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使用基于有限人群的动脉输入函数对骨肉瘤动态对比增强MRI数据进行药代动力学建模的可行性。

Feasibility of using limited-population-based arterial input function for pharmacokinetic modeling of osteosarcoma dynamic contrast-enhanced MRI data.

作者信息

Wang Ya, Huang Wei, Panicek David M, Schwartz Lawrence H, Koutcher Jason A

机构信息

Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA.

出版信息

Magn Reson Med. 2008 May;59(5):1183-9. doi: 10.1002/mrm.21432.

Abstract

For clinical dynamic contrast-enhanced (DCE) MRI studies, it is often not possible to obtain reliable arterial input function (AIF) in each measurement. Thus, it is important to find a representative AIF for pharmacokinetic modeling of DCE-MRI data when individual AIF (Ind-AIF) measurements are not available. A total of 16 patients with osteosarcomas in the lower extremity (knee region) underwent multislice DCE-MRI. Reliable Ind-AIFs were obtained in five patients with a contrast injection rate of 2 cc/s and another five patients with a 1 cc/s injection rate. Average AIF (Avg-AIF) for each injection rate was constructed from the corresponding five Ind-AIFs. For each injection rate there are no statistically significant differences between pharmacokinetic parameters of the five patients derived with Ind-AIFs and Avg-AIF. There are no statistically significant changes in pharmacokinetic parameters of the 16 patients when the two Avg-AIFs were applied in kinetic modeling. The results suggest that it is feasible, as well as practical, to use a limited-population-based Avg-AIF for pharmacokinetic modeling of osteosarcoma DCE-MRI data. Further validation with a larger population and multiple regions is desirable.

摘要

对于临床动态对比增强(DCE)MRI研究,在每次测量中往往无法获得可靠的动脉输入函数(AIF)。因此,当无法获得个体AIF(Ind-AIF)测量值时,为DCE-MRI数据的药代动力学建模找到一个具有代表性的AIF非常重要。共有16例下肢(膝关节区域)骨肉瘤患者接受了多层DCE-MRI检查。5例以2 cc/s的造影剂注射速率和另外5例以1 cc/s注射速率的患者获得了可靠的Ind-AIF。每种注射速率的平均AIF(Avg-AIF)由相应的5个Ind-AIF构建而成。对于每种注射速率,使用Ind-AIF和Avg-AIF得出的5例患者的药代动力学参数之间无统计学显著差异。当将两种Avg-AIF应用于动力学建模时,16例患者的药代动力学参数无统计学显著变化。结果表明,使用基于有限人群的Avg-AIF对骨肉瘤DCE-MRI数据进行药代动力学建模是可行且实用的。需要更大规模人群和多个区域的进一步验证。

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