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Jin H, Cai Y, Zhang M, Huang L, Bao W, Hu Q, Chen X, Zhou L, Ling W. LI-RADS LR-5 on contrast-enhanced ultrasonography has satisfactory diagnostic specificity for hepatocellular carcinoma: a systematic review and meta-analysis. Quant Imaging Med Surg 2023; 13:957-969. [PMID: 36819240 PMCID: PMC9929373 DOI: 10.21037/qims-22-591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 12/18/2022] [Indexed: 01/12/2023]
Abstract
Background The Liver Imaging Reporting and Data System (LI-RADS) for contrast-enhanced ultrasonography (CEUS) was invented to define suspected liver nodules based on their imaging characteristics. Among the categories of nodules of LI-RADS for CEUS, LR-5 is generally considered to be definitely malignant; however, the exact diagnostic performance of this liver nodule category has varied between different studies. Therefore, we performed this systematic review and meta-analysis to calculate the pooled diagnostic sensitivity, specificity based on important data extracted from some influential clinical studies. Methods A preliminary search of national and international databases, including PubMed/Ovid Medline, Embase, Cochrane Library, Web of Science, and Wan Fang Data, for relevant studies on CEUS LI-RADS LR-5 published between January 2017 and June 2021 was conducted. A literature screening and selection process was undertaken to evaluate the relevance of the articles, and studies deemed eligible for inclusion in the review were subsequently identified. The updated Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied as the main method to assess the risk of bias and applicability of the studies. A meta-analysis of the diagnostic sensitivity and specificity of CEUS LI-RADS LR-5 was performed using the free software, Meta-DiSc 1.4 (Ramóny Cajal Hospital, Madrid, Spain). The area under curve (AUC) was calculated to help determine the diagnostic efficiency. A meta-regression analysis was also performed to identify factors that could have contributed to heterogeneity between the studies. Results Twelve studies with 20 observations focused on investigating the relative diagnostic performance of the CEUS LI-RADS LR-5 category for hepatocellular carcinoma (HCC) detection were finally recruited into the systematic review and meta-analysis. The pooled diagnostic sensitivity was 0.71 [95% confidence interval (CI): 0.69-0.72], with heterogeneity (I2) of 88.4%, and the pooled specificity was 0.93 (95% CI: 0.92-0.95), with an I2 of 71.2%. Study heterogeneity was observed and statistically correlated with the number of centers and the reference standard. Conclusions The CEUS LI-RADS LR-5 category has satisfactory diagnostic efficacy for HCC, as evidenced by an acceptable diagnostic sensitivity of 0.71 and a good diagnostic specificity of 0.93.
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Affiliation(s)
- Hongyu Jin
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Yunshi Cai
- Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Man Zhang
- Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Libin Huang
- Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China
| | - Wanying Bao
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Qibo Hu
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Xuan Chen
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Lingyun Zhou
- Department of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China
| | - Wenwu Ling
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, China
