Study Results
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Basic Information
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UNKNOWN
150 participants
OBSERVATIONAL
2020-08-01
2022-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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OTHER
PROSPECTIVE
Study Groups
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F0
Normal control group
Quantitative MRI imaging
Dynamic contrast enhanced magnetic resonance imaging,Intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging,Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence
F1
Grade 1 of liver fibrosis
Quantitative MRI imaging
Dynamic contrast enhanced magnetic resonance imaging,Intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging,Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence
F2
Grade 2 of liver fibrosis
Quantitative MRI imaging
Dynamic contrast enhanced magnetic resonance imaging,Intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging,Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence
F3
Grade 3 of liver fibrosis
Quantitative MRI imaging
Dynamic contrast enhanced magnetic resonance imaging,Intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging,Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence
F4
Hepatic cirrhosis
Quantitative MRI imaging
Dynamic contrast enhanced magnetic resonance imaging,Intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging,Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence
Interventions
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Quantitative MRI imaging
Dynamic contrast enhanced magnetic resonance imaging,Intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging,Iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence
Eligibility Criteria
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Inclusion Criteria
1. Fatty liver, liver fibrosis or cirrhosis confirmed by clinical, biochemical, imaging examination and liver biopsy;
2. no secondary portal hypertension and increase alpha feto protein(AFP);
3. no thrombus or plaque in the portal vein and abdominal aorta;
4. no history of psychotropic drug addiction;
5. MRI examination three days before liver puncture or liver transplantation;
6. isolated liver of patients undergoing liver transplantation.
The selection criteria of the normal control group (F0) (meet all the following 1-4 criteria can be selected or only meet the 5 criteria):
1. no known acute or chronic liver disease (serologically negative);
2. no history of alcoholism, and normal liver function tests;
3. no signs of chronic liver disease in CT or MRI;
4. no CT or MRI manifestations of focal or diffuse liver disease in the liver;
5. abandoned donor liver
Exclusion Criteria
2. allergy to contrast media and poor image quality can not meet the needs of clinical diagnosis;
3. less than 18 years of age, poor quality of liver biopsy;
4. renal insufficiency (eGFP \< 60ml/min/1.73mm2);
5. with severe heart, brain, lung and blood system diseases.
6. liver complicated with fulminant liver failure and gastrointestinal bleeding.
18 Years
75 Years
ALL
Yes
Sponsors
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Fifth Affiliated Hospital, Sun Yat-Sen University
OTHER
Responsible Party
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ShaoLin Li
Director of Radiology Department
Principal Investigators
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Shaolin Li, Director
Role: PRINCIPAL_INVESTIGATOR
Radiology Department,the Fifth Affiliated Hospital of Sun Yat-sen University
Locations
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52 Meihua East Road, New Xiangzhou
Zhuhai, Guangdong, China
Countries
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Central Contacts
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Facility Contacts
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References
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Fan JG, Kim SU, Wong VW. New trends on obesity and NAFLD in Asia. J Hepatol. 2017 Oct;67(4):862-873. doi: 10.1016/j.jhep.2017.06.003. Epub 2017 Jun 19.
Sheka AC, Adeyi O, Thompson J, Hameed B, Crawford PA, Ikramuddin S. Nonalcoholic Steatohepatitis: A Review. JAMA. 2020 Mar 24;323(12):1175-1183. doi: 10.1001/jama.2020.2298.
Younossi ZM, Stepanova M, Afendy M, Fang Y, Younossi Y, Mir H, Srishord M. Changes in the prevalence of the most common causes of chronic liver diseases in the United States from 1988 to 2008. Clin Gastroenterol Hepatol. 2011 Jun;9(6):524-530.e1; quiz e60. doi: 10.1016/j.cgh.2011.03.020. Epub 2011 Mar 25.
Poynard T, Lenaour G, Vaillant JC, Capron F, Munteanu M, Eyraud D, Ngo Y, M'Kada H, Ratziu V, Hannoun L, Charlotte F. Liver biopsy analysis has a low level of performance for diagnosis of intermediate stages of fibrosis. Clin Gastroenterol Hepatol. 2012 Jun;10(6):657-63.e7. doi: 10.1016/j.cgh.2012.01.023. Epub 2012 Feb 14.
