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首页> 外文期刊>Physics in medicine and biology. >Optimal number of pinholes in multi-pinhole SPECT for mouse brain imaging-a simulation study.
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Optimal number of pinholes in multi-pinhole SPECT for mouse brain imaging-a simulation study.

机译:用于小鼠大脑成像的多针孔SPECT中的最佳针孔数量-模拟研究。

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摘要

This study simulates a multi-pinhole single-photon emission computed tomography (SPECT) system using the Monte Carlo method, and investigates different multi-pinhole designs for quantitative mouse brain imaging. Prior approaches investigating multi-pinhole SPECT were not often optimal, as the number and geometrical arrangement of pinholes were usually chosen empirically. The present study seeks to optimize the number of pinholes for a given pinhole arrangement, and also for the specific application of quantitative neuroreceptor binding in the mouse brain. An analytical Monte Carlo simulation based method was used to generate the projection data for various count levels. A three-dimensional ordered-subsets expectation-maximization algorithm was developed and used to reconstruct the images, incorporating a realistic pinhole model for resolution recovery and noise reduction. Although artefacts arising from overlapping projections could be a major problem in multi-pinhole reconstruction, the cold-rod phantom study showed minimal loss of spatial resolution in multi-pinhole systems, compared to a single-pinhole system with the same pinhole diameter. A quantitative study of neuroreceptor binding sites using a mouse brain phantom and low activity (37 MBq) showed that the multi-pinhole system outperformed the single-pinhole system by maintaining the mean and lowering the variance in the measured uptake ratio. Multi-pinhole collimation can be used to reduce the injected dose and thereby reduce the radiation exposure to the animal. Results also suggest that the nine-pinhole configuration shown in this paper is a good choice for mouse brain imaging.
机译:这项研究使用蒙特卡洛方法模拟了多针孔单光子发射计算机断层扫描(SPECT)系统,并研究了用于定量小鼠大脑成像的不同多针孔设计。研究多针孔SPECT的先前方法通常不是最佳的,因为通常根据经验选择针孔的数量和几何排列。本研究旨在针对给定的针孔排列优化针孔的数量,并针对定量神经受体结合在小鼠大脑中的特定应用。基于分析的蒙特卡洛模拟方法用于生成各种计数级别的投影数据。开发了三维有序子集期望最大化算法,并将其用于重建图像,并结合了现实的针孔模型以实现分辨率恢复和降噪。尽管重叠投影产生的假象可能是多针孔重建中的主要问题,但冷棒幻象研究显示,与具有相同针孔直径的单针孔系统相比,多针孔系统的空间分辨率损失最小。使用小鼠脑部幻影和低活性(37 MBq)进行的神经受体结合位点的定量研究表明,多针孔系统通过保持平均值并降低测得的摄取率方差,优于单针孔系统。可以使用多针孔准直来减少注射剂量,从而减少对动物的辐射暴露。结果还表明,本文显示的九针孔配置是小鼠大脑成像的不错选择。

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