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For: Bashir MR, Huang R, Mayes N, Marin D, Berg CL, Nelson RC, Jaffe TA. Concordance of hypervascular liver nodule characterization between the organ procurement and transplant network and liver imaging reporting and data system classifications: LI-RADS vs. OPTN Categorization. J Magn Reson Imaging 2015;42:305-14. [DOI: 10.1002/jmri.24793] [Cited by in Crossref: 38] [Cited by in F6Publishing: 35] [Article Influence: 4.8] [Reference Citation Analysis]
Number Citing Articles
1 Lewis S, Peti S, Hectors SJ, King M, Rosen A, Kamath A, Putra J, Thung S, Taouli B. Volumetric quantitative histogram analysis using diffusion-weighted magnetic resonance imaging to differentiate HCC from other primary liver cancers. Abdom Radiol (NY) 2019;44:912-22. [PMID: 30712136 DOI: 10.1007/s00261-019-01906-7] [Cited by in Crossref: 23] [Cited by in F6Publishing: 19] [Article Influence: 7.7] [Reference Citation Analysis]
2 Abdelrahman AS, Madkour SS, Ekladious MEY. Interrater reliability and agreement of the liver imaging reporting and data system (LI-RADS) v2018 for the evaluation of hepatic lesions. Pol J Radiol 2022;87:e316-24. [PMID: 35892071 DOI: 10.5114/pjr.2022.117590] [Reference Citation Analysis]
3 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: 33] [Cited by in F6Publishing: 32] [Article Influence: 5.5] [Reference Citation Analysis]
4 Burke LM, Sofue K, Alagiyawanna M, Nilmini V, Muir AJ, Choudhury KR, Semelka RC, Bashir MR. Natural history of liver imaging reporting and data system category 4 nodules in MRI. Abdom Radiol (NY) 2016;41:1758-66. [PMID: 27145771 DOI: 10.1007/s00261-016-0762-3] [Cited by in Crossref: 28] [Cited by in F6Publishing: 27] [Article Influence: 4.7] [Reference Citation Analysis]
5 Kim SS, Hwang JA, Shin HC, Choi S, Kang TW, Jou SS, Lee WH, Park S, Heo NH. LI-RADS v2017 categorisation of HCC using CT: Does moderate to severe fatty liver affect accuracy? Eur Radiol 2019;29:186-94. [DOI: 10.1007/s00330-018-5657-y] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 1.8] [Reference Citation Analysis]
6 Chernyak V, Flusberg M, Law A, Kobi M, Paroder V, Rozenblit AM. Liver Imaging Reporting and Data System: Discordance Between Computed Tomography and Gadoxetate-Enhanced Magnetic Resonance Imaging for Detection of Hepatocellular Carcinoma Major Features. Journal of Computer Assisted Tomography 2018;42:155-61. [DOI: 10.1097/rct.0000000000000642] [Cited by in Crossref: 15] [Cited by in F6Publishing: 4] [Article Influence: 3.8] [Reference Citation Analysis]
7 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 DOI: 10.1186/s40644-018-0183-3] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 2.5] [Reference Citation Analysis]
8 Shropshire EL, Chaudhry M, Miller CM, Allen BC, Bozdogan E, Cardona DM, King LY, Janas GL, Do RK, Kim CY, Ronald J, Bashir MR. LI-RADS Treatment Response Algorithm: Performance and Diagnostic Accuracy. Radiology. 2019;292:226-234. [PMID: 31038409 DOI: 10.1148/radiol.2019182135] [Cited by in Crossref: 40] [Cited by in F6Publishing: 34] [Article Influence: 13.3] [Reference Citation Analysis]
9 Tang A, Cruite I, Mitchell DG, Sirlin CB. Hepatocellular carcinoma imaging systems: why they exist, how they have evolved, and how they differ. Abdom Radiol (NY) 2018;43:3-12. [PMID: 28840293 DOI: 10.1007/s00261-017-1292-3] [Cited by in Crossref: 32] [Cited by in F6Publishing: 29] [Article Influence: 8.0] [Reference Citation Analysis]