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Comparison of Gadobenate-Enhanced MRI and Gadoxetate-Enhanced MRI for Hepatocellular Carcinoma Detection Using LI-RADS Version 2018: A Prospective Intraindividual Randomized Study. AJR Am J Roentgenol 2021; 218:687-698. [PMID: 34817191 DOI: 10.2214/ajr.21.26818] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: Gadobenate and gadoxetate demonstrate different degrees of intracellular accumulation within hepatocytes, potentially impacting these agents' relative performance for hepatocellular carcinoma (HCC) diagnosis. Objective: To perform an intraindividual comparison of gadobenate-enhanced MRI and gadoxetate-enhanced MRI for detection of HCC, and to assess the impact of inclusion of hepatobiliary phase images on HCC detection for both agents. Methods: This prospective study enrolled 126 patients (112 men, 14 women; mean age 52.3 years) at high risk for HCC who consented to undergo two 3-T liver MRI examinations [one using gadobenate (0.05 mmol/kg), one using gadoxetate (0.025 mmol/kg)], separated by 7-14 days. The order of the two contrast agents was randomized. All examinations included post-contrast dynamic and hepatobiliary phase images (120 minutes for gadobenate; 20 minutes for gadoxetate). Three radiologists independently reviewed the gadobenate and gadoxetate examinations in separate sessions and recorded the location of detected observations. Observations were classified using LI-RADS version 2018 and using a LI-RADS modification whereby hepatobiliary phase hypointensity may upgrade observations from LR-4 to LR-5. Observations classified as LR-5 were considered positive interpretations for HCC. Diagnostic performance for histologically confirmed HCC (n=96) was assessed. Results: Across readers, sensitivity for HCC using dynamic images alone was 74.0%-80.2% for gadobenate versus 54.2%-67.7% for gadoexetate and using dynamic and hepatobiliary phase images was 82.1%-87.4% for gadobenate versus 66.3%-81.1% for gadoxetate. For HCCs measuring 1.0-2.0 cm, sensitivity using dynamic images alone was 61.9% (all readers) for gadobenate versus 38.1%-57.1% for gadoxetate and using dynamic and hepatobiliary phase images was 76.2%-85.7% for gadobenate versus 52.4%-61.9% for gadoxetate. PPV for HCC ranged from 88.6%-97.4% across readers, agents, and image sets. Conclusion: Sensitivity for HCC was higher for gadobenate than for gadoxetate, whether using dynamic images alone or dynamic and hepatobiliary phase images; the improved sensitivity using gadobenate was more pronounced for small HCCs. While hepatobiliary phase images improved sensitivity for both agents, sensitivity of gadobenate using dynamic images alone compared favorably with that of gadoxetate using dynamic and hepatobiliary phase images. Clinical Impact: The findings support gadobenate as a preferred agent over gadoxetate when performing liver MRI in patients at high risk for HCC.
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Consul N, Sirlin CB, Chernyak V, Fetzer DT, Masch WR, Arora SS, Do RKG, Marks RM, Fowler KJ, Borhani AA, Elsayes KM. Imaging Features at the Periphery: Hemodynamics, Pathophysiology, and Effect on LI-RADS Categorization. Radiographics 2021; 41:1657-1675. [PMID: 34559586 DOI: 10.1148/rg.2021210019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Liver lesions have different enhancement patterns at dynamic contrast-enhanced imaging. The Liver Imaging Reporting and Data System (LI-RADS) applies the enhancement kinetic of liver observations in its algorithms for imaging-based diagnosis of hepatocellular carcinoma (HCC) in at-risk populations. Therefore, careful analysis of the spatial and temporal features of these enhancement patterns is necessary to increase the accuracy of liver mass characterization. The authors focus on enhancement patterns that are found at or around the margins of liver observations-many of which are recognized and defined by LI-RADS, such as targetoid appearance, rim arterial phase hyperenhancement, peripheral washout, peripheral discontinuous nodular enhancement, enhancing capsule appearance, nonenhancing capsule appearance, corona enhancement, and periobservational arterioportal shunts-as well as peripheral and periobservational enhancement in the setting of posttreatment changes. Many of these are considered major or ancillary features of HCC, ancillary features of malignancy in general, features of non-HCC malignancy, features associated with benign entities, or features related to treatment response. Distinction between these different patterns of enhancement can help with achieving a more specific diagnosis of HCC and better assessment of response to local-regional therapy. ©RSNA, 2021.
