Department of Radiological Technology, School of Health Sciences, College of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, 920-0942, Japan.
J Radiat Res. 2013 Jan;54(1):146-51. doi: 10.1093/jrr/rrs055. Epub 2012 Jul 22.
Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). It is important to keep the patient dose as low as possible while maintaining tracking accuracy. A simulation approach would be helpful to optimize the imaging conditions. This study was performed to develop a computer simulation platform based on a noise property of the imaging system for the evaluation of tracking accuracy at any noise level. Flat-field images were obtained using a direct-type dynamic FPD, and noise power spectrum (NPS) analysis was performed. The relationship between incident quantum number and pixel value was addressed, and a conversion function was created. The pixel values were converted into a map of quantum number using the conversion function, and the map was then input into the random number generator to simulate image noise. Simulation images were provided at different noise levels by changing the incident quantum numbers. Subsequently, an implanted marker was tracked automatically and the maximum tracking errors were calculated at different noise levels. The results indicated that the maximum tracking error increased with decreasing incident quantum number in flat-field images with an implanted marker. In addition, the range of errors increased with decreasing incident quantum number. The present method could be used to determine the relationship between image noise and tracking accuracy. The results indicated that the simulation approach would aid in determining exposure dose conditions according to the necessary tracking accuracy.
实时肿瘤追踪在外部放射治疗中可以通过诊断（kV）X 射线成像与动态平板探测器（FPD）来实现。在保持跟踪精度的同时，尽量降低患者剂量非常重要。模拟方法将有助于优化成像条件。本研究旨在开发一种基于成像系统噪声特性的计算机模拟平台，用于评估任何噪声水平下的跟踪精度。使用直接型动态 FPD 获得平面场图像，并进行噪声功率谱（NPS）分析。研究了入射量子数与像素值之间的关系，并创建了转换函数。使用转换函数将像素值转换为量子数图，并将该图输入到随机数生成器中以模拟图像噪声。通过改变入射量子数，在不同噪声水平下提供模拟图像。然后，自动跟踪植入的标记，并计算不同噪声水平下的最大跟踪误差。结果表明，在具有植入标记的平面场图像中，最大跟踪误差随入射量子数的减少而增加。此外，误差范围随入射量子数的减少而增加。本方法可用于确定图像噪声与跟踪精度之间的关系。结果表明，模拟方法将有助于根据必要的跟踪精度确定曝光剂量条件。
