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在 1.5T 下评估短 TE 体内 ¹H MRS 数据时模拟和实验基组的比较。

A comparison between simulated and experimental basis sets for assessing short-TE in vivo ¹H MRS data at 1.5 T.

机构信息

Cancer Sciences, University of Birmingham, UK.

出版信息

NMR Biomed. 2010 Dec;23(10):1117-26. doi: 10.1002/nbm.1538. Epub 2010 Oct 15.

Abstract

A number of algorithms designed to determine metabolite concentrations from in vivo (1)H MRS require a collection of single metabolite spectra, known as a basis set, which can be obtained experimentally or by simulation. It has been assumed that basis sets can be used interchangeably, but no systematic study has investigated the effects of small variations in basis functions on the metabolite values obtained. The aim of this study was to compare the results of simulated with experimental basis sets when used to fit short-TE (1)H MRS data of variable quality at 1.5 T. Two hundred and twelve paediatric brain tumour spectra were included in the analysis, and each was analysed twice with LCModel™ using a simulated and experimental basis set. To determine the influence of data quality on quantification, each spectrum was assessed and 152 were classified as being of 'good' quality. Bland-Altman statistics were used to measure the agreement between the two basis sets for all available spectra and only 'good'-quality spectra. Monte-Carlo simulations were performed to investigate the influence of minor shifts in metabolite frequencies on metabolite concentration estimates. All metabolites showed good agreement between the two basis sets, and the average metabolite limits of agreement were approximately ±3.84 mM for all available data and ±0.99 mM for good-quality data. Errors obtained from the Monte-Carlo analysis were found to be more accurate than the Cramer-Rao lower bounds (CRLB) for 12 of 15 metabolites when metabolite frequency shifting was considered. For the majority of purposes, a level of agreement of ±0.99 mM between simulated and experimental basis sets is sufficiently small for them to be used interchangeably. Multiple analyses using slightly modified basis sets may be useful in estimating fitting errors, which are not predicted by CRLBs.

摘要

许多旨在从体内(1)H MRS 确定代谢物浓度的算法都需要一组称为基础集的单代谢物光谱,这些光谱可以通过实验或模拟获得。人们假设基础集可以互换使用,但没有系统的研究调查基础函数的微小变化对获得的代谢物值的影响。本研究的目的是比较在 1.5 T 下使用模拟和实验基础集拟合不同质量短 TE(1)H MRS 数据的结果。共有 212 例儿科脑肿瘤光谱纳入分析,使用 LCModel™ 分别用模拟和实验基础集对其进行了两次分析。为了确定数据质量对定量的影响,对每个光谱进行了评估,其中 152 个被归类为“良好”质量。Bland-Altman 统计用于测量两种基础集之间的一致性,包括所有可用光谱和仅“良好”质量的光谱。Monte-Carlo 模拟用于研究代谢物频率的微小偏移对代谢物浓度估计的影响。两种基础集之间所有代谢物均具有良好的一致性,对于所有可用数据,平均代谢物一致性界限约为 ±3.84 mM,对于高质量数据约为 ±0.99 mM。在考虑代谢物频率偏移的情况下,Monte-Carlo 分析得到的误差比 Cramer-Rao 下限(CRLB)更准确,对于 15 种代谢物中的 12 种情况都是如此。对于大多数目的而言,模拟和实验基础集之间的一致性水平为 ±0.99 mM 足以允许它们互换使用。使用略有修改的基础集进行多次分析可能有助于估计拟合误差,这些误差无法通过 CRLB 预测。

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