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Affiliation(s)
- Nikita Consul
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Claude B Sirlin
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Victoria Chernyak
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - David T Fetzer
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - William R Masch
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Sandeep S Arora
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Richard K G Do
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Robert M Marks
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Kathryn J Fowler
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Amir A Borhani
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
| | - Khaled M Elsayes
- From the Department of Radiology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 (N.C.); University of California San Diego Health, San Diego, Calif (C.B.S., K.J.F.); Montefiore Medical Center, Bronx, NY (V.C.); University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); University of Michigan Medical School, Ann Arbor, Mich (W.R.M.); Yale School of Medicine, New Haven, Conn (S.S.A.); Memorial Sloan Kettering Cancer Center, New York, NY (R.K.G.D.); Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Northwestern University, Chicago, Ill (A.A.B.); and University of Texas MD Anderson Cancer Center, Houston, Tex (K.M.E.)
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Alksas A, Shehata M, Saleh GA, Shaffie A, Soliman A, Ghazal M, Khelifi A, Khalifeh HA, Razek AA, Giridharan GA, El-Baz A. A novel computer-aided diagnostic system for accurate detection and grading of liver tumors. Sci Rep 2021; 11:13148. [PMID: 34162893 PMCID: PMC8222341 DOI: 10.1038/s41598-021-91634-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 05/28/2021] [Indexed: 12/13/2022] Open
Abstract
Liver cancer is a major cause of morbidity and mortality in the world. The primary goals of this manuscript are the identification of novel imaging markers (morphological, functional, and anatomical/textural), and development of a computer-aided diagnostic (CAD) system to accurately detect and grade liver tumors non-invasively. A total of 95 patients with liver tumors (M = 65, F = 30, age range = 34–82 years) were enrolled in the study after consents were obtained. 38 patients had benign tumors (LR1 = 19 and LR2 = 19), 19 patients had intermediate tumors (LR3), and 38 patients had hepatocellular carcinoma (HCC) malignant tumors (LR4 = 19 and LR5 = 19). A multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) was collected to extract the imaging markers. A comprehensive CAD system was developed, which includes the following main steps: i) estimation of morphological markers using a new parametric spherical harmonic model, ii) estimation of textural markers using a novel rotation invariant gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) models, and iii) calculation of the functional markers by estimating the wash-in/wash-out slopes, which enable quantification of the enhancement characteristics across different CE-MR phases. These markers were subsequently processed using a two-stages random forest-based classifier to classify the liver tumor as benign, intermediate, or malignant and determine the corresponding grade (LR1, LR2, LR3, LR4, or LR5). The overall CAD system using all the identified imaging markers achieved a sensitivity of 91.8%±0.9%, specificity of 91.2%±1.9%, and F\documentclass[12pt]{minimal}
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\begin{document}$$_{1}$$\end{document}1 score of 0.91±0.01, using the leave-one-subject-out (LOSO) cross-validation approach. Importantly, the CAD system achieved overall accuracies of \documentclass[12pt]{minimal}
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\begin{document}$$88\%\pm 5\%$$\end{document}88%±5%, 85%±2%, 78%±3%, 83%±4%, and 79%±3% in grading liver tumors into LR1, LR2, LR3, LR4, and LR5, respectively. In addition to LOSO, the developed CAD system was tested using randomly stratified 10-fold and 5-fold cross-validation approaches. Alternative classification algorithms, including support vector machine, naive Bayes classifier, k-nearest neighbors, and linear discriminant analysis all produced inferior results compared to the proposed two stage random forest classification model. These experiments demonstrate the feasibility of the proposed CAD system as a novel tool to objectively assess liver tumors based on the new comprehensive imaging markers. The identified imaging markers and CAD system can be used as a non-invasive diagnostic tool for early and accurate detection and grading of liver cancer.
