, borderline-lesions in cirrhosis, metastasis, cavernous hemangioma, cyst, focal nodular hyperplasia, hepatic adenoma, abscess, and hematoma. DW imaging is an important supplementary sequence of routine MR imaging protocols of the liver. Radiologists need to understand its usefulness and limitations in the detection and characterization of benign and malignant focal hepatic diseases.
Collapse
|
|
29
|
Validation of organ procurement and transplant network (OPTN)/united network for organ sharing (UNOS) criteria for imaging diagnosis of hepatocellular carcinoma. Transplantation 2013; 95:1506-11. [PMID: 23778569 DOI: 10.1097/tp.0b013e31828eeab2] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Imaging diagnosis of hepatocellular carcinoma (HCC) presents an important pathway for transplant exception points and priority for cirrhotic patients. The purpose of this retrospective study is to evaluate the validity of the new Organ Procurement and Transplant Network (OPTN) classification system on patients undergoing transplantation for HCC. METHODS One hundred twenty-nine patients underwent transplantation for HCC from April 14, 2006 to April 18, 2011; a total of 263 lesions were reported as suspicious for HCC on pretransplantation magnetic resonance imaging. Magnetic resonance imaging examinations were reviewed independently by two experienced radiologists, blinded to final pathology. Reviewers identified major imaging features and an OPTN classification was assigned to each lesion. Final proof of diagnosis was pathology on explant or necrosis along with imaging findings of ablation after transarterial chemoembolization. RESULTS Application of OPTN imaging criteria in our population resulted in high specificity for the diagnosis of HCC. Sensitivity in diagnosis of small lesions (≥1 and <2 cm) was low (range, 26%-34%). Use of the OPTN system would have resulted in different management in 17% of our population who had received automatic exception points for HCC based on preoperative imaging but would not have met criteria under the new system. Eleven percent of the patients not meeting OPTN criteria were found to have T2 stage tumor burden on pathology. CONCLUSIONS The OPTN imaging policy introduces a high level of specificity for HCC but may decrease sensitivity for small lesions. Management may be impacted in a number of patients, potentially requiring longer surveillance periods or biopsy to confirm diagnosis.
Collapse
|
|
30
|
Kim BS, Hayashi PH, Kim SH, Angthong W, Srirattanapong S, Woosley JT, Semelka RC. Outcomes of Patients with Elevated α-Fetoprotein Level and Initial Negative Findings at MR Imaging. Radiology 2013; 268:109-19. [DOI: 10.1148/radiol.13121314] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
|
|
31
|
Hennedige T, Venkatesh SK. Imaging of hepatocellular carcinoma: diagnosis, staging and treatment monitoring. Cancer Imaging 2013; 12:530-547. [PMID: 23400006 PMCID: PMC3666429 DOI: 10.1102/1470-7330.2012.0044] [Citation(s) in RCA: 126] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/23/2012] [Indexed: 12/11/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Imaging is important for establishing a diagnosis of HCC. Several imaging modalities including ultrasonography (US), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and angiography are used in evaluating patients with chronic liver disease and suspected HCC. CT, MRI and contrast-enhanced US have replaced biopsy for diagnosis of HCC. Dynamic multiphase contrast-enhanced CT or MRI is the current standard for imaging diagnosis of HCC. Functional imaging techniques such as perfusion CT and diffusion-weighted MRI provide additional information about tumor angiogenesis that may be useful for treatment. Techniques evaluating tissue mechanical properties such as magnetic resonance elastography, and acoustic radiation force impulse imaging are being explored for characterizing liver lesions. The role of PET in the evaluation of HCC is evolving with promise seen especially with the use of a hepatocyte-specific PET tracer. Imaging is also critical for assessment of treatment response and detection of recurrence following locoregional treatment. Knowledge of the post-treatment appearance of HCC is essential for correct interpretation. This review article provides an overview of the role of imaging in the diagnosis, staging and post-treatment follow-up of HCC.