10 Chernyak V, Kobi M, Flusberg M, Fruitman KC, Sirlin CB. Effect of threshold growth as a major feature on LI-RADS categorization. Abdom Radiol (NY) 2017;42:2089-100. [PMID: 28352950 DOI: 10.1007/s00261-017-1105-8] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis]
11 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]
12 Alhasan A, Cerny M, Olivié D, Billiard JS, Bergeron C, Brown K, Bodson-Clermont P, Castel H, Turcotte S, Perreault P, Tang A. LI-RADS for CT diagnosis of hepatocellular carcinoma: performance of major and ancillary features. Abdom Radiol (NY) 2019;44:517-28. [PMID: 30167771 DOI: 10.1007/s00261-018-1762-2] [Cited by in Crossref: 21] [Cited by in F6Publishing: 15] [Article Influence: 7.0] [Reference Citation Analysis]
13 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: 34] [Cited by in F6Publishing: 35] [Article Influence: 8.5] [Reference Citation Analysis]
14 Dioguardi Burgio M, Picone D, Cabibbo G, Midiri M, Lagalla R, Brancatelli G. MR-imaging features of hepatocellular carcinoma capsule appearance in cirrhotic liver: comparison of gadoxetic acid and gadobenate dimeglumine. Abdom Radiol (NY) 2016;41:1546-54. [PMID: 27052455 DOI: 10.1007/s00261-016-0726-7] [Cited by in Crossref: 36] [Cited by in F6Publishing: 30] [Article Influence: 6.0] [Reference Citation Analysis]
15 Masch WR, Parikh ND, Licari TL, Mendiratta-Lala M, Davenport MS. Radiologist Quality Assurance by Nonradiologists at Tumor Board. J Am Coll Radiol 2018;15:1259-65. [PMID: 29866627 DOI: 10.1016/j.jacr.2018.04.021] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 2.3] [Reference Citation Analysis]
16 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]
17 Ronot M, Fouque O, Esvan M, Lebigot J, Aubé C, Vilgrain V. Comparison of the accuracy of AASLD and LI-RADS criteria for the non-invasive diagnosis of HCC smaller than 3 cm. J Hepatol 2018;68:715-23. [PMID: 29274407 DOI: 10.1016/j.jhep.2017.12.014] [Cited by in Crossref: 51] [Cited by in F6Publishing: 47] [Article Influence: 10.2] [Reference Citation Analysis]
18 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]
19 Hong CW, Hamilton G, Hooker C, Park CC, Tran CA, Henderson WC, Hooker JC, Fazeli Dehkordy S, Schwimmer JB, Reeder SB, Sirlin CB. Measurement of spleen fat on MRI-proton density fat fraction arises from reconstruction of noise. Abdom Radiol (NY) 2019;44:3295-303. [PMID: 31172210 DOI: 10.1007/s00261-019-02079-z] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
20 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]
21 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]
22 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]
23 Cunha GM, Tamayo-Murillo DE, Fowler KJ. LI-RADS and transplantation: challenges and controversies. Abdom Radiol (NY) 2021;46:29-42. [PMID: 31696268 DOI: 10.1007/s00261-019-02311-w] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
24 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]
25 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]
26 Bashir MR, Hussain HK. Imaging in Patients with Cirrhosis. Radiologic Clinics of North America 2015;53:919-31. [DOI: 10.1016/j.rcl.2015.05.006] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.3] [Reference Citation Analysis]