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Affiliation(s)
- Ahmed Alksas
- BioImaging Lab, Department of Bioengineering, University of Louisville, Louisville, KY, 40292, USA
| | - Mohamed Shehata
- BioImaging Lab, Department of Bioengineering, University of Louisville, Louisville, KY, 40292, USA
| | - Gehad A Saleh
- Department of Radiology, Faculty of Medicine, Mansoura University, Mansoura, 35516, Egypt
| | - Ahmed Shaffie
- BioImaging Lab, Department of Bioengineering, University of Louisville, Louisville, KY, 40292, USA
| | - Ahmed Soliman
- BioImaging Lab, Department of Bioengineering, University of Louisville, Louisville, KY, 40292, USA
| | - Mohammed Ghazal
- College of Engineering, Abu Dhabi University, Abu Dhabi, UAE
| | - Adel Khelifi
- Computer Science and Information Technology, Abu Dhabi University, Abu Dhabi, UAE
| | | | - Ahmed Abdel Razek
- Department of Radiology, Faculty of Medicine, Mansoura University, Mansoura, 35516, Egypt
| | - Guruprasad A Giridharan
- BioImaging Lab, Department of Bioengineering, University of Louisville, Louisville, KY, 40292, USA
| | - Ayman El-Baz
- BioImaging Lab, Department of Bioengineering, University of Louisville, Louisville, KY, 40292, USA.
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Pesapane F, Downey K, Rotili A, Cassano E, Koh DM. Imaging diagnosis of metastatic breast cancer. Insights Imaging 2020; 11:79. [PMID: 32548731 PMCID: PMC7297923 DOI: 10.1186/s13244-020-00885-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 05/22/2020] [Indexed: 12/11/2022] Open
Abstract
Numerous imaging modalities may be used for the staging of women with advanced breast cancer. Although bone scintigraphy and multiplanar-CT are the most frequently used tests, others including PET, MRI and hybrid scans are also utilised, with no specific recommendations of which test should be preferentially used. We review the evidence behind the imaging modalities that characterise metastases in breast cancer and to update the evidence on comparative imaging accuracy.
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Affiliation(s)
- Filippo Pesapane
- Breast Imaging Division, IEO - European Institute of Oncology IRCCS, Via Giuseppe Ripamonti, 435, 20141, Milano, MI, Italy.
| | - Kate Downey
- Department of Breast Radiology, Royal Marsden Hospital, Downs Road, Sutton, SM2 5PT, UK
| | - Anna Rotili
- Breast Imaging Division, IEO - European Institute of Oncology IRCCS, Via Giuseppe Ripamonti, 435, 20141, Milano, MI, Italy
| | - Enrico Cassano
- Breast Imaging Division, IEO - European Institute of Oncology IRCCS, Via Giuseppe Ripamonti, 435, 20141, Milano, MI, Italy
| | - Dow-Mu Koh
- Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research, 15 Cotswold Road, Sutton, SM2 5NG, UK.,Department of Radiology, Royal Marsden Hospital, Downs Road, Sutton, SM2 5PT, UK
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Liver Imaging Reporting and Data System Version 2018: What Radiologists Need to Know. J Comput Assist Tomogr 2020; 44:168-177. [PMID: 32195795 DOI: 10.1097/rct.0000000000000995] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
In this article, we aim to review Liver Imaging Reporting and Data System version 18 (LI-RADS v2018). Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. Liver Imaging Reporting and Data System developed for standardizing interpreting, reporting, and data collection of HCC describes 5 major features for accurate HCC diagnosis and several ancillary features, some favoring HCC in particular or malignancy in general and others favoring benignity. Untreated hepatic lesions LI-RADS affords 8 unique categories based on imaging appearance on computed tomography and magnetic resonance imaging, which indicate the possibility of HCC or malignancy with or without tumor in vein. Furthermore, LI-RADS defines 4 treatment response categories for treated HCCs after different locoregional therapy. These continuous recent updates on LI-RADS improve the communication between the radiologists and the clinicians for better management and patient outcome.