Collapse
Affiliation(s)
- Tiffany Hennedige
- Diagnostic Imaging, National University Hospital, National University Health System, Singapore
| | | |
Collapse
|
|
32
|
Higaki A, Ito K, Tamada T, Teruki S, Yamamoto A, Higashi H, Kanki A, Sato T, Noda Y. High-risk nodules detected in the hepatobiliary phase of Gd-EOB-DTPA-enhanced mr imaging in cirrhosis or chronic hepatitis: Incidence and predictive factors for hypervascular transformation, preliminary results. J Magn Reson Imaging 2012; 37:1377-83. [DOI: 10.1002/jmri.23933] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2012] [Accepted: 10/02/2012] [Indexed: 12/13/2022] Open
|
|
33
|
Parente DB, Perez RM, Eiras-Araujo A, Oliveira Neto JA, Marchiori E, Constantino CP, Amorim VB, Rodrigues RS. MR imaging of hypervascular lesions in the cirrhotic liver: a diagnostic dilemma. Radiographics 2012; 32:767-87. [PMID: 22582358 DOI: 10.1148/rg.323115131] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Cirrhosis is characterized by a spectrum of hepatocellular nodules that mark the progression from regenerative nodules to low- and high-grade dysplastic nodules, followed by small and large hepatocellular carcinomas (HCCs). Characterization of small nodules on the basis of imaging and histopathologic findings is complicated by an overlap in findings associated with each type of nodule, a reflection of their multistep transitions. Vascularity patterns change gradually as the nodules evolve, with an increasing shift from predominantly venous to predominantly arterial perfusion. Regenerative and low-grade dysplastic nodules demonstrate predominantly portal perfusion and contrast enhancement similar to that of surrounding parenchyma. Differentiation of high-grade dysplastic nodules and well-differentiated HCCs on the basis of dynamic imaging and histologic findings is challenging, with a high rate of false-negative results. Some small nodules that lack hypervascularity may be early HCCs. Progressed small and large HCCs usually present no diagnostic difficulty because of their characteristic findings. Although characterization of hypervascular lesions in the cirrhotic liver is difficult, it is a key step in disease management and is the radiologist's responsibility.
Collapse
Affiliation(s)
- Daniella B Parente
- Federal University of Rio de Janeiro, Av. Lineu de Paula Machado 896/601, Jardim Botânico, CEP 22470-040, Rio de Janeiro, Brazil.
| | | | | | | | | | | | | | | |
Collapse
|
|
34
|
Park MS, Kim S, Patel J, Hajdu CH, Do RKG, Mannelli L, Babb JS, Taouli B. Hepatocellular carcinoma: detection with diffusion-weighted versus contrast-enhanced magnetic resonance imaging in pretransplant patients. Hepatology 2012; 56:140-8. [PMID: 22370974 DOI: 10.1002/hep.25681] [Citation(s) in RCA: 89] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2011] [Accepted: 02/16/2012] [Indexed: 12/13/2022]
Abstract
UNLABELLED This study evaluates the performance of diffusion-weighted magnetic resonance imaging (DWI) for the detection of hepatocellular carcinoma (HCC) in pre-liver transplantation patients, compared and combined with contrast-enhanced T1-weighted imaging (CET1WI), using liver explant as the standard of reference. We included 52 patients with cirrhosis (40 men, 12 women; mean age, 56 years) who underwent DWI and CET1WI within 90 days of liver transplantation. Magnetic resonance images were analyzed for HCC detection in three separate sessions by two independent observers: DWI images (DW-set), CET1WI (CE-set), and all images together (All-set). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), per-patient accuracy, and per-lesion PPV were calculated for each image set. A total of 72 HCCs were present in 33 patients at explant (mean size, 1.5 cm [range, 0.3-6.2 cm]). Per-patient sensitivity and NPV of CE-set were significantly higher than those of DW-set when using pooled data between observers (P = 0.02 and 0.03, respectively), whereas specificity, PPV, and accuracy were equivalent. Per-lesion sensitivity was significantly higher for CE-set versus DW-set (59.0% versus 43.8%; P = 0.008, pooled data from two observers). When stratified by lesion size, the difference was significant only for lesions with a size between 1 and 2 cm (42.0% for DW-set versus 74.0% for CE-set; P = 0.001). The addition of DWI to CET1WI improved sensitivity for the more experienced observer. CONCLUSION DWI is outperformed by CET1WI for detection of HCC, but represents a reasonable alternative to CET1WI for detection of HCC with a size above 2 cm. The addition of DWI to CET1WI slightly increases the detection rate.
