BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Barth BK, Donati OF, Fischer MA, Ulbrich EJ, Karlo CA, Becker A, Seifert B, Reiner CS. Reliability, Validity, and Reader Acceptance of LI-RADS-An In-depth Analysis. Acad Radiol 2016;23:1145-53. [PMID: 27174029 DOI: 10.1016/j.acra.2016.03.014] [Cited by in Crossref: 29] [Cited by in F6Publishing: 28] [Article Influence: 4.8] [Reference Citation Analysis]
Number Citing Articles
1 Ballotin VR, Bigarella LG, Soldera J, Soldera J. Deep learning applied to the imaging diagnosis of hepatocellular carcinoma. Artif Intell Gastrointest Endosc 2021; 2(4): 127-135 [DOI: 10.37126/aige.v2.i4.127] [Reference Citation Analysis]
2 Huang Z, Zhou P, Li S, Li K. MR versus CEUS LI-RADS for Distinguishing Hepatocellular Carcinoma from other Hepatic Malignancies in High-Risk Patients. Ultrasound Med Biol 2021;47:1244-52. [PMID: 33610338 DOI: 10.1016/j.ultrasmedbio.2021.01.020] [Reference Citation Analysis]
3 Zhang N, Xu H, Ren AH, Zhang Q, Yang DW, Ba T, Wang ZC, Yang ZH. Does Training in LI-RADS Version 2018 Improve Readers' Agreement with the Expert Consensus and Inter-reader Agreement in MRI Interpretation? J Magn Reson Imaging 2021. [PMID: 33963801 DOI: 10.1002/jmri.27688] [Reference Citation Analysis]
4 Stocker D, Becker AS, Barth BK, Skawran S, Kaniewska M, Fischer MA, Donati O, Reiner CS. Does quantitative assessment of arterial phase hyperenhancement and washout improve LI-RADS v2018–based classification of liver lesions? Eur Radiol 2020;30:2922-33. [DOI: 10.1007/s00330-019-06596-9] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
5 Dietrich CF, Potthoff A, Helmberger T, Ignee A, Willmann JK; on behalf of the CEUS LI-RADS Working Group. Standardisierte Befundung und Dokumentation der Kontrastmittelsonografie der Leber (CEUS LI-RADS). Z Gastroenterol 2018;56:499-506. [DOI: 10.1055/s-0043-124874] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]
6 Li J, Ling W, Chen S, Ma L, Yang L, Lu Q, Luo Y. The interreader agreement and validation of contrast-enhanced ultrasound liver imaging reporting and data system. European Journal of Radiology 2019;120:108685. [DOI: 10.1016/j.ejrad.2019.108685] [Cited by in Crossref: 14] [Cited by in F6Publishing: 10] [Article Influence: 4.7] [Reference Citation Analysis]
7 Kim Y, Furlan A, Borhani AA, Bae KT. Computer-aided diagnosis program for classifying the risk of hepatocellular carcinoma on MR images following liver imaging reporting and data system (LI-RADS). J Magn Reson Imaging. 2018;47:710-722. [PMID: 28556283 DOI: 10.1002/jmri.25772] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 1.8] [Reference Citation Analysis]
8 Wang SH, Han XJ, Du J, Wang ZC, Yuan C, Chen Y, Zhu Y, Dou X, Xu XW, Xu H, Yang ZH. Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI. Insights Imaging 2021;12:173. [PMID: 34817732 DOI: 10.1186/s13244-021-01117-z] [Reference Citation Analysis]
9 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. 2018;286:173-185. [PMID: 29091751 DOI: 10.1148/radiol.2017170376] [Cited by in Crossref: 51] [Cited by in F6Publishing: 48] [Article Influence: 10.2] [Reference Citation Analysis]
10 Yamashita R, Mittendorf A, Zhu Z, Fowler KJ, Santillan CS, Sirlin CB, Bashir MR, Do RKG. Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study. Abdom Radiol45:24-35. [PMID: 31696269 DOI: 10.1007/s00261-019-02306-7] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
11 Park SH, Shim YS, Kim B, Kim SY, Kim YS, Huh J, Park JH, Kim KW, Lee SS. Retrospective analysis of current guidelines for hepatocellular carcinoma diagnosis on gadoxetic acid-enhanced MRI in at-risk patients. Eur Radiol 2021;31:4751-63. [PMID: 33389037 DOI: 10.1007/s00330-020-07577-z] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
