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Simultaneous monitoring of PET image resolution, noise, uniformity and quantitative accuracy using uniform cylinder phantom measurements in the multi-center setting

机译:在多中心设置中使用统一的圆柱体幻像测量来同时监控PET图像的分辨率,噪声,均匀性和定量精度

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We have proposed and implemented simultaneous monitoring of image resolution and noise, as well as image uniformity and quantitative accuracy, in a multi-center study of vascular dementia, only utilizing cylinder phantoms. Three centers were enrolled within the ARIC (Atherosclerosis Risk in Communities)-PET study involving amyloid imaging using F-18 Florbetapir. Weekly uniform phantom scans involving ~1mCi of F-18 were conducted for the study duration in each of the three centers. The acquisition protocol consisted of 4×5min frames, consistent with the subject scans (4×5min, 50-70min post-injection). Image resolution was extracted by analyzing the blurring extent of the phantom edges. Specifically, the effective point-spread function (PSF) was obtained by taking the derivative of edges, followed by fitting with a Gaussian function. Noise was extracted by analysis of two back-to-back dynamic images, subtracted from one another, to remove the impact of any spatial non-uniformity, followed by computation of the standard deviation, which was then corrected by sqrt(2) given the difference operation. The phantom was also used to assess uniformity, using ratio of mean uptake within an inner circle to uptake within an outer annulus. Having knowledge of the exact dose, times of injection and scan, as well as phantom volume, enabled measurements of the true concentration, which in turn allowed assessment of quantitative accuracy. Our proposed framework enables feasible and routine multi-center monitoring of image quality, which also allowed us to arrive at a number of interesting observations and conclusions.
机译:我们已经在仅利用圆柱体模的多中心血管性痴呆研究中提出并实施了对图像分辨率和噪声以及图像均匀性和定量准确性的同步监控。三个中心参与了ARIC(社区中的动脉粥样硬化风险)-PET研究,该研究涉及使用F-18 Florbetapir进行淀粉样蛋白成像。在三个中心的每个中心,进行了每周约1mCi的F-18均匀幻像扫描。采集方案由4×5min帧组成,与受试者扫描(4×5min,注射后50-70min)一致。通过分析幻像边缘的模糊程度来提取图像分辨率。具体而言,通过取边的导数,然后拟合高斯函数,可获得有效的点扩展函数(PSF)。通过分析两个背对背的动态图像来提取噪声,并将它们彼此相减,以消除任何空间不均匀性的影响,然后计算标准差,然后通过sqrt(2)校正给定差异运算。体模还用于评估均匀性,方法是使用内圆内的平均摄取量与外圆环内的摄取量之比。了解确切的剂量,注射和扫描的时间以及幻像体积后,就可以测量真实浓度了,从而可以评估定量准确性。我们提出的框架使可行,常规的多中心图像质量监控成为可能,这也使我们得出了许多有趣的观察结果和结论。

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