Collapse
Affiliation(s)
- Mi-Suk Park
- Departments of Radiology, New York University Langone Medical Center, New York, NY, USA
| | | | | | | | | | | | | | | |
Collapse
|
|
35
|
Frydrychowicz A, Lubner MG, Brown JJ, Merkle EM, Nagle SK, Rofsky NM, Reeder SB. Hepatobiliary MR imaging with gadolinium-based contrast agents. J Magn Reson Imaging 2012; 35:492-511. [PMID: 22334493 DOI: 10.1002/jmri.22833] [Citation(s) in RCA: 107] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
The advent of gadolinium-based "hepatobiliary" contrast agents offers new opportunities for diagnostic magnetic resonance imaging (MRI) and has triggered great interest for innovative imaging approaches to the liver and bile ducts. In this review article we discuss the imaging properties of the two gadolinium-based hepatobiliary contrast agents currently available in the U.S., gadobenate dimeglumine and gadoxetic acid, as well as important pharmacokinetic differences that affect their diagnostic performance. We review potential applications, protocol optimization strategies, as well as diagnostic pitfalls. A variety of illustrative case examples will be used to demonstrate the role of these agents in detection and characterization of liver lesions as well as for imaging the biliary system. Changes in MR protocols geared toward optimizing workflow and imaging quality are also discussed. It is our aim that the information provided in this article will facilitate the optimal utilization of these agents and will stimulate the reader's pursuit of new applications for future benefit.
Collapse
Affiliation(s)
- Alex Frydrychowicz
- Department of Radiology and Nuclear Medicine, University of Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | | | | | | | | | | | | |
Collapse
|
|
36
|
Golfieri R, Grazioli L, Orlando E, Dormi A, Lucidi V, Corcioni B, Dettori E, Romanini L, Renzulli M. Which is the best MRI marker of malignancy for atypical cirrhotic nodules: hypointensity in hepatobiliary phase alone or combined with other features? Classification after Gd-EOB-DTPA administration. J Magn Reson Imaging 2012; 36:648-57. [PMID: 22592930 DOI: 10.1002/jmri.23685] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2011] [Accepted: 03/20/2012] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To investigate whether the malignancy of atypical nodules in cirrhosis can be identified at gadoxetic-acid-disodium(Gd-EOB-DTPA)-MRI by their hypointensity in the hepatobiliary(HB)-phase alone or combined with any other MR imaging features. MATERIALS AND METHODS One hundred eleven atypical nodules detected in 77 consecutive Gd-EOB-DTPA-MRIs were divided, based on arterial-phase behavior, into: Class I, isovascular (n = 82), and Class II, hypervascular without portal/delayed washout (n = 29). The two classes were further grouped based on HB-phase intensity (A/B/C hypo/iso/hyperintensity). Portal/venous/equilibrium-phase behavior and T2w features were also collected. Histology was the gold standard. Per-nodule sensitivity, specificity, negative and positive predictive values (NPV/PPV), and diagnostic accuracy were calculated for HB-phase hypointensity alone, and combined with vascular patterns and T2w hyperintensity. RESULTS Histology detected 60 benign and 51 malignant/premalignant nodules [10 overt hepatocellular carcinomas (HCCs) and 41 high-grade dysplastic nodules (HGDN)/early HCC]. Class IA contained 31 (94%) malignancies, IB one (3%), and IC only benign lesions. Class IIA had 100% malignancies, IIB three (37.5%) and IIC only two (28.5%). HB-phase hypointensity alone (Classes I-IIA) had 88% sensitivity, 91% NPV, and 93% diagnostic accuracy, superior (P < 0.05, P < 0.006, and P < 0.05, respectively) to any other MR imaging feature alone or combined. CONCLUSION In atypical cirrhotic nodules, HB-phase hypointensity by itself is the strongest marker of malignancy.
Collapse
Affiliation(s)
- Rita Golfieri
- Radiology Unit, Department of Digestive Diseases and Internal Medicine; Sant'Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, Bologna, Italy
| | | | | | | | | | | | | | | | | |
Collapse
|
|
37
|
Rhee H, Kim MJ, Park MS, Kim KA. Differentiation of early hepatocellular carcinoma from benign hepatocellular nodules on gadoxetic acid-enhanced MRI. Br J Radiol 2012; 85:e837-44. [PMID: 22553295 DOI: 10.1259/bjr/13212920] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE To test new diagnostic criteria for the discrimination of early hepatocellular carcinoma (HCC) from benign hepatocellular nodules on gadoxetic acid-enhanced MRI (Gd-EOB-MRI). METHODS We retrospectively analysed 34 patients with 29 surgically diagnosed early HCCs and 31 surgically diagnosed benign hepatocellular nodules. Two radiologists reviewed Gd-EOB-MRI, including diffusion-weighted imaging (DWI), and the signal intensity at each sequence, presence of arterial enhancement and washout were recorded. We composed new diagnostic criteria based on the lesion size and MRI findings, and then the diagnostic performance was compared with that of conventional imaging criteria with logistic regression and a generalised estimating equation method. RESULTS A size cut-off value (≥1.5 cm diameter) and MRI findings of T(1) hypointensity, T(2) hyperintensity, DWI hyperintensity on both low and high b-value images (b=50 and 800 s mm(-2), respectively), arterial enhancement, late washout and hepatobiliary hypointensity were selected as the diagnostic criteria. When lesions were considered malignant if they satisfied three or more of the above criteria, the sensitivity was significantly higher than when making a diagnosis based on arterial enhancement and washout alone (58.6% vs 13.8%, respectively; p=0.0002), while the specificity was 100.0% for both criteria. CONCLUSION Our new diagnostic criteria on Gd-EOB-MRI may help to improve the discrimination of early HCC from benign hepatocellular nodules.