12 Fraum TJ, Tsai R, Rohe E, Ludwig DR, Salter A, Nalbantoglu I, Heiken JP, Fowler KJ. Differentiation of Hepatocellular Carcinoma from Other Hepatic Malignancies in Patients at Risk: Diagnostic Performance of the Liver Imaging Reporting and Data System Version 2014. Radiology 2018;286:158-72. [PMID: 28853673 DOI: 10.1148/radiol.2017170114] [Cited by in Crossref: 70] [Cited by in F6Publishing: 67] [Article Influence: 14.0] [Reference Citation Analysis]
13 Pereira RCR, Heming CAM, Tejo TR, de Oliveira TCL, da Silva RDSU, Parente DB. Use of the LI-RADS classification in patients with cirrhosis due to infection with hepatitis B, C, or D, or infected with hepatitis B and D. Radiol Bras 2020;53:14-20. [PMID: 32313331 DOI: 10.1590/0100-3984.2018.0077] [Reference Citation Analysis]
14 An C, Lee CH, Byun JH, Lee MH, Jeong WK, Choi SH, Kim DY, Lim YS, Kim YS, Kim JH, Choi MS, Kim MJ. Intraindividual Comparison between Gadoxetate-Enhanced Magnetic Resonance Imaging and Dynamic Computed Tomography for Characterizing Focal Hepatic Lesions: A Multicenter, Multireader Study. Korean J Radiol 2019;20:1616-26. [PMID: 31854149 DOI: 10.3348/kjr.2019.0363] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 5.0] [Reference Citation Analysis]
15 Yokoo T, Singal AG, Diaz de Leon A, Ananthakrishnan L, Fetzer DT, Pedrosa I, Khatri G. Prevalence and clinical significance of discordant LI-RADS® observations on multiphase contrast-enhanced MRI in patients with cirrhosis. Abdom Radiol 2020;45:177-87. [DOI: 10.1007/s00261-019-02133-w] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 1.7] [Reference Citation Analysis]
16 Hamm CA, Wang CJ, Savic LJ, Ferrante M, Schobert I, Schlachter T, Lin M, Duncan JS, Weinreb JC, Chapiro J, Letzen B. Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI. Eur Radiol. 2019;29:3338-3347. [PMID: 31016442 DOI: 10.1007/s00330-019-06205-9] [Cited by in Crossref: 66] [Cited by in F6Publishing: 56] [Article Influence: 22.0] [Reference Citation Analysis]
17 Yacoub JH, Miller FH. Understanding LI-RADS, Its Relationship to AASLD and OPTN, and the Challenges of Its Adoption. Curr Hepatology Rep 2017;16:72-80. [DOI: 10.1007/s11901-017-0337-y] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.6] [Reference Citation Analysis]
18 Xie J, Zhang A, Wang X. Metabolomic applications in hepatocellular carcinoma: toward the exploration of therapeutics and diagnosis through small molecules. RSC Adv 2017;7:17217-26. [DOI: 10.1039/c7ra00698e] [Cited by in Crossref: 13] [Article Influence: 2.6] [Reference Citation Analysis]
19 Wang CJ, Hamm CA, Savic LJ, Ferrante M, Schobert I, Schlachter T, Lin M, Weinreb JC, Duncan JS, Chapiro J, Letzen B. Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features. Eur Radiol. 2019;29:3348-3357. [PMID: 31093705 DOI: 10.1007/s00330-019-06214-8] [Cited by in Crossref: 30] [Cited by in F6Publishing: 27] [Article Influence: 10.0] [Reference Citation Analysis]
20 Hong CW, Park CC, Mamidipalli A, Hooker JC, Fazeli Dehkordy S, Igarashi S, Alhumayed M, Kono Y, Loomba R, Wolfson T, Gamst A, Murphy P, Sirlin CB. Longitudinal evolution of CT and MRI LI-RADS v2014 category 1, 2, 3, and 4 observations. Eur Radiol 2019;29:5073-81. [PMID: 30809719 DOI: 10.1007/s00330-019-06058-2] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 2.7] [Reference Citation Analysis]
21 Chernyak V, Fowler KJ, Kamaya A, Kielar AZ, Elsayes KM, Bashir MR, Kono Y, Do RK, Mitchell DG, Singal AG, Tang A, Sirlin CB. Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients. Radiology 2018;289:816-30. [PMID: 30251931 DOI: 10.1148/radiol.2018181494] [Cited by in Crossref: 212] [Cited by in F6Publishing: 196] [Article Influence: 53.0] [Reference Citation Analysis]
