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首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >Correcting saturation effects of the arterial input function in dynamic susceptibility contrast-enhanced MRI - a Monte Carlo simulation
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Correcting saturation effects of the arterial input function in dynamic susceptibility contrast-enhanced MRI - a Monte Carlo simulation

机译:校正动态磁化率对比增强MRI中动脉输入功能的饱和效应-蒙特卡洛模拟

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To prevent systematic errors in quantitative brain perfusion studies using dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI), a reliable determination of the arterial input function (AIF) is essential. We propose a novel algorithm for correcting distortions of the AIF caused by saturation of the peak amplitude and discuss its relevance for longitudinal studies. The algorithm is based on the assumption that the AIF can be separated into a reliable part at low contrast agent concentrations and an unreliable part at high concentrations. This unreliable part is reconstructed, applying a theoretical framework based on a transport-diffusion theory and using the bolus-shape in the tissue. A validation of the correction scheme is tested by a Monte Carlo simulation. The input of the simulation was a wide range of perfusion, and the main aim was to compare this input to the determined perfusion parameters. Another input of the simulation was an AIF template derived from in vivo measurements. The distortions of this template was modeled via a Rician distribution for image intensities. As for a real DSC-MRI experiment, the simulation returned the AIF and the tracer concentration-dependent signal in the tissue. The novel correction scheme was tested by deriving perfusion parameters from the simulated data for the corrected and the uncorrected case. For this analysis, a common truncated singular value decomposition approach was applied. We find that the saturation effect caused by Rician-distributed noise leads to an overestimation of regional cerebral blood flow and regional cerebral blood volume, as compared to the input parameter. The aberration can be amplified by a decreasing signal-to-noise ratio (SNR) or an increasing tracer concentration. We also find that the overestimation can be successfully eliminated by the proposed saturation-correction scheme. In summary, the correction scheme will allow DSC-MRI to be expanded towards higher tracer concentrations and lower SNR and will help to increase the measurement to measurement reproducibility for longitudinal studies. (c) 2007 Elsevier Inc. All rights reserved.
机译:为了防止使用动态磁化率对比增强磁共振成像(DSC-MRI)进行定量脑灌注研究的系统性错误,可靠地确定动脉输入功能(AIF)是必不可少的。我们提出了一种新的算法,用于校正由峰值幅度饱和引起的AIF失真,并讨论其与纵向研究的相关性。该算法基于这样的假设:在低造影剂浓度下,AIF可以分为可靠的部分,而在高浓度下,则可以分为不可靠的部分。通过使用基于运输扩散理论的理论框架并使用组织中的团团形状来重建此不可靠的部分。通过蒙特卡洛模拟测试校正方案的有效性。模拟的输入是广泛的灌注,并且主要目的是将输入与确定的灌注参数进行比较。模拟的另一个输入是来自体内测量的AIF模板。该模板的变形通过Rician分布对图像强度进行建模。对于真实的DSC-MRI实验,模拟返回组织中的AIF和示踪剂浓度依赖性信号。通过从模拟数据中获得针对校正和未校正情况的灌注参数来测试新型校正方案。对于此分析,使用了通用的截断奇异值分解方法。我们发现,与输入参数相比,由Rician分布的噪声引起的饱和效应导致对区域脑血流量和区域脑血容量的高估。可以通过降低信噪比(SNR)或增加示踪剂浓度来放大像差。我们还发现,通过提出的饱和度校正方案可以成功消除高估。总而言之,该校正方案将使DSC-MRI扩展到更高的示踪剂浓度和更低的SNR,并将有助于增加纵向研究的测量重复性。 (c)2007 Elsevier Inc.保留所有权利。

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