Collapse
Affiliation(s)
- H Rhee
- Department of Radiology, Yonsei University Severance Hospital, Seoul, Republic of Korea
| | | | | | | |
Collapse
|
|
38
|
Abstract
Magnetic resonance imaging, MRI has more advantages than ultrasound, computed tomography, CT, positron emission tomography, PET, or any other imaging modality in diagnosing focal hepatic masses. With a combination of basic T1 and T2 weighted sequences, diffusion weighted imaging, DWI, and hepatobiliary gadolinium contrast agents, that is gadobenate dimeglumine (Gd-BOPTA) and gadoxetic acid (Gd-EOB), most liver lesions can be adequately diagnosed. Benign lesions, as cyst, hemangioma, focal nodular hyperplasia, FNH or adenoma, can be distinguished from malignant lesions. In a non-cirrhotic liver, the most common malignant lesions are metastases which may be hypovascular or hypervascular. In the cirrhotic liver hepatocellular carcinoma, HCC, is of considerable importance. Besides, intrahepatic cholangiocarcinoma and other less common malignancies has to be assessed. In this review, the techniques and typical MRI features are presented as well as the new algorithm issued by American Association for the Study of the Liver Diseases (AASLD).
Collapse
Affiliation(s)
- Nils Albiin
- Division of Radiology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| |
Collapse
|
|
39
|
Can the patient with cirrhosis be imaged for hepatocellular carcinoma without gadolinium?: Comparison of combined T2-weighted, T2*-weighted, and diffusion-weighted MRI with gadolinium-enhanced MRI using liver explantation standard. J Comput Assist Tomogr 2012; 35:711-5. [PMID: 22082541 DOI: 10.1097/rct.0b013e31823421ac] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE This study aimed to evaluate a non-gadolinium-enhanced magnetic resonance imaging (MRI) protocol including T2-weighted, T2*-weighted, and diffusion-weighted MRI sequences for identifying hepatocellular carcinoma (HCC) with liver explantation as the reference standard. Also, a stand-alone pre- and dynamic post-gadolinium-enhanced liver MRI data set was interpreted from the available patient data for relative comparison purposes. MATERIALS AND METHODS A retrospective review identified 37 appropriately selected liver transplant patients who had had preoperative MRI. Two data sets were created from the MRI studies: (1) non-gadolinium-enhanced (including T2-weighted, T2*-weighted, and diffusion-weighted sequences) and (2) pre- and dynamic post-gadolinium-enhanced (3-dimensional T1-weighted gradient recalled echo) and were presented to 2 independent, blinded observers. A separate blinded observer assessed the pathologic results from liver explantation to establish the reference standard. RESULTS On explant pathology, 21 of 37 patients had 31 HCC (mean [SD] largest diameter, 19 [9] cm; range, 7-40 mm). Per-lesion sensitivity of non-gadolinium-enhanced MRI for identifying HCC was 52% (reader 1) and 55% (reader 2), and specificity was 90% (reader 1) and 88% (reader 2). Per-lesion sensitivity of the stand-alone pre- and dynamic post-gadolinium-enhanced MRI was 84% (reader 1) and 81% (reader 2), and specificity was 62% (reader 1) and 65% (reader 2). CONCLUSIONS Non-gadolinium-enhanced MRI had a moderate sensitivity for HCC but had a high specificity. Although non-gadolinium-enhanced MRI cannot be recommended as a primary imaging approach for HCC, the results demonstrate the contribution of non-gadolinium-enhanced sequences to imaging of HCC. A non-gadolinium-enhanced MRI protocol may have a diagnostic value when gadolinium cannot be administered.
