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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均匀气缸幻像测量来同时监测PET图像分辨率,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:我们提出并实施了同时监测图像分辨率和噪声,以及图像均匀性和定量准确性,在血管痴呆的多中心研究中,仅利用汽缸幽灵。三个中心在ARIC(社区的动脉粥样硬化风险)内注册 - 涉及使用F-18抗血管造成的淀粉样品成像的PATE的研究。每周均匀的幻影扫描〜1mci的F-18进行了三个中心的研究持续时间。采集协议由4×5min框架组成,与主题扫描(4×5min,注射后50-70min)一致。通过分析幻影边缘的模糊程度来提取图像分辨率。具体地,通过采用边缘的衍生物来获得有效点扩散功能(PSF),然后用高斯函数拟合。通过分析两个背对背动态图像来提取噪声,彼此减去,以消除任何空间不均匀性的影响,然后计算标准偏差,然后通过SQRT(2)校正差异操作。使用内圈内的平均圆内的平均摄取的比例来评估幽灵来评估均匀性。知识了解确切的剂量,注射和扫描的时间,以及幽灵体积,使能真正浓度的测量,这反过来允许评估定量精度。我们所提出的框架可以实现可行和常规的图像质量的多中心监测,这也使我们能够达到一些有趣的观察和结论。

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