Investigating the regional effect of the chemical shift displacement artefact on the J‐modulated lactate signal at ultra high‐field,NMR in Biomedicine

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Investigating the regional effect of the chemical shift displacement artefact on the J‐modulated lactate signal at ultra high‐field
NMR in Biomedicine ( IF 2.7 ) Pub Date : 2020-11-02 , DOI: 10.1002/nbm.4440
Carolina C Fernandes ₁ , Bernard Lanz ₁ , Chen Chen ₁ , Peter G Morris ₁ , Carlos G Salmon _{1,

2}

Affiliation

The present work aims to show the applicability of an analytical model for the optimisation of the STEAM sequence timing parameters for lactate detection at ultra high‐field. The effects of the chemical shift displacement artefact on the J‐modulated signal for a weakly‐coupled spin system were considered in the three applied directions of field gradients and the product operator formalism was used to obtain expressions for the signal modulation in each compartment of the excited volume. The validity of this model was demonstrated experimentally at 7 T in a phantom and acquisitions with optimised parameters were performed on a healthy volunteer. The spectra acquired with TE = 144 ms with the optimised mixing time and TE = 288 ms showed easily detectable lactate peaks in the normal human brain. Additionally, the acquisition with the longer TE resulted in a spectrum with less lipid/macromolecular contamination. The simulations shown here demonstrated that the proposed analytical model is suitable for correctly predicting the resulting lactate signal. With the optimised parameters, it was possible to use a simple sequence with sufficient signal‐to‐noise ratio to reliably distinguish lactate from overlapping resonances in a healthy brain.

中文翻译：

研究化学位移伪影对超高场 J 调制乳酸信号的区域影响

本工作旨在展示分析模型在优化 STEAM 序列时序参数以在超高场检测乳酸的适用性。在场梯度的三个施加方向上考虑了化学位移位移伪影对弱耦合自旋系统的 J 调制信号的影响，并使用乘积算子形式获得了每个隔室中信号调制的表达式兴奋的音量。该模型的有效性在 7 T 的体模中通过实验证明，并在健康志愿者身上进行了优化参数的采集。TE = 144 ms 和优化混合时间和 TE = 288 ms 获得的光谱显示在正常人脑中容易检测到乳酸峰。此外，使用较长 TE 的采集导致光谱中脂质/大分子污染较少。这里显示的模拟表明，所提出的分析模型适用于正确预测产生的乳酸信号。通过优化参数，可以使用具有足够信噪比的简单序列来可靠地区分乳酸与健康大脑中的重叠共振。

更新日期：2021-01-04

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