Collapse
|
|
40
|
|
|
41
|
Fowler KJ, Brown JJ, Narra VR. Magnetic resonance imaging of focal liver lesions: approach to imaging diagnosis. Hepatology 2011; 54:2227-37. [PMID: 21932400 DOI: 10.1002/hep.24679] [Citation(s) in RCA: 83] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
This article is a review of magnetic resonance imaging (MRI) of incidental focal liver lesions. This review provides an overview of liver MRI protocol, diffusion-weighted imaging, and contrast agents. Additionally, the most commonly encountered benign and malignant lesions are discussed with emphasis on imaging appearance and the diagnostic performance of MRI based on a review of the literature.
Collapse
Affiliation(s)
- Kathryn J Fowler
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO 63110, USA.
| | | | | |
Collapse
|
|
42
|
Guo L, Liang C, Yu T, Wang G, Li N, Sun H, Gao F, Liu C. 3 T MRI of hepatocellular carcinomas in patients with cirrhosis: does T2-weighted imaging provide added value? Clin Radiol 2011; 67:319-28. [PMID: 22099524 DOI: 10.1016/j.crad.2011.08.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2011] [Revised: 07/31/2011] [Accepted: 08/12/2011] [Indexed: 01/08/2023]
Abstract
AIM To assess whether T2-weighted imaging (T2WI) provides any added value for the detection of hepatocellular carcinoma (HCC) in patients with cirrhosis, especially for lesions smaller than 2 cm. MATERIALS AND METHODS Sixty-five patients with cirrhosis underwent liver 3 T MRI. Images were qualitatively analysed independently by two observers in two separate sessions, including a dynamic enhanced session and a combination of dynamic and T2WI. The diagnostic accuracy was evaluated using the alternating free-response receiver operating characteristic. Sensitivity and positive predictive values were calculated for all HCCs and for the subgroup of HCCs that were smaller than 2 cm. Additionally, artefacts on T2WI were evaluated by two observers in consensus. RESULTS Ninety HCCs (>2 cm n = 36; ≤2 cm n = 54) were detected in 46 patients. For all HCCs and for lesions smaller than 2 cm, the sensitivities were significantly higher for the combined session than the dynamic session alone (p < 0.05). Conversely, for the Az and positive predictive values, there was no significant difference between the two sessions. For smaller HCC, 9% (5/54) and 7% (4/54) of the 54 HCCs were correctly interpreted by observers 1 and 2, respectively, only when T2WI was included. Three false-positive lesions (≤2 cm) were correctly diagnosed by one of the observers after combining T2WI. Conspicuity of only one large HCC was severely reduced by the artefacts from massive ascites. CONCLUSION At 3 T liver imaging, combining with T2WI can improve the sensitivity of detection of HCC compared with dynamic MRI alone by increasing observer confidence, especially for lesions smaller than 2 cm. Additionally, T2 image quality was not significantly affected by artefacts.
Collapse
Affiliation(s)
- L Guo
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, PR China
| | | | | | | | | | | | | | | |
Collapse
|
|
43
|
Hypervascular hepatocellular carcinoma 1 cm or smaller in patients with chronic liver disease: characterization with gadoxetic acid-enhanced MRI that includes diffusion-weighted imaging. AJR Am J Roentgenol 2011; 196:W758-65. [PMID: 21606265 DOI: 10.2214/ajr.10.4394] [Citation(s) in RCA: 99] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE The purpose of this study was to determine the finding most predictive for characterizing hypervascular hepatocellular carcinoma (HCC) measuring 1 cm or less at gadoxetic acid-enhanced MRI that includes diffusion-weighted images. MATERIALS AND METHODS In this retrospective study, between May 2008 and June 2009, 66 patients with 108 hypervascular HCCs 1 cm or smaller underwent gadoxetic acid-enhanced 3-T MRI that included diffusion-weighted images. The diagnosis of HCC was determined by surgical resection in 32 cases, percutaneous biopsy in three cases, or interval growth to larger than 1 cm on follow-up images in accordance with the American Association for the Study of Liver Diseases guidelines in 73 cases. MRI findings of HCC and 33 benign hypervascular lesions in a control group were analyzed by two radiologists in consensus. They based their assessments on the presence or absence of the following five findings: hyperintensity on T2-weighted images, hyperintensity on diffusion-weighted images with low b values, washout pattern, capsular enhancement, and hypointensity on gadoxetic acid-enhanced hepatobiliary phase images. The findings were compared by use of univariate and multivariate analyses. RESULTS No HCC with capsular enhancement was found. Fifty-seven HCCs (52.8%) had four findings, 36 (33.3%) had three, nine (8.3%) had two findings, and six (5.6%) had one finding. Univariate analysis showed significant differences between the HCC and control groups with respect to four findings (p < 0.0001). Multivariate analysis showed that hyperintensity on T2-weighted (p < 0.0001) and diffusion-weighted (p = 0.0081) images were statistically significant MRI findings for predicting HCC. CONCLUSION Hyperintensity on both T2- and diffusion-weighted images is helpful in the diagnosis of hypervascular HCC smaller than 1 cm in diameter.