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The diagnostic value of diffusion-weighted imaging in differentiating benign from malignant hepatic lesions. EGYPTIAN LIVER JOURNAL 2020. [DOI: 10.1186/s43066-020-0020-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Abstract
Background
Diffusion-weighted imaging (DWI) is a novel imaging technique with growing application in onco-imaging. This modality evaluates the diffusion of water molecules in various tissues, which is restricted in hyper cellular regions such as malignant tissue. Apparent diffusion co-efficient (ADC) is a method which can quantify the degree of restriction in tissues and can have diagnostic roles in characterization of hepatic lesions. In this study, 93 patients with proven hepatic lesions were included. These patients had undergone initial evaluation via ultrasonography and dynamic CT scan, and had a definite diagnosis confirmed by biopsy. These patients underwent DW imaging and ADC values of their lesions were calculated. Patients were divided into two groups, benign and malignant groups, based on their biopsy results; and ADC values of hepatic lesions were compared in the two groups.
Results
The two groups were gender matched. There was a significant difference in the age distribution between the two groups. Mean ADC values for benign and malignant hepatic lesions were 1.58 ± 0.35 (10-3 mm2/s) and 0.87 ± 0.16 (10-3 mm2/s), respectively. There was a statistically significant differences between benign and malignant hepatic lesions (p value < 10-3). DW imaging had a sensitivity of 97.6% and specificity of 98.7% in detecting malignant hepatic lesions from benign ones (p = 0.0001, AUC = 0.99).
Conclusion
DW MRI imaging can differentiate malignant and benign liver lesions with high sensitivity and specificity using ADC values generated; furthermore, each subgroup of hepatic lesions could be determined based on ADC values.
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Chaudhry M, McGinty KA, Mervak B, Lerebours R, Li C, Shropshire E, Ronald J, Commander L, Hertel J, Luo S, Bashir MR, Burke LMB. The LI-RADS Version 2018 MRI Treatment Response Algorithm: Evaluation of Ablated Hepatocellular Carcinoma. Radiology 2020; 294:320-326. [PMID: 31845843 DOI: 10.1148/radiol.2019191581] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background The Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is used to assess presumed hepatocellular carcinoma (HCC) after local-regional therapy, but its performance has not been extensively assessed. Purpose To assess the performance of LI-RADS version 2018 TRA in the evaluation of HCC after ablation. Materials and Methods In this retrospective study, patients who underwent ablation therapy for presumed HCC followed by liver transplantation between January 2011 and December 2015 at a single tertiary care center were identified. Lesions were categorized as completely (100%) or incompletely (≤99%) necrotic based on transplant histology. Three radiologists assessed pre- and posttreatment MRI findings using LI-RADS version 2018 and the TRA, respectively. Interreader agreement was assessed by using the Fleiss κ test. Performance characteristics for predicting necrosis category based on LI-RADS treatment response (LR-TR) category (viable or nonviable) were calculated by using generalized mixed-effects models to account for clustering by subject. Results A total of 36 patients (mean age, 58 years ± 5 [standard deviation]; 32 men) with 53 lesions was included. Interreader agreement for pretreatment LI-RADS category was 0.40 (95% confidence interval [CI]: 0.15, 0.67; P < .01) and was lower than the interreader agreement for TRA category (κ = 0.71; 95% CI: 0.59, 0.84; P < .01). After accounting for clustering by subject, sensitivity of tumor necrosis across readers ranged from 40% to 77%, and specificity ranged from 85% to 97% when LR-TR equivocal assessments were treated as nonviable. When LR-TR equivocal assessments were treated as viable, sensitivity of tumor necrosis across readers ranged from 81% to 87%, and specificity ranged from 81% to 85% across readers. Six (11%) of 53 treated lesions were LR-TR equivocal by consensus, with most (five of six) incompletely necrotic at histopathology. Conclusion The Liver Imaging Reporting and Data System treatment response algorithm can be used to predict viable or nonviable hepatocellular carcinoma after ablation. Most ablated lesions rated as treatment response equivocal were incompletely necrotic at histopathology. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Do and Mendiratta-Lala in this issue.