27 Joo I, Lee JM, Lee SM, Lee JS, Park JY, Han JK. Diagnostic accuracy of liver imaging reporting and data system (LI-RADS) v2014 for intrahepatic mass-forming cholangiocarcinomas in patients with chronic liver disease on gadoxetic acid-enhanced MRI. J Magn Reson Imaging. 2016;44:1330-1338. [PMID: 27087012 DOI: 10.1002/jmri.25287] [Cited by in Crossref: 48] [Cited by in F6Publishing: 45] [Article Influence: 8.0] [Reference Citation Analysis]
28 Sofue K, Marin D, Jaffe TA, Nelson RC, Bashir MR. Can combining triple-arterial phase acquisition with fluoroscopic triggering provide both optimal early and late hepatic arterial phase images during gadoxetic acid-enhanced MRI? J Magn Reson Imaging 2016;43:1073-81. [PMID: 26469796 DOI: 10.1002/jmri.25079] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 0.9] [Reference Citation Analysis]
29 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]
30 Sofue K, Sirlin CB, Allen BC, Nelson RC, Berg CL, Bashir MR. How reader perception of capsule affects interpretation of washout in hypervascular liver nodules in patients at risk for hepatocellular carcinoma. J Magn Reson Imaging 2016;43:1337-45. [PMID: 26559157 DOI: 10.1002/jmri.25094] [Cited by in Crossref: 28] [Cited by in F6Publishing: 24] [Article Influence: 4.0] [Reference Citation Analysis]
31 Zhang YD, Zhu FP, Xu X, Wang Q, Wu CJ, Liu XS, Shi HB. Liver Imaging Reporting and Data System:: Substantial Discordance Between CT and MR for Imaging Classification of Hepatic Nodules. Acad Radiol 2016;23:344-52. [PMID: 26777590 DOI: 10.1016/j.acra.2015.11.002] [Cited by in Crossref: 33] [Cited by in F6Publishing: 31] [Article Influence: 5.5] [Reference Citation Analysis]
32 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]
33 Sofue K, Burke LM, Nilmini V, Alagiyawanna M, Muir AJ, Choudhury KR, Jaffe TA, Semelka RC, Bashir MR. Liver imaging reporting and data system category 4 observations in MRI: Risk factors predicting upgrade to category 5: LI-RADS Category 4 Observations in MRI. J Magn Reson Imaging 2017;46:783-92. [DOI: 10.1002/jmri.25627] [Cited by in Crossref: 18] [Cited by in F6Publishing: 18] [Article Influence: 3.6] [Reference Citation Analysis]
34 Allen BC, Ho LM, Jaffe TA, Miller CM, Mazurowski MA, Bashir MR. Comparison of Visualization Rates of LI-RADS Version 2014 Major Features With IV Gadobenate Dimeglumine or Gadoxetate Disodium in Patients at Risk for Hepatocellular Carcinoma. AJR Am J Roentgenol 2018;210:1266-72. [PMID: 29629800 DOI: 10.2214/AJR.17.18981] [Cited by in Crossref: 9] [Cited by in F6Publishing: 4] [Article Influence: 2.3] [Reference Citation Analysis]
35 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]
36 Corwin MT, Lee AY, Fananapazir G, Loehfelm TW, Sarkar S, Sirlin CB. Nonstandardized Terminology to Describe Focal Liver Lesions in Patients at Risk for Hepatocellular Carcinoma: Implications Regarding Clinical Communication. American Journal of Roentgenology 2018;210:85-90. [DOI: 10.2214/ajr.17.18416] [Cited by in Crossref: 15] [Cited by in F6Publishing: 3] [Article Influence: 3.8] [Reference Citation Analysis]
37 Joo I, Lee JM, Lee DH, Ahn SJ, Lee ES, Han JK. Liver imaging reporting and data system v2014 categorization of hepatocellular carcinoma on gadoxetic acid-enhanced MRI: Comparison with multiphasic multidetector computed tomography: LI-RADS for HCCs: Gd-EOB-MRI vs. MDCT. J Magn Reson Imaging 2017;45:731-40. [DOI: 10.1002/jmri.25406] [Cited by in Crossref: 41] [Cited by in F6Publishing: 37] [Article Influence: 6.8] [Reference Citation Analysis]