22 Esposito A, Buscarino V, Raciti D, Casiraghi E, Manini M, Biondetti P, Forzenigo L. Characterization of liver nodules in patients with chronic liver disease by MRI: performance of the Liver Imaging Reporting and Data System (LI-RADS v.2018) scale and its comparison with the Likert scale. Radiol Med 2020;125:15-23. [PMID: 31587182 DOI: 10.1007/s11547-019-01092-y] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.7] [Reference Citation Analysis]
23 Tang A, Bashir MR, Corwin MT, Cruite I, Dietrich CF, Do RKG, Ehman EC, Fowler KJ, Hussain HK, Jha RC, Karam AR, Mamidipalli A, Marks RM, Mitchell DG, Morgan TA, Ohliger MA, Shah A, Vu KN, Sirlin CB; LI-RADS Evidence Working Group. Evidence Supporting LI-RADS Major Features for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review. Radiology 2018;286:29-48. [PMID: 29166245 DOI: 10.1148/radiol.2017170554] [Cited by in Crossref: 131] [Cited by in F6Publishing: 128] [Article Influence: 26.2] [Reference Citation Analysis]
24 Schellhaas B, Hammon M, Strobel D, Pfeifer L, Kielisch C, Goertz RS, Cavallaro A, Janka R, Neurath MF, Uder M, Seuss H. Interobserver and intermodality agreement of standardized algorithms for non-invasive diagnosis of hepatocellular carcinoma in high-risk patients: CEUS-LI-RADS versus MRI-LI-RADS.Eur Radiol. 2018;28:4254-4264. [PMID: 29675659 DOI: 10.1007/s00330-018-5379-1] [Cited by in Crossref: 32] [Cited by in F6Publishing: 29] [Article Influence: 8.0] [Reference Citation Analysis]
25 Sevim S, Dicle O, Gezer NS, Barış MM, Altay C, Akın IB. How high is the inter-observer reproducibility in the LIRADS reporting system? Pol J Radiol 2019;84:e464-9. [PMID: 31969967 DOI: 10.5114/pjr.2019.90090] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
26 Mendiratta-Lala M, Gu E, Owen D, Cuneo KC, Bazzi L, Lawrence TS, Hussain HK, Davenport MS. Imaging Findings Within the First 12 Months of Hepatocellular Carcinoma Treated With Stereotactic Body Radiation Therapy. Int J Radiat Oncol Biol Phys. 2018;102:1063-1069. [PMID: 29029891 DOI: 10.1016/j.ijrobp.2017.08.022] [Cited by in Crossref: 28] [Cited by in F6Publishing: 22] [Article Influence: 5.6] [Reference Citation Analysis]
27 Kim TH, Woo S, Han S, Suh CH, Do RKG, Lee JM. Risk Factors for Hypervascularization in Hepatobiliary Phase Hypointense Nodules without Arterial Phase Hyperenhancement: A Systematic Review and Meta-analysis. Acad Radiol 2020:S1076-6332(20)30512-2. [PMID: 32962925 DOI: 10.1016/j.acra.2020.08.031] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
28 Horvat N, Nikolovski I, Long N, Gerst S, Zheng J, Pak LM, Simpson A, Zheng J, Capanu M, Jarnagin WR, Mannelli L, Do RKG. Imaging features of hepatocellular carcinoma compared to intrahepatic cholangiocarcinoma and combined tumor on MRI using liver imaging and data system (LI-RADS) version 2014. Abdom Radiol (NY) 2018;43:169-78. [PMID: 28765978 DOI: 10.1007/s00261-017-1261-x] [Cited by in Crossref: 30] [Cited by in F6Publishing: 31] [Article Influence: 10.0] [Reference Citation Analysis]
29 Elsayes KM, Kielar AZ, Elmohr MM, Chernyak V, Masch WR, Furlan A, Marks RM, Cruite I, Fowler KJ, Tang A, Bashir MR, Hecht EM, Kamaya A, Jambhekar K, Kamath A, Arora S, Bijan B, Ash R, Kassam Z, Chaudhry H, McGahan JP, Yacoub JH, McInnes M, Fung AW, Shanbhogue K, Lee J, Deshmukh S, Horvat N, Mitchell DG, Do RKG, Surabhi VR, Szklaruk J, Sirlin CB. White paper of the Society of Abdominal Radiology hepatocellular carcinoma diagnosis disease-focused panel on LI-RADS v2018 for CT and MRI. Abdom Radiol (NY). 2018;43:2625-2642. [PMID: 30155697 DOI: 10.1007/s00261-018-1744-4] [Cited by in Crossref: 31] [Cited by in F6Publishing: 27] [Article Influence: 15.5] [Reference Citation Analysis]
30 Abdel Razek AAK, El-Serougy LG, Saleh GA, Shabana W, Abd El-Wahab R. 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] [Cited by in Crossref: 23] [Cited by in F6Publishing: 12] [Article Influence: 11.5] [Reference Citation Analysis]