Dong XQ, Wu Z, Zhao H, Wang GQ; China HepB-Related Fibrosis Assessment Research Group. Evaluation and comparison of thirty noninvasive models for diagnosing liver fibrosis in chinese hepatitis B patients. J Viral Hepat. 2019 Feb;26(2):297-307. doi: 10.1111/jvh.13031. Epub 2018 Nov 28.
Wai CT, Greenson JK, Fontana RJ, Kalbfleisch JD, Marrero JA, Conjeevaram HS, Lok AS. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology. 2003 Aug;38(2):518-26. doi: 10.1053/jhep.2003.50346.
Thiele M, Detlefsen S, Sevelsted Moller L, Madsen BS, Fuglsang Hansen J, Fialla AD, Trebicka J, Krag A. Transient and 2-Dimensional Shear-Wave Elastography Provide Comparable Assessment of Alcoholic Liver Fibrosis and Cirrhosis. Gastroenterology. 2016 Jan;150(1):123-33. doi: 10.1053/j.gastro.2015.09.040. Epub 2015 Oct 3.
Wu S, Yang Z, Zhou J, Zeng N, He Z, Zhan S, Jia J, You H. Systematic review: diagnostic accuracy of non-invasive tests for staging liver fibrosis in autoimmune hepatitis. Hepatol Int. 2019 Jan;13(1):91-101. doi: 10.1007/s12072-018-9907-5. Epub 2018 Nov 15.
Zhang YN, Fowler KJ, Hamilton G, Cui JY, Sy EZ, Balanay M, Hooker JC, Szeverenyi N, Sirlin CB. Liver fat imaging-a clinical overview of ultrasound, CT, and MR imaging. Br J Radiol. 2018 Sep;91(1089):20170959. doi: 10.1259/bjr.20170959. Epub 2018 Jun 6.
Singh S, Venkatesh SK, Wang Z, Miller FH, Motosugi U, Low RN, Hassanein T, Asbach P, Godfrey EM, Yin M, Chen J, Keaveny AP, Bridges M, Bohte A, Murad MH, Lomas DJ, Talwalkar JA, Ehman RL. Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data. Clin Gastroenterol Hepatol. 2015 Mar;13(3):440-451.e6. doi: 10.1016/j.cgh.2014.09.046. Epub 2014 Nov 20.
Li Z, Sun J, Chen L, Huang N, Hu P, Hu X, Han G, Zhou Y, Bai W, Niu T, Yang X. Assessment of liver fibrosis using pharmacokinetic parameters of dynamic contrast-enhanced magnetic resonance imaging. J Magn Reson Imaging. 2016 Jul;44(1):98-104. doi: 10.1002/jmri.25132. Epub 2015 Dec 28.
Wu CH, Ho MC, Jeng YM, Liang PC, Hu RH, Lai HS, Shih TT. Assessing hepatic fibrosis: comparing the intravoxel incoherent motion in MRI with acoustic radiation force impulse imaging in US. Eur Radiol. 2015 Dec;25(12):3552-9. doi: 10.1007/s00330-015-3774-4. Epub 2015 May 20.
Li J, Liu H, Zhang C, Yang S, Wang Y, Chen W, Li X, Wang D. Native T1 mapping compared to ultrasound elastography for staging and monitoring liver fibrosis: an animal study of repeatability, reproducibility, and accuracy. Eur Radiol. 2020 Jan;30(1):337-345. doi: 10.1007/s00330-019-06335-0. Epub 2019 Jul 23.
Hoffman DH, Ayoola A, Nickel D, Han F, Chandarana H, Shanbhogue KP. T1 mapping, T2 mapping and MR elastography of the liver for detection and staging of liver fibrosis. Abdom Radiol (NY). 2020 Mar;45(3):692-700. doi: 10.1007/s00261-019-02382-9.
Loomba R, Neuschwander-Tetri BA, Sanyal A, Chalasani N, Diehl AM, Terrault N, Kowdley K, Dasarathy S, Kleiner D, Behling C, Lavine J, Van Natta M, Middleton M, Tonascia J, Sirlin C; NASH Clinical Research Network. Multicenter Validation of Association Between Decline in MRI-PDFF and Histologic Response in NASH. Hepatology. 2020 Oct;72(4):1219-1229. doi: 10.1002/hep.31121. Epub 2020 Oct 9.
Other Identifiers
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ZDWY.FSK.005
Identifier Type: -
Identifier Source: org_study_id
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