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多期伪连续动脉自旋标记(MP-PCASL)用于脑血流的稳健定量。

Multiphase pseudocontinuous arterial spin labeling (MP-PCASL) for robust quantification of cerebral blood flow.

机构信息

Center for Functional MRI and Department of Radiology, University of California San Diego, La Jolla, California 92093, USA.

出版信息

Magn Reson Med. 2010 Sep;64(3):799-810. doi: 10.1002/mrm.22465.

Abstract

Pseudocontinuous arterial spin labeling (PCASL) has been demonstrated to provide the sensitivity of the continuous arterial spin labeling method while overcoming many of the limitations of that method. Because the specification of the phases in the radiofrequency pulse train in PCASL defines the tag and control conditions of the flowing arterial blood, its tagging efficiency is sensitive to factors, such as off-resonance fields, that induce phase mismatches between the radiofrequency pulses and the flowing spins. As a result, the quantitative estimation of cerebral blood flow with PCASL can exhibit a significant amount of error when these factors are not taken into account. In this paper, the sources of the tagging efficiency loss are characterized and a novel PCASL method that utilizes multiple phase offsets is proposed to reduce the tagging efficiency loss in PCASL. Simulations are performed to evaluate the feasibility and the performance of the proposed method. Quantitative estimates of cerebral blood flow obtained with multiple phase offset PCASL are compared to estimates obtained with conventional PCASL and pulsed arterial spin labeling. Our results show that multiple phase offset PCASL provides robust cerebral blood flow quantification while retaining much of the sensitivity advantage of PCASL.

摘要

伪连续动脉自旋标记(PCASL)已被证明提供了连续动脉自旋标记方法的灵敏度,同时克服了该方法的许多限制。由于 PCASL 中射频脉冲序列的相位规范定义了流动动脉血液的标记和控制条件,因此其标记效率对导致射频脉冲与流动自旋之间相位失配的因素(如离共振场)敏感。结果,当这些因素未被考虑时,使用 PCASL 进行脑血流的定量估计可能会出现大量误差。在本文中,对标记效率损失的来源进行了特征描述,并提出了一种利用多个相位偏移的新型 PCASL 方法,以减少 PCASL 中的标记效率损失。进行了模拟以评估所提出方法的可行性和性能。使用多相偏移 PCASL 获得的脑血流量的定量估计与使用常规 PCASL 和脉冲动脉自旋标记获得的估计进行了比较。我们的结果表明,多相偏移 PCASL 提供了稳健的脑血流定量,同时保留了 PCASL 的大部分灵敏度优势。

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