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磁共振血管造影在灌注成像中用于识别动脉输入函数的应用。

Utilization of MR angiography in perfusion imaging for identifying arterial input function.

作者信息

Buyuksarac Bora, Ozkan Mehmed

机构信息

Institute of Biomedical Engineering, Bogazici University, Kandilli Campus, Üsküdar, 34684, Istanbul, Turkey.

出版信息

MAGMA. 2017 Dec;30(6):609-620. doi: 10.1007/s10334-017-0643-y. Epub 2017 Jul 25.

Abstract

OBJECTIVE

This research utilizes magnetic resonance angiography (MRA) to identify arterial locations during the parametric evaluation of concentration time curves (CTCs), and to prevent shape distortions in arterial input function (AIF).

MATERIALS AND METHODS

We carried out cluster analysis with the CTC parameters of voxels located within and around the middle cerebral artery (MCA). Through MRA, we located voxels that meet the AIF criteria and those with distorted CTCs. To minimize partial volume effect, we re-scaled the time integral of CTCs by the time integral of venous output function (VOF). We calculated the steady-state value to area under curve ratio (SS:AUC) of VOF and used it as a reference in selecting AIF. CTCs close to this reference value (selected AIF) and those far from it were used (eliminated AIF) to compute cerebral blood flow (CBF).

RESULTS

Eliminated AIFs were found to be either on or anterior to MCA, whereas selected AIFs were located superior, inferior, posterior, or anterior to MCA. If the SS:AUC of AIF was far from the reference value, CBF was either under- or over-estimated by a maximum of 41.1 ± 14.3 and 36.6 ± 19.2%, respectively.

CONCLUSION

MRA enables excluding voxels on the MCA during cluster analysis, and avoiding the risk of shape distortions.

摘要

目的

本研究利用磁共振血管造影(MRA)在浓度-时间曲线(CTC)的参数评估过程中识别动脉位置,并防止动脉输入函数(AIF)出现形状扭曲。

材料与方法

我们对位于大脑中动脉(MCA)及其周围的体素的CTC参数进行了聚类分析。通过MRA,我们定位了符合AIF标准的体素以及那些CTC出现扭曲的体素。为了使部分容积效应最小化,我们用静脉输出函数(VOF)的时间积分对CTC的时间积分进行重新缩放。我们计算了VOF的稳态值与曲线下面积之比(SS:AUC),并将其用作选择AIF的参考。接近该参考值(选定的AIF)和远离该参考值的CTC(排除的AIF)用于计算脑血流量(CBF)。

结果

发现排除的AIF位于MCA上或其前方,而选定的AIF位于MCA的上方、下方、后方或前方。如果AIF的SS:AUC远离参考值,则CBF分别被低估或高估,最多可达41.1±14.3%和36.6±19.2%。

结论

MRA能够在聚类分析过程中排除MCA上的体素,并避免形状扭曲的风险。

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