Yokoo Takeshi, Serai Suraj D, Pirasteh Ali, Bashir Mustafa R, Hamilton Gavin, Hernando Diego, Hu Houchun H, Hetterich Holger, Kühn Jens-Peter, Kukuk Guido M, Loomba Rohit, Middleton Michael S, Obuchowski Nancy A, Song Ji Soo, Tang An, Wu Xinhuai, Reeder Scott B, Sirlin Claude B
From the Department of Radiology, Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Deptartment of Radiology, Cincinnati Children's Hospital and Medical Center, Cincinnati, Ohio (S.D.S.); Department of Radiology and Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Department of Radiology and Liver Imaging Group, University of California at San Diego, San Diego, Calif (G.H., M.S.M., C.B.S.); Division of Gastroenterology, Department of Medicine, University of California, San Diego, La Jolla, Calif (R.L.); Division of Epidemiology, Department of Family Medicine and Preventive Medicine, University of California, San Diego, La Jolla, Calif (R.L.); Departments of Radiology and Medical Physics, University of Wisconsin, Madison, Wis (D.H., S.B.R.); Biomedical Engineering, Medicine and Emergency Medicine, University of Wisconsin, Madison, Wis (S.B.R.); Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (H.H.H.); Institute of Clinical Radiology, Hospital of the Ludwig-Maximilian University, Munich, Germany (H.H.); Institute of Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany (J.P.K.); Department of Radiology, University Hospital, Carl Gustav Carus University, Dresden, Germany (J.P.K.); Department of Radiology, Rheinische Friedrich-Wilhelms Universität, Bonn, Germany (G.M.K.); Quantitative Health Sciences, The Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Chonbuk National University Medical School and Hospital, Jeonju, Chonbuk, Korea (J.S.S.); Department of Radiology, Université de Montréal, Montréal, QC, Canada (A.T.); and Department of Radiology, Beijing Military General Hospital, Beijing, China (X.W.).
Radiology. 2018 Feb;286(2):486-498. doi: 10.1148/radiol.2017170550. Epub 2017 Sep 11.
Purpose To determine the linearity, bias, and precision of hepatic proton density fat fraction (PDFF) measurements by using magnetic resonance (MR) imaging across different field strengths, imager manufacturers, and reconstruction methods. Materials and Methods This meta-analysis was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic literature search identified studies that evaluated the linearity and/or bias of hepatic PDFF measurements by using MR imaging (hereafter, MR imaging-PDFF) against PDFF measurements by using colocalized MR spectroscopy (hereafter, MR spectroscopy-PDFF) or the precision of MR imaging-PDFF. The quality of each study was evaluated by using the Quality Assessment of Studies of Diagnostic Accuracy 2 tool. De-identified original data sets from the selected studies were pooled. Linearity was evaluated by using linear regression between MR imaging-PDFF and MR spectroscopy-PDFF measurements. Bias, defined as the mean difference between MR imaging-PDFF and MR spectroscopy-PDFF measurements, was evaluated by using Bland-Altman analysis. Precision, defined as the agreement between repeated MR imaging-PDFF measurements, was evaluated by using a linear mixed-effects model, with field strength, imager manufacturer, reconstruction method, and region of interest as random effects. Results Twenty-three studies (1679 participants) were selected for linearity and bias analyses and 11 studies (425 participants) were selected for precision analyses. MR imaging-PDFF was linear with MR spectroscopy-PDFF (R = 0.96). Regression slope (0.97; P < .001) and mean Bland-Altman bias (-0.13%; 95% limits of agreement: -3.95%, 3.40%) indicated minimal underestimation by using MR imaging-PDFF. MR imaging-PDFF was precise at the region-of-interest level, with repeatability and reproducibility coefficients of 2.99% and 4.12%, respectively. Field strength, imager manufacturer, and reconstruction method each had minimal effects on reproducibility. Conclusion MR imaging-PDFF has excellent linearity, bias, and precision across different field strengths, imager manufacturers, and reconstruction methods. RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on October 2, 2017.
目的 通过磁共振（MR）成像，在不同场强、成像仪制造商和重建方法下，确定肝脏质子密度脂肪分数（PDFF）测量的线性、偏差和精密度。材料与方法 本荟萃分析按照系统评价和荟萃分析的首选报告项目指南进行。系统文献检索确定了评估通过MR成像（以下简称MR成像-PDFF）测量肝脏PDFF的线性和/或偏差与通过共定位MR波谱测量的PDFF（以下简称MR波谱-PDFF）的研究，或评估MR成像-PDFF的精密度的研究。使用诊断准确性研究的质量评估2工具评估每项研究的质量。汇总所选研究中去除标识的原始数据集。通过MR成像-PDFF与MR波谱-PDFF测量值之间的线性回归评估线性。偏差定义为MR成像-PDFF与MR波谱-PDFF测量值之间的平均差异，通过Bland-Altman分析进行评估。精密度定义为重复的MR成像-PDFF测量值之间的一致性，通过线性混合效应模型进行评估，将场强、成像仪制造商、重建方法和感兴趣区域作为随机效应。结果 23项研究（1679名参与者）被选用于线性和偏差分析，11项研究（425名参与者）被选用于精密度分析。MR成像-PDFF与MR波谱-PDFF呈线性关系（R = 0.96）。回归斜率（0.97；P <.001）和平均Bland-Altman偏差（-0.13%；95%一致性界限：-3.95%，3.40%）表明使用MR成像-PDFF时低估程度最小。MR成像-PDFF在感兴趣区域水平上具有精密度，重复性和再现性系数分别为2.99%和
4.12%。场强、成像仪制造商和重建方法对再现性的影响均最小。结论 MR成像-PDFF在不同场强、成像仪制造商和重建方法下具有出色的线性、偏差和精密度。RSNA，2017 本文提供在线补充材料。本文的一个早期错误版本已在线发布。本文于2017年10月2日更正。