Collapse
|
|
44
|
Ouedraogo W, Tran-Van Nhieu J, Baranes L, Lin SJ, Decaens T, Laurent A, Djabbari M, Pigneur F, Duvoux C, Kobeiter H, Deux JF, Rahmouni A, Luciani A. [Evaluation of noninvasive diagnostic criteria for hepatocellular carcinoma on pretransplant MRI (2010): correlation between MR imaging features and histological features on liver specimen]. ACTA ACUST UNITED AC 2011; 92:688-700. [PMID: 21819911 DOI: 10.1016/j.jradio.2011.03.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2010] [Revised: 03/01/2011] [Accepted: 03/14/2011] [Indexed: 12/23/2022]
Abstract
PURPOSE To validate the 2010 diagnostic criteria from the American Association for the Study of Liver Diseases (AASLD) for hepatocellular carcinoma (HCC) on MRI using the surgical liver specimen as a gold standard. PATIENTS AND METHODS A total of 21 liver transplant recipients were retrospectively included. Each underwent surgery because of HCC between January 2007 and January 2008. Pre-transplant MRI was performed on a 1.5 Tesla MR unit. The T1W and T2W signal and kinetic contrast enhancement were correlated for each lesion with the surgical specimen. Lesion diameters between MRI and specimen were compared (Spearman). A multivariate model was created (R statistics software package) to predict the presence and grade of tumor differentiation (WHO, Edmonson Steiner). RESULTS A total of 71 nodules were detected at histology, including 54 HCC (mean size: 25.3mm) compared to 68 on MRI. There was moderate agreement (r=0.58, P<0.001) between the maximum lesion diameters measured on MRI and at histology. Wash-out on MRI provided an accuracy of 75 % for the detection of HCC (sensitivity=75 %, specificity=76 %). Adding T2W hyperintensity to the AASLD criteria increased the sensitivity of MRI from 70.3 % to 77.7 % for the diagnosis of HCC and from 67.6 % to 79 % for nodules less than 20mm in diameter, without affecting specificity. On multivariate analysis, wash out as a single variable was significantly associated with a diagnosis of HCC (P<0.01, odds ratio 12.0, CI 95 % [2.6-55.5]). T1W hyperintensity (P=0.04, odds ratio 5.4) and loss of signal on opposed-phase images (P=0.02, odds ratio 9.2) were predictive of good differentiation. CONCLUSION On MRI, the AASLD criteria or presence of wash out within a liver nodule in patients with underlying chronic hepatocellular disease are suggestive of tumoral transformation. The addition of T2W hyperintensity to the AASLD criteria increases the detection of HCC, especially nodules smaller than 20mm.
