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使用二维先验知识拟合的定量J-分辨前列腺波谱分析

Quantitative J-resolved prostate spectroscopy using two-dimensional prior-knowledge fitting.

作者信息

Lange Thomas, Schulte Rolf F, Boesiger Peter

机构信息

Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, Switzerland.

出版信息

Magn Reson Med. 2008 May;59(5):966-72. doi: 10.1002/mrm.21438.

Abstract

Two-dimensional (2D) prior-knowledge fitting (ProFit) was adapted and applied for the quantification of J-resolved (JPRESS) spectra acquired at a field strength of 3T from the human prostate in vivo. In contrast to methods based on simple line fitting and peak integration, commonly applied for metabolite quantification in the prostate, ProFit yields metabolite concentration ratios that are independent of sequence and field strength, since it is based on the linear combination of 2D basis spectra. It is demonstrated that ProFit benefits from the increased information content and reduced baseline distortion in JPRESS prostate spectra, in particular for the quantification of coupled metabolites like citrate (Cit), spermine (Spm), and myo-inositol (mI). The method is validated with 10 repetitive prostate measurements on the same subject. Furthermore, a study carried out on 10 healthy subjects shows that the six prostate metabolites creatine (Cr), total choline (Cho), Cit, Spm, mI, and scyllo-inositol (sI) can be reliably detected in vivo, some of which--especially total Cho and Cit--have proven to be useful markers for the detection of prostate cancer.

摘要

二维(2D)先验知识拟合(ProFit)方法经过调整后,用于对在3T场强下从人体前列腺活体采集的J分辨(JPRESS)谱进行定量分析。与常用于前列腺代谢物定量分析的基于简单谱线拟合和峰积分的方法不同,ProFit得出的代谢物浓度比与序列和场强无关,因为它基于二维基础谱的线性组合。结果表明,ProFit受益于JPRESS前列腺谱中增加的信息含量和减少的基线失真,特别是对于柠檬酸(Cit)、精胺(Spm)和肌醇(mI)等耦合代谢物的定量分析。该方法在同一受试者身上进行了10次重复性前列腺测量验证。此外,对10名健康受试者进行的一项研究表明,六种前列腺代谢物肌酸(Cr)、总胆碱(Cho)、Cit、Spm、mI和异肌醇(sI)能够在活体中可靠检测,其中一些代谢物——尤其是总Cho和Cit——已被证明是检测前列腺癌的有用标志物。

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