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基于化学位移的水/脂分离:信号模型比较。

Chemical shift-based water/fat separation: a comparison of signal models.

机构信息

Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.

出版信息

Magn Reson Med. 2010 Sep;64(3):811-22. doi: 10.1002/mrm.22455.

Abstract

Quantitative water/fat separation in MRI requires careful modeling of the acquired signal. Multiple signal models have been proposed in recent years, but their relative performance has not yet been established. This article presents a comparative study of 12 signal models for quantitative water/fat separation. These models were selected according to three main criteria: magnitude or complex fitting, use of single-peak or multipeak fat spectrum, and modeling of T(2)() decay. The models were compared based on an analysis of the bias and standard deviation of their resulting estimates. Results from theoretical analysis, simulation, phantom experiments, and in vivo data were in good agreement. These results show that (a) complex fitting is uniformly superior to magnitude fitting, (b) multipeak fat modeling is able to remove the bias present in single-peak fat modeling, and (c) a single-T(2)() model performs best over a range of clinically relevant signal-to-noise ratios (SNRs) and water/fat ratios.

摘要

MRI 中的定量水/脂分离需要仔细地对采集信号进行建模。近年来已经提出了多种信号模型,但它们的相对性能尚未确定。本文对 12 种用于定量水/脂分离的信号模型进行了比较研究。这些模型是根据三个主要标准选择的:幅度或复数拟合、使用单峰或多峰脂肪谱以及 T(2)()衰减的建模。基于对其估计结果的偏差和标准差的分析,对模型进行了比较。理论分析、模拟、体模实验和体内数据的结果非常吻合。这些结果表明:(a)复数拟合普遍优于幅度拟合;(b)多峰脂肪建模能够消除单峰脂肪建模中的偏差;(c)在一系列与临床相关的信噪比 (SNR) 和水/脂比范围内,单-T(2)()模型表现最佳。

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