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Affiliation(s)
- Mohammad Chaudhry
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Katrina A McGinty
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Benjamin Mervak
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Reginald Lerebours
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Cai Li
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Erin Shropshire
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - James Ronald
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Leah Commander
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Johann Hertel
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Sheng Luo
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Mustafa R Bashir
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
| | - Lauren M B Burke
- From the Department of Radiology (M.C., E.S., J.R., M.R.B.), Division of Gastroenterology, Department of Medicine (M.R.B.), and Center for Advanced Magnetic Development (M.R.B.), Duke University Medical Center, 200 Trent Dr, Durham, NC 27710; Departments of Radiology (M.C., K.A.M., B.M., L.M.B.B.) and Pathology (L.C., J.H.); Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC (R.L., C.L., S.L.)
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9
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The utility of diffusion-weighted imaging in improving the sensitivity of LI-RADS classification of small hepatic observations suspected of malignancy. Abdom Radiol (NY) 2019; 44:1773-1784. [PMID: 30603882 DOI: 10.1007/s00261-018-01887-z] [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: 12/14/2022]
Abstract
PURPOSE We investigated the added value of diffusion-weighted imaging (DWI)/apparent diffusion coefficient (ADC) in the categorization of small hepatic observation (≤ 20 mm) detected in patients with chronic liver disease in reference to LI-RADS (liver imaging reporting and data system) classification system. METHODS We prospectively evaluated 165 patients with chronic liver disease with small hepatic observations (≤ 20 mm) which were previously categorized as LI-RADS grade 3-5 on dynamic contrast-enhanced CT (DCE-CT). All patients were submitted to a functional MRI including DCE and DWI. Using LI-RADS v2017, two radiologists independently evaluated the observations and assigned a LI-RADS category to each observation using DCE-MRI alone and combined DCE-MRI and DWI/ADC. In the combined technique, the radiologists assigned a LI-RADS category based on a modified LI-RADS criteria in which restricted diffusion on DWI was considered a major feature of HCC. We evaluated the inter-reader agreement with Kappa statistics and compared the diagnostic performance of the LI-RADS with two imaging techniques by Fisher's exact test using histopathology as the reference standard. RESULTS Combined technique in LI-RADS yielded better sensitivities (reader 1, 97% [65/67]; reader 2, 95.5% [64/67]) for HCC diagnosis than DCE-MRI alone (reader 1, 80.6% [54/67], p = 0.005; reader 2, 83.6% [56/67], p = 0.04). The specificities were insignificantly lower in combined technique (reader 1, 88.4% [107/121]; reader 2, 77.7% [94/121]) than in DCE-MRI alone (reader 1, 90.9% [110/121], p = 0.67; reader 2, 79.3% [96/121], p = 0.88). The inter-reader agreement of the LI-RADS scores between combined technique and DCE-MRI was good (κ = 0.765). CONCLUSION The use of DWI/ADC as an additional major criterion, improved the sensitivity of LI-RADS in the diagnosis of HCC while keeping high specificity.
