Horng Debra E, Hernando Diego, Reeder Scott B
Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.
Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
J Magn Reson Imaging. 2017 Feb;45(2):428-439. doi: 10.1002/jmri.25382. Epub 2016 Jul 13.
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.
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.
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.
Single-R2* modeling enables accurate PDFF quantification, even in patients with iron overload.
1 J. Magn. Reson. Imaging 2017;45:428-439.
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。
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。
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%。
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。
1 J. Magn. Reson. Imaging 2017;45:428 - 439。