Collapse
Affiliation(s)
- W Ouedraogo
- Service d'imagerie médicale, groupe Henri-Mondor-Albert-Chenevier, AP-HP, 51, avenue du Maréchal-de-Lattre-de-Tassigny, 94010 Créteil, France
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
|
45
|
Microvascular invasion in hepatocellular carcinoma: is it predictable with pretransplant MRI? AJR Am J Roentgenol 2011; 196:1083-9. [PMID: 21512074 DOI: 10.2214/ajr.10.4720] [Citation(s) in RCA: 86] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE The purpose of this article is to correlate clinicopathologic and MRI parameters with the presence of microvascular invasion at histopathologic examination in patients with hepatocellular carcinoma (HCC) who are undergoing liver transplantation. MATERIALS AND METHODS In this retrospective single-center study, we assessed 60 patients (47 men and 13 women; mean age, 58 years) with HCC who underwent liver transplantation and pretransplant MRI (performed within 90 days before liver transplantation). Two observers analyzed the following tumor parameters in consensus: number, size, T1 and T2 signal intensity, margins, presence of capsule or pseudocapsule, distance to closest vessel, distance to liver capsule, and quantitative tumor enhancement. The size and number of HCCs, tumor differentiation, and the presence or absence of microvascular invasion were determined at histopathologic examination. Odds ratios (ORs) were calculated and logistic regression analysis was performed to assess the utility of these clinicopathologic and imaging parameters for predicting microvascular invasion. RESULTS None of the clinical parameters or morphologic and enhancement MRI features of HCC was predictive of microvascular invasion. Tumor multifocality, on both MRI and pathologic examination, was the only variable that predicted microvascular invasion (OR = 2.43 and p = 0.013 for MRI; OR = 1.94 and p = 0.013 for pathologic examination). The presence of three or more tumors on MRI and four or more tumors at pathologic examination had high specificity (88.2% and 91.2%, respectively) for the prediction of microvascular invasion. CONCLUSION Tumor multifocality on MRI was the only parameter that correlated significantly with microvascular invasion. All other MRI tumor characteristics failed to predict microvascular invasion.
Collapse
|
|
46
|
Lewis RB, Lattin GE, Makhlouf HR, Levy AD. Tumors of the liver and intrahepatic bile ducts: radiologic-pathologic correlation. Magn Reson Imaging Clin N Am 2011; 18:587-609, xii. [PMID: 21094457 DOI: 10.1016/j.mric.2010.08.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Primary tumors of the liver can be classified pathologically based on their cell of origin into epithelial tumors, arising from hepatocytes or biliary epithelium, and nonepithelial tumors, including mesenchymal tumors and lymphoma. Characteristic findings on MR imaging can be seen in many cases. This article reviews the MR imaging appearance of these tumors with pathologic correlation.
Collapse
Affiliation(s)
- Rachel B Lewis
- Department of Radiologic Pathology, Armed Forces Institute of Pathology, 6825 16th Street NW, Washington, DC 20306-6000, USA.
| | | | | | | |
Collapse
|
|
47
|
Khatri G, Merrick L, Miller FH. MR imaging of hepatocellular carcinoma. Magn Reson Imaging Clin N Am 2011; 18:421-50, x. [PMID: 21094448 DOI: 10.1016/j.mric.2010.08.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Hepatocellular carcinoma (HCC) is a common malignancy typically associated with chronic liver disease and is a leading cause of mortality among these patients. Prognosis is improved when detected early. MRI is the best imaging examination for accurate diagnosis. Although arterial enhancement with delayed washout, increased T2-weighted signal intensity, delayed capsular enhancement, restricted diffusion, and tumor thrombus are typical features, not all lesions demonstrate these findings. The radiologist must be familiar with these typical imaging characteristics, and less common appearances and associated findings of HCC, and must be able to differentiate them from those of lesions that mimic HCC. Knowledge of therapeutic options and how those are related to imaging findings is imperative to assist clinicians in managing these patients.
Collapse
Affiliation(s)
- Gaurav Khatri
- Department of Radiology, Northwestern University Feinberg School of Medicine, 676 North St Clair Street, Suite 800, Chicago, IL 60611, USA
| | | | | |
Collapse
|
|
48
|
Saboo SS, Krajewski KM, Jagannathan JP, O'Regan KN, Odze R, Ramaiya N, Wolpin BM. Rapid progression of combined hepatocellular carcinoma and cholangiocarcinoma. Cancer Imaging 2011; 11:37-41. [PMID: 21507775 PMCID: PMC3080125 DOI: 10.1102/1470-7330.2011.0009] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CC) is a rare entity comprising 1–14.2% of all primary liver carcinomas. In this report, we present a case of rapid progression of cHCC-CC, a rare tumor in a 77-year-old Caucasian male patient with hepatitis B-induced cirrhosis, moderately elevated alpha fetoprotein, and imaging and pathologic features of a mixed liver tumor. There was no evidence of metastatic disease in the chest, abdomen or pelvis by computed tomography (CT) scan at the time of diagnosis. Needle biopsy of the segment 8 lesion revealed two discrete histologic components to the tumor: well-differentiated HCC and poorly differentiated adenocarcinoma, consistent with intrahepatic CC.The patient rapidly developed metastatic disease after initial local therapy with hepatic arterial chemoembolization and percutaneous cryoablation, dying within 5 months of diagnosis. Radiofrequency ablation, cryoablation and radioembolization with yttrium-90 microspheres remain possible treatment strategies for patients with cHCC-CC unable to undergo surgical resection. The diagnosis and treatment of cHCC-CC can be challenging due to clinical, imaging and histological features that overlap with pure HCC and CC.
