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用于造影剂动脉输入函数估计的多参考组织方法

Multiple reference tissue method for contrast agent arterial input function estimation.

作者信息

Yang Cheng, Karczmar Gregory S, Medved Milica, Stadler Walter M

机构信息

Department of Medicine, University of Chicago, Chicago, Illinois, USA.

出版信息

Magn Reson Med. 2007 Dec;58(6):1266-75. doi: 10.1002/mrm.21311.

Abstract

A precise contrast agent (CA) arterial input function (AIF) is important for accurate quantitative analysis of dynamic contrast-enhanced (DCE)-MRI. This paper proposes a method to estimate the AIF using the dynamic data from multiple reference tissues, assuming that their AIFs have the same shape, with a possible difference in bolus arrival time. By minimizing a cost function, one can simultaneously estimate the parameters and underlying AIF of the reference tissues. The method is computationally efficient and the estimated AIF is smooth and can have higher temporal resolution than the original data. Simulations suggest that this method can provide a reliable estimate of the AIF for DCE-MRI data with a moderate signal-to-noise ratio (SNR) and temporal resolution, and its performance increases significantly as the SNR and temporal resolution increase. As demonstrated by its clinical application, sufficient reference tissues can be easily obtained from normal tissues and subregions segmented from a tumor region of interest (ROI), which suggests this method can be generally applied to cancer-based DCE-MRI studies to estimate the AIF. This method is applicable to general kinetic models in DCE-MRI, as well as other CE imaging modalities.

摘要

精确的对比剂(CA)动脉输入函数(AIF)对于动态对比增强(DCE)-MRI的准确定量分析很重要。本文提出了一种利用来自多个参考组织的动态数据估计AIF的方法,假设它们的AIF具有相同的形状,仅团注到达时间可能存在差异。通过最小化一个代价函数,可以同时估计参考组织的参数和潜在的AIF。该方法计算效率高,估计出的AIF平滑,并且可以具有比原始数据更高的时间分辨率。模拟表明,对于具有中等信噪比(SNR)和时间分辨率的DCE-MRI数据,该方法可以提供可靠的AIF估计,并且随着SNR和时间分辨率的提高,其性能显著提升。临床应用表明,从正常组织和从感兴趣肿瘤区域(ROI)分割出的子区域中可以轻松获得足够的参考组织,这表明该方法通常可应用于基于癌症的DCE-MRI研究以估计AIF。该方法适用于DCE-MRI中的一般动力学模型以及其他对比增强成像模态。

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