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10
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Filippi L, Schillaci O, Bagni O. Recent advances in PET probes for hepatocellular carcinoma characterization. Expert Rev Med Devices 2019; 16:341-350. [DOI: 10.1080/17434440.2019.1608817] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Luca Filippi
- Department of Nuclear Medicine, Santa Maria Goretti Hospital, Latina, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University Tor Vergata, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Oreste Bagni
- Department of Nuclear Medicine, Santa Maria Goretti Hospital, Latina, Italy
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11
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Krishan S, Dhiman RK, Kalra N, Sharma R, Baijal SS, Arora A, Gulati A, Eapan A, Verma A, Keshava S, Mukund A, Deva S, Chaudhary R, Ganesan K, Taneja S, Gorsi U, Gamanagatti S, Madhusudan KS, Puri P, Shalimar, Govil S, Wadhavan M, Saigal S, Kumar A, Thapar S, Duseja A, Saraf N, Khandelwal A, Mukhopadyay S, Gulati A, Shetty N, Verma N. Joint Consensus Statement of the Indian National Association for Study of the Liver and Indian Radiological and Imaging Association for the Diagnosis and Imaging of Hepatocellular Carcinoma Incorporating Liver Imaging Reporting and Data System. J Clin Exp Hepatol 2019; 9:625-651. [PMID: 31695253 PMCID: PMC6823668 DOI: 10.1016/j.jceh.2019.07.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 07/12/2019] [Indexed: 02/07/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the 6th most common cancer and the second most common cause of cancer-related mortality worldwide. There are currently no universally accepted practice guidelines for the diagnosis of HCC on imaging owing to the regional differences in epidemiology, target population, diagnostic imaging modalities, and staging and transplant eligibility. Currently available regional and national guidelines include those from the American Association for the Study of Liver Disease (AASLD), the European Association for the Study of the Liver (EASL), the Asian Pacific Association for the Study of the Liver, the Japan Society of Hepatology, the Korean Liver Cancer Study Group, Hong Kong, and the National Comprehensive Cancer Network in the United States. India with its large population and a diverse health infrastructure faces challenges unique to its population in diagnosing HCC. Recently, American Association have introduced a Liver Imaging Reporting and Data System (LIRADS, version 2017, 2018) as an attempt to standardize the acquisition, interpretation, and reporting of liver lesions on imaging and hence improve the coherence between radiologists and clinicians and provide guidance for the management of HCC. The aim of the present consensus was to find a common ground in reporting and interpreting liver lesions pertaining to HCC on imaging keeping LIRADSv2018 in mind.
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Affiliation(s)
- Sonal Krishan
- Department of Radiology, Medanta Hospital, Gurgaon, India
| | - Radha K. Dhiman
- Department of Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India,Address for correspondence: Radha Krishan Dhiman, MD, DM, FACG, FRCP, FAASLD, Department of Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
| | - Navin Kalra
- Department of Radiology, Postgraduate Institute Of Medical Education and Research, Chandigarh, India
| | - Raju Sharma
- Department of Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Sanjay S. Baijal
- Department of Diagnostic and Intervention Radiology, Medanta Hospital, Gurgaon, India
| | - Anil Arora
- Institute Of Liver Gastroenterology & Pancreatico Biliary Sciences, Sir Gangaram Hospital, New Delhi, India
| | - Ajay Gulati
- Department of Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Anu Eapan
- Department of Radiology, Christian Medical College, Vellore, India
| | - Ashish Verma
- Department of Radiology, Banaras Hindu University, Varanasi, India
| | - Shyam Keshava
- Department of Radiology, Christian Medical College, Vellore, India
| | - Amar Mukund
- Department of Intervention Radiology, Institute of liver and biliary Sciences, New Delhi, India
| | - S. Deva
- Department of Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Ravi Chaudhary
- Department of Radiology, Medanta Hospital, Gurgaon, India
| | | | - Sunil Taneja
- Department of Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Ujjwal Gorsi
- Department of Radiology, Postgraduate Institute Of Medical Education and Research, Chandigarh, India
| | | | - Kumble S. Madhusudan
- Department of Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Pankaj Puri
- Institute Of Liver Gastroenterology & Pancreatico Biliary Sciences, Sir Gangaram Hospital, New Delhi, India
