Optimization strategies for evaluation of brain hemodynamic parameters with qBOLD technique.
Optimization strategies for evaluation of brain hemodynamic parameters with qBOLD technique.
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DOI：
10.1002/mrm.24338
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发表时间：
2013-04
影响因子：
3.3
通讯作者：
Yablonskiy, Dmitriy A.
中科院分区：
文献类型：
--
作者：
Wang, Xiaoqi;Sukstanskii, Alexander L.;Yablonskiy, Dmitriy A.
qBOLD（定量血氧水平依赖）技术提供了一种基于MRI的方法，用于测量组织血液动力学参数，如氧提取分数（OEF）和含脱氧血红蛋白（静脉和毛细血管前部分）的脑血容量分数（dCBV）。它是基于在血管网络和实验方法的存在下的MR信号移相的理论-自旋回波的梯度回波采样（GESSE）先前提出和验证的幻影和动物。人体体内研究也证明了这种方法的可行性，但也认识到，获得可靠的结果需要高信噪比的数据。在本文中，我们详细分析的qBOLD参数估计的贝叶斯概率理论的框架下，即，我们研究如何估计参数OEF和dCBV取决于他们的“真值”，信噪比，和数据采样策略的不确定性。基于这一分析，我们制定了优化qBOLD技术用于dCBV和OEF评价的策略。特别是，它表明，使用GESSE序列允许大幅减少测量误差，因为数据采集的自旋回波的两侧。我们在模拟血管网络结构的体模上验证了我们的理论。3D GESSE脉冲序列用于采集随后由贝叶斯应用软件分析的MRI信号。实验结果与理论预测吻合较好。
qBOLD (quantitative Blood Oxygenation Level Depend) technique provides an MRI-based method to measure tissue hemodynamic parameters such as oxygen extraction fraction (OEF) and deoxyhemoglobin-containing (veins and pre-vinous part of capillaries) cerebral blood volume fraction (dCBV). It is based on a theory of MR signal dephasing in the presence of blood vessel network and experimental method – Gradient Echo Sampling of Spin Echo (GESSE) previously proposed and validated on phantoms and animals. In vivo human studies also demonstrated feasibility of this approach but also recognized that obtaining reliable results requires high SNR in the data. In the present paper, we analyze in detail the uncertainties of the qBOLD parameter estimates in the framework of the Bayesian probability theory, namely, we examine how the estimated parameters OEF and dCBV depend on their “true values”, signal-to-noise ratio, and data sampling strategies. Based on this analysis we develop strategies for optimization of the qBOLD technique for dCBV and OEF evaluation. In particular, it is demonstrated that the use of GESSE sequence allows substantial decrease of measurement errors as the data are acquired on both sides of spin echo. We test our theory on phantom mimicking the structure of blood vessel network. A 3D GESSE pulse sequence is used for the acquisition of the MRI signal that was subsequently analyzed by Bayesian Application Software. The experimental results demonstrated a good agreement with theoretical predictions.
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DOI：
10.1124/jpet.112.192138
发表时间：
2012-09-01
影响因子：
3.5
作者：
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影响因子：
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DOI：
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发表时间：
2001-01-16
影响因子：
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作者：
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