Suppr超能文献

铁过载情况下肝脏脂肪的定量分析。

Quantification of liver fat in the presence of iron overload.

作者信息

Horng Debra E, Hernando Diego, Reeder Scott B

机构信息

Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.

Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.

出版信息

J Magn Reson Imaging. 2017 Feb;45(2):428-439. doi: 10.1002/jmri.25382. Epub 2016 Jul 13.

Abstract

PURPOSE

To evaluate the accuracy of R2* models (1/T * = R2*) for chemical shift-encoded magnetic resonance imaging (CSE-MRI)-based proton density fat-fraction (PDFF) quantification in patients with fatty liver and iron overload, using MR spectroscopy (MRS) as the reference standard.

MATERIALS AND METHODS

Two Monte Carlo simulations were implemented to compare the root-mean-squared-error (RMSE) performance of single-R2* and dual-R2* correction in a theoretical liver environment with high iron. Fatty liver was defined as hepatic PDFF >5.6% based on MRS; only subjects with fatty liver were considered for analyses involving fat. From a group of 40 patients with known/suspected iron overload, nine patients were identified at 1.5T, and 13 at 3.0T with fatty liver. MRS linewidth measurements were used to estimate R2* values for water and fat peaks. PDFF was measured from CSE-MRI data using single-R2* and dual-R2* correction with magnitude and complex fitting.

RESULTS

Spectroscopy-based R2* analysis demonstrated that the R2* of water and fat remain close in value, both increasing as iron overload increases: linear regression between R2* and R2* resulted in slope = 0.95 [0.79-1.12] (95% limits of agreement) at 1.5T and slope = 0.76 [0.49-1.03] at 3.0T. MRI-PDFF using dual-R2* correction had severe artifacts. MRI-PDFF using single-R2* correction had good agreement with MRS-PDFF: Bland-Altman analysis resulted in -0.7% (bias) ± 2.9% (95% limits of agreement) for magnitude-fit and -1.3% ± 4.3% for complex-fit at 1.5T, and -1.5% ± 8.4% for magnitude-fit and -2.2% ± 9.6% for complex-fit at 3.0T.

CONCLUSION

Single-R2* modeling enables accurate PDFF quantification, even in patients with iron overload.

LEVEL OF EVIDENCE

1 J. Magn. Reson. Imaging 2017;45:428-439.

摘要

目的

以磁共振波谱(MRS)作为参考标准,评估基于化学位移编码磁共振成像(CSE-MRI)的质子密度脂肪分数(PDFF)定量分析中R2模型(1/T = R2*)在脂肪肝和铁过载患者中的准确性。

材料与方法

进行了两次蒙特卡洛模拟,以比较在高铁含量的理论肝脏环境中,单R2校正和双R2校正的均方根误差(RMSE)性能。基于MRS,将脂肪肝定义为肝脏PDFF>5.6%;仅纳入患有脂肪肝的受试者进行涉及脂肪的分析。在一组40例已知/疑似铁过载的患者中,1.5T时识别出9例脂肪肝患者,3.0T时识别出13例脂肪肝患者。使用MRS线宽测量来估计水峰和脂肪峰的R2值。使用单R2校正和双R2*校正,通过幅度拟合和复数拟合从CSE-MRI数据中测量PDFF。

结果

基于波谱的R2分析表明,水和脂肪的R2值相近,且随着铁过载的增加两者均升高:R2与R2之间的线性回归在1.5T时斜率 = 0.95 [0.79 - 1.12](95%一致性界限),在3.0T时斜率 = 0.76 [0.49 - 1.03]。使用双R2校正的MRI-PDFF有严重伪影。使用单R2校正的MRI-PDFF与MRS-PDFF有良好的一致性:Bland-Altman分析在1.5T时幅度拟合的偏差为 -0.7% ± 2.9%(95%一致性界限),复数拟合为 -1.3% ± 4.3%;在3.0T时幅度拟合的偏差为 -1.5% ± 8.4%,复数拟合为 -2.2% ± 9.6%。

