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Construction and evaluation of a quantitative arterial spin labeling brain perfusion template at 3T

机译:3T时定量动脉旋转脑灌注模板的施工与评价

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Arterial spin labeling (ASL) allows non-invasive imaging and quantification of brain perfusion by magnetically labeling blood in the brain-feeding arteries. ASL has been used to study cerebrovascular diseases, brain tumors and neurodegenerative disorders as well as for functional imaging. The use of a perfusion template could be of great interest to study inter-subject regional variation of perfusion and to perform automatic detection of individual perfusion abnormalities. However, low spatial resolution and partial volume effects (PVE) issues inherent to ASL acquisitions remain to be solved. The purpose of this study is to enhance the template quality by using DARTEL non-rigid registration and by correcting for PVE. PICORE-Q2TIPS ASL datasets were acquired on 25 healthy volunteers at 3T. Four methods of creating the template were evaluated using leave-one-out cross correlation. Subsequently, these methods were applied to hyper-perfusion detection on functional ASL data of 8 healthy volunteers and compared with the standard generalized linear model (GLM) activation detection.
机译:动脉旋转标记(ASL)允许通过脑喂养动脉中的磁标记血液进行非侵入性成像和量化脑灌注。 ASL已被用于研究脑血管疾病,脑肿瘤和神经退行性疾病以及功能性成像。使用灌注模板可能具有很大的兴趣,以研究灌注的受试者间区域变异并进行自动检测单个灌注异常。然而,ASL采集所固有的低空间分辨率和部分体积效应(PVE)仍然是待解决的。本研究的目的是通过使用Dartel非刚性注册和校正PVE来提高模板质量。 Picore-Q2TIPS ASL数据集在3T的25个健康的志愿者上获得。使用休假递交相关性评估创建模板的四种方法。随后,将这些方法应用于8个健康志愿者的功能ASL数据的超灌注检测,并与标准广义线性模型(GLM)激活检测相比。

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