Liver Fat Quantification Using a Multi-Step Adaptive Fitting Approach with Multi-Echo GRE Imaging
Liver Fat Quantification Using a Multi-Step Adaptive Fitting Approach with Multi-Echo GRE Imaging
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DOI：
10.1002/mrm.25054
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发表时间：
2014-11-01
影响因子：
3.3
通讯作者：
Bashir, Mustafa R.
中科院分区：
文献类型：
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作者：
Zhong, Xiaodong;Nickel, Marcel D.;Bashir, Mustafa R.
本研究的目的是开发肝脏质子密度脂肪分数（PDFF）和R-2*定量的多步骤自适应拟合方法，并在广泛可用的硬件平台上进行初步验证。理论与方法该方法采用多回波三维梯度回波采集，根据对所选回波的Dixon分解初步猜测脂肪和水信号分量。基于多峰脂肪谱模型的星等信号方程，进行多步非线性拟合，自适应更新脂肪和水信号分量及R-2*值。所提出的方法使用数字幻影作为基础真理进行了验证，随后在30例患者中对PDFF计算进行了初步临床验证。结果所提出的方法与数值幻象的真实值吻合较好，对场强、场均匀性、单极/双极读数、信噪比和回波时间选择的变化相对不敏感。体内患者研究表明，与光谱学相比，采用该方法测量的PDFF值具有良好的一致性。结论该多步自适应拟合方法在模拟和初步临床评估中均取得了较好的效果，在肝脂肪变性定量诊断中具有一定的应用潜力。中华医学杂志，2014,32(2):563 - 568。(c) 2013 Wiley Periodicals, Inc.；
PurposeThe purpose of this study was to develop a multi-step adaptive fitting approach for liver proton density fat fraction (PDFF) and R-2* quantification, and to perform an initial validation on a broadly available hardware platform.Theory and MethodsThe proposed method uses a multi-echo three-dimensional gradient echo acquisition, with initial guesses for the fat and water signal fractions based on a Dixon decomposition of two selected echoes. Based on magnitude signal equations with a multi-peak fat spectral model, a multi-step nonlinear fitting procedure is then performed to adaptively update the fat and water signal fractions and R-2* values. The proposed method was validated using numeric phantoms as ground truth, followed by preliminary clinical validation of PDFF calculations against spectroscopy in 30 patients.ResultsThe results of the proposed method agreed well with the ground truth of numerical phantoms, and were relatively insensitive to changes in field strength, field homogeneity, monopolar/bipolar readout, signal to noise ratio, and echo time selections. The in vivo patient study showed excellent consistency between the PDFF values measured with the proposed approach compared with spectroscopy.ConclusionThis multi-step adaptive fitting approach performed well in both simulated and initial clinical evaluation, and shows potential in the quantification of hepatic steatosis. Magn Reson Med 72:1353-1365, 2014. (c) 2013 Wiley Periodicals, Inc.