Collapse
Affiliation(s)
- Sachin S Saboo
- Department of Radiology, Dana Farber Cancer Institute, Harvard Medical School, and Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA.
| | | | | | | | | | | | | |
Collapse
|
|
49
|
Rode A. [Radiological diagnosis of hepatocellular carcinoma in 2010]. Cancer Radiother 2011; 15:7-12. [PMID: 21256790 DOI: 10.1016/j.canrad.2010.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2010] [Revised: 05/10/2010] [Accepted: 11/05/2010] [Indexed: 11/25/2022]
Abstract
The aim of diagnosis imaging is to detect hepatocellular carcinoma at an early stage, when a curative treatment is available. Biopsy is no longer required prior to treatment, and diagnosis of hepatocellular carcinoma is heavily dependent of imaging characteristics. Therefore, the purpose of this article is to describe the typical features of small (<20mm) and larger hepatocellular carcinomas with noninvasive diagnostic criteria, including ultrasound, computed tomography and MRI. Advances in these imaging modalities have greatly improved the detection of small hepatic nodules on liver cirrhosis, including the different steps of carcinogenesis, from regenerative to dysplastic nodules, and we emphasize the difficulties of radiological differentiation of precancerous lesions and small hepatocellular carcinomas.
Collapse
Affiliation(s)
- A Rode
- Service d'imagerie médicale, hôpital de la Croix-Rousse, 93 Grande-Rue de la Croix-Rousse, Lyon, France.
| |
Collapse
|
|
50
|
Enomoto S, Tamai H, Shingaki N, Mori Y, Moribata K, Shiraki T, Deguchi H, Ueda K, Inoue I, Maekita T, Iguchi M, Yanaoka K, Oka M, Ichinose M. Assessment of hepatocellular carcinomas using conventional magnetic resonance imaging correlated with histological differentiation and a serum marker of poor prognosis. Hepatol Int 2011; 5:730-7. [PMID: 21484138 DOI: 10.1007/s12072-010-9245-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2010] [Accepted: 12/20/2010] [Indexed: 02/08/2023]
Abstract
PURPOSE To establish a method of assessing the malignant potential of hepatocellular carcinoma (HCC) using magnetic resonance imaging (MRI). METHODS For 69 nodules [12 Edmondson (Ed)-I, 48 Ed-II, 9 Ed-III] in 54 HCC patients, signal intensity patterns and enhancement patterns of gadopentate dimeglumine (Gd-DTPA) dynamic studies were correlated with histological differentiation and serum lens culinaris agglutinin-reactive alpha-fetoprotein (AFP-L3) level, which is an indicator of poor prognosis. RESULTS Hypointensity on T1-weighted imaging was seen in 17, 72, and 89% of Ed-I, Ed-II, and Ed-III HCCs, respectively (P < 0.001). Meanwhile, hyperintensity on T2-weighted imaging was seen in 42, 88, and 89% (P < 0.005). Tumor stain during the arterial phase of Gd dynamic MRI was seen in 75, 86, and 89%. Tumor stain washout during the portal phase was seen in 43% of Ed-II and 100% of Ed-III HCCs (P < 0.005). In the Ed-II and Ed-III HCCs, hypointensity on T1-weighted imaging was seen in 65% of AFP-L3-negative HCCs and 90% of AFP-L3-positive HCCs (P = 0.071). Washout of tumor stain during the portal phase was seen in 39% of AFP-L3-negative HCCs and 75% of AFP-L3-positive HCCs (P < 0.05). CONCLUSIONS Although hyperintensity of tumor on T2-weighted imaging and arterial hypervascularity of tumor are considered to be useful for differential diagnosis between well differentiated HCCs and moderately/poorly differentiated HCCs, hypointensity of tumor on T1-weighted imaging and tumor stain washout during the portal phase of Gd-DTPA dynamic MRI reflected poorer histological differentiation of HCCs and correlated with AFP-L3 levels.
Collapse
Affiliation(s)
- Shotaro Enomoto
- Second Department of Internal Medicine, Wakayama Medical University, 811-1 Kimiidera Wakayama City, Wakayama, 641-0012, Japan
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|