结论

即使在铁过载患者中,单R2*建模也能实现准确的PDFF定量分析。

证据水平

1 J. Magn. Reson. Imaging 2017;45:428 - 439。

相似文献

1
Quantification of liver fat in the presence of iron overload.
J Magn Reson Imaging. 2017 Feb;45(2):428-439. doi: 10.1002/jmri.25382. Epub 2016 Jul 13.
2
Accurate simultaneous quantification of liver steatosis and iron overload in diffuse liver diseases with MRI.
Abdom Radiol (NY). 2017 May;42(5):1434-1443. doi: 10.1007/s00261-017-1048-0.
3
Standardized Approach for ROI-Based Measurements of Proton Density Fat Fraction and R2* in the Liver.
AJR Am J Roentgenol. 2017 Sep;209(3):592-603. doi: 10.2214/AJR.17.17812. Epub 2017 Jul 13.
6
Validation of a motion-robust 2D sequential technique for quantification of hepatic proton density fat fraction during free breathing.
J Magn Reson Imaging. 2018 Dec;48(6):1578-1585. doi: 10.1002/jmri.26056. Epub 2018 Apr 17.
7
Cross-sectional correlation between hepatic R2* and proton density fat fraction (PDFF) in children with hepatic steatosis.
J Magn Reson Imaging. 2018 Feb;47(2):418-424. doi: 10.1002/jmri.25748. Epub 2017 May 25.
9
Comparison of R2* correction methods for accurate fat quantification in fatty liver.
J Magn Reson Imaging. 2013 Feb;37(2):414-22. doi: 10.1002/jmri.23835. Epub 2012 Nov 16.

引用本文的文献

3
Whole liver phase-based R2 mapping in liver iron overload within a breath-hold.
Magn Reson Med. 2025 Jul;94(1):183-198. doi: 10.1002/mrm.30461. Epub 2025 Feb 18.
5
Differential association of abdominal, liver, and epicardial adiposity with anthropometry, diabetes, and cardiac remodeling in Asians.
Front Endocrinol (Lausanne). 2024 Aug 23;15:1439691. doi: 10.3389/fendo.2024.1439691. eCollection 2024.
6
Effect of particle size on liver MRI relaxometry: Monte Carlo simulation and phantom studies.
Magn Reson Med. 2024 Oct;92(4):1743-1754. doi: 10.1002/mrm.30154. Epub 2024 May 9.
10
Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease.
Magn Reson Med Sci. 2023 Oct 1;22(4):435-445. doi: 10.2463/mrms.rev.2021-0152. Epub 2022 May 18.

本文引用的文献

1
Modeling of T2* decay in vertebral bone marrow fat quantification.
NMR Biomed. 2015 Nov;28(11):1535-42. doi: 10.1002/nbm.3420. Epub 2015 Oct 1.
2
Proton density fat-fraction is an accurate biomarker of hepatic steatosis in adolescent girls and young women.
Eur Radiol. 2015 Oct;25(10):2921-30. doi: 10.1007/s00330-015-3724-1. Epub 2015 Apr 28.
3
Sensitivity of chemical shift-encoded fat quantification to calibration of fat MR spectrum.
Magn Reson Med. 2016 Feb;75(2):845-51. doi: 10.1002/mrm.25681. Epub 2015 Apr 4.
4
Dysregulation of iron and copper homeostasis in nonalcoholic fatty liver.
World J Hepatol. 2015 Feb 27;7(2):177-88. doi: 10.4254/wjh.v7.i2.177.
7
Relaxivity-iron calibration in hepatic iron overload: Predictions of a Monte Carlo model.
Magn Reson Med. 2015 Sep;74(3):879-83. doi: 10.1002/mrm.25459. Epub 2014 Sep 19.
8
Fat and iron quantification in the liver: past, present, and future.
Top Magn Reson Imaging. 2014 Apr;23(2):73-94. doi: 10.1097/RMR.0000000000000016.
9
Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging.
Magn Reson Med. 2014 Nov;72(5):1353-65. doi: 10.1002/mrm.25054. Epub 2013 Dec 9.
10
Quantitative chemical shift-encoded MRI is an accurate method to quantify hepatic steatosis.
J Magn Reson Imaging. 2014 Jun;39(6):1494-501. doi: 10.1002/jmri.24289. Epub 2013 Oct 10.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验