| | - Shalimar
- Department of GastroEnterology, All India Institute of Medical Sciences, New Delhi, India
| | | | - Manav Wadhavan
- Institute of Digestive and Liver Diseases, BLK Hospital, Delhi, India
| | - Sanjiv Saigal
- Department of Hepatology, Medanta Hospital, Gurgaon, India
| | - Ashish Kumar
- Institute Of Liver Gastroenterology & Pancreatico Biliary Sciences, Sir Gangaram Hospital, New Delhi, India
| | - Shallini Thapar
- Department of Radiology, Institute of liver and biliary Sciences, New Delhi, India
| | - Ajay Duseja
- Department of Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Neeraj Saraf
- Department of Hepatology, Medanta Hospital, Gurgaon, India
| | | | | | - Ajay Gulati
- Department of Radiology, Postgraduate Institute Of Medical Education and Research, Chandigarh, India
| | - Nitin Shetty
- Department of Radiology, Tata Memorial Hospital, Kolkata, India
| | - Nipun Verma
- Department of Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
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12
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Ding Y, Rao SX, Wang WT, Chen CZ, Li RC, Zeng M. Comparison of gadoxetic acid versus gadopentetate dimeglumine for the detection of hepatocellular carcinoma at 1.5 T using the liver imaging reporting and data system (LI-RADS v.2017). Cancer Imaging 2018; 18:48. [PMID: 30526674 PMCID: PMC6286579 DOI: 10.1186/s40644-018-0183-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Accepted: 11/29/2018] [Indexed: 12/15/2022] Open
Abstract
PURPOSE The goal of this study was to investigate the Liver Imaging Reporting and Data System (LI-RADS) v.2017 for the categorization of hepatocellular carcinomas (HCCs) with gadoxetic acid compared with gadopentetate dimeglumine-enhanced 1.5-T magnetic resonance imaging (MRI). MATERIAL AND METHODS We included 141 high-risk patients with 145 pathologically-confirmed HCCs who first underwent gadopentetate dimeglumine-enhanced 1.5-T followed by gadoxetic acid-enhanced 1.5-T MRI. Two independent radiologists evaluated the presence or absence of major HCC features and assigned LI-RADS categories after considering ancillary features on both MRIs. Finally, the sensitivity of LI-RADS category 5 (LR-5) and the frequencies of major HCC features were compared between gadoxetic acid- and gadopentetate dimeglumine-enhanced 1.5-T MRI using the Wilcoxon test. RESULTS The sensitivity of LR-5 for diagnosing HCCs was significantly different between gadoxetic acid- and gadopentetate dimeglumine-enhanced MRI (73.8% [107/145] vs 26.2% [38/145], P < 0.001; 71% [103/145] vs 29% [42/145], P < 0.001 for reviewers 1 and 2, respectively). Among the major HCC LI-RADS features, capsule appearance was less frequently demonstrated on gadoxetic acid-enhanced MRI than on gadopentetate dimeglumine-enhanced MRI (3.4% [5/145] vs 5.5% [8/145], P = 0.793; 4.1% [6/145] vs 5.5% [8/145], P = 0.87 for reviewers 1 and 2, respectively), and the frequency of arterial hyperenhancement was not significantly different between gadoxetic acid and gadopentetate dimeglumine (89% [129/145] vs 89% [129/145], P = 1.000). In addition, the frequency of a washout appearance was less in the transitional phase (TP) than in the portal venous phase (PVP) on gadoxetic acid-enhanced MRI (43% [46/107] vs 57% [61/107], P = 0.367). CONCLUSION Gadoxetic acid-enhanced MRI showed a comparable sensitivity to gadopentetate dimeglumine-enhanced MRI for the diagnosis of HCCs, and LI-RADS category 4 (LR-4) hepatic nodules were upgraded to LR-5 when taking into account the major features according to LI-RADS v.2017.
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Affiliation(s)
- Ying Ding
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai Institute of Medical Imaging, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
| | - Sheng-xiang Rao
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai Institute of Medical Imaging, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
- Department of Medical Imaging, Shanghai Medical College, Fudan University, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
| | - Wen-tao Wang
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai Institute of Medical Imaging, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
| | - Cai-zhong Chen
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai Institute of Medical Imaging, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
| | - Ren-chen Li
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai Institute of Medical Imaging, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai Institute of Medical Imaging, No138, Fenglin Road, Xuhui District, Shanghai, 200032 China
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