Literature DB >> 24767318

Magnetic resonance fat quantification in living donor liver transplantation.

H-J Chiang1, L-H Lin2, C-W Li3, C-C Lin2, H-W Chiang2, T-L Huang2, C-L Chen4, Y-F Cheng5.   

Abstract

OBJECTIVE: Hepatic steatosis can cause substantial problems for both donors and recipients in living donor liver transplantation (LDLT). The aim of this study is to evaluate the accuracy of the magnetic resonance IDEAL (iterative decomposition of water and fat with echo asymmetry and least squares estimation) sequence in quantifying the liver fat during LDLT.
MATERIALS AND METHODS: A total of 63 liver donors (29 men and 34 women ranging from 18 to 47 years old with a mean age of 30) who received both magnetic resonance imaging (MRI) and intraoperative liver biopsy were enrolled in this study. MR IDEAL IQ sequences were performed by 1.5-T MRI (Discovery 450; GE Healthcare, Milwaukee, Wis, United States) to estimate the liver fatty content. Accuracy was assessed through linear regression between fat fraction image and pathology grading. Sensitivity and specificity of MR IDEAL IQ fat fractions were also calculated.
RESULTS: A total of 63 LDLTs were performed and with pathology grading. No fatty content was found in 48 donors (76.2%; group 1), 5% to 10% fatty liver in 11 donors (17.4%; group 2), 11% to 15% fatty liver in 2 donors (3.2%; group 3), and >16% fatty change in 2 donors (3.2%; group 4). MR IDEAL fat fraction results were excellent in prediction of the normal and fatty content and with good correlation with the pathology grading (2.9 ± 0.9, 8.3 ± 4.2, P < .0001). Linear regression between IDEAL image and pathology grading indicated a high accuracy rate (R(2) = 0.813, R(2) = 0.9286) for all 4 groups. The sensitivity and specificity for detection of liver steatosis in MRI fat fraction image were 100% and 77.1% (P < .0001, 95% confidence interval 0.000-1.000).
CONCLUSION: MR IDEAL IQ sequencing is a highly precise and accurate method in quantifying hepatic steatosis for the living donor.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2014        PMID: 24767318     DOI: 10.1016/j.transproceed.2013.11.050

Source DB:  PubMed          Journal:  Transplant Proc        ISSN: 0041-1345            Impact factor:   1.066


  11 in total

1.  Effect of gadolinium on hepatic fat quantification using multi-echo reconstruction technique with T2* correction and estimation.

Authors:  Mingmei Ge; Jing Zhang; Bing Wu; Zhiqin Liu; Hai Song; Xiangfeng Meng; Xinhuai Wu
Journal:  Eur Radiol       Date:  2015-09-17       Impact factor: 5.315

Review 2.  Adult living donor liver imaging.

Authors:  Larry Cai; Benjamin M Yeh; Antonio C Westphalen; John P Roberts; Zhen J Wang
Journal:  Diagn Interv Radiol       Date:  2016 May-Jun       Impact factor: 2.630

Review 3.  European guideline on obesity care in patients with gastrointestinal and liver diseases - Joint European Society for Clinical Nutrition and Metabolism / United European Gastroenterology guideline.

Authors:  Stephan C Bischoff; Rocco Barazzoni; Luca Busetto; Marjo Campmans-Kuijpers; Vincenzo Cardinale; Irit Chermesh; Ahad Eshraghian; Haluk Tarik Kani; Wafaa Khannoussi; Laurence Lacaze; Miguel Léon-Sanz; Juan M Mendive; Michael W Müller; Johann Ockenga; Frank Tacke; Anders Thorell; Darija Vranesic Bender; Arved Weimann; Cristina Cuerda
Journal:  United European Gastroenterol J       Date:  2022-08-12       Impact factor: 6.866

4.  MRI liver fat quantification in an oncologic population: the added value of complex chemical shift-encoded MRI.

Authors:  Giuseppe Corrias; Simone Krebs; Sarah Eskreis-Winkler; Davinia Ryan; Junting Zheng; Marinela Capanu; Luca Saba; Serena Monti; Maggie Fung; Scott Reeder; Lorenzo Mannelli
Journal:  Clin Imaging       Date:  2018-08-08       Impact factor: 1.605

5.  Diagnostic accuracy of hepatic proton density fat fraction measured by magnetic resonance imaging for the evaluation of liver steatosis with histology as reference standard: a meta-analysis.

Authors:  Yali Qu; Mou Li; Gavin Hamilton; Yingzhen N Zhang; Bin Song
Journal:  Eur Radiol       Date:  2019-03-15       Impact factor: 5.315

6.  Comparison of Multimaterial Decomposition Fat Fraction with DECT and Proton Density Fat Fraction with IDEAL IQ MRI for Quantification of Liver Steatosis in a Population Exposed to Chemotherapy.

Authors:  Giuseppe Corrias; Marco Erta; Marcello Sini; Claudia Sardu; Luca Saba; Usman Mahmood; Sandra Huicochea Castellanos; David Bates; Nicola Mondanelli; Brian Thomsen; Gabriella Carollo; Peter Sawan; Lorenzo Mannelli
Journal:  Dose Response       Date:  2021-04-20       Impact factor: 2.658

7.  Comparative accuracy of CT, dual-echo MRI and MR spectroscopy for preoperative liver fat quantification in living related liver donors.

Authors:  Ruchi Rastogi; Subhash Gupta; Bhavya Garg; Sandeep Vohra; Manav Wadhawan; Harsh Rastogi
Journal:  Indian J Radiol Imaging       Date:  2016 Jan-Mar

Review 8.  Hepatic steatosis and fibrosis: Non-invasive assessment.

Authors:  Rustam N Karanjia; Mary M E Crossey; I Jane Cox; Haddy K S Fye; Ramou Njie; Robert D Goldin; Simon D Taylor-Robinson
Journal:  World J Gastroenterol       Date:  2016-12-07       Impact factor: 5.742

9.  Liver Iron Load Influences Hepatic Fat Fraction in End-Stage Renal Disease Patients on Dialysis: A Proof of Concept Study.

Authors:  Guy Rostoker; Christelle Loridon; Mireille Griuncelli; Clémentine Rabaté; Fanny Lepeytre; Pablo Ureña-Torres; Belkacem Issad; Nasredine Ghali; Yves Cohen
Journal:  EBioMedicine       Date:  2018-11-28       Impact factor: 8.143

10.  Computed Tomography-Based Radiomic Analysis for Preoperatively Predicting the Macrovesicular Steatosis Grade in Cadaveric Donor Liver Transplantation.

Authors:  Shengnan Ding; Weimin Yang; Xiaodong Sun; Yan Guo; Guangjie Zhao; Jinzhu Yang; Lei Zhang; Guoyue Lv
Journal:  Biomed Res Int       Date:  2022-01-22       Impact factor: 3.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.