标题： 通过实时容积X射线成像进行三维肿瘤定位用于肺癌放疗 显示英文标题

标题： 3D tumor localization through real-time volumetric x-ray imaging for lung cancer radiotherapy

摘要： 最近，我们开发了一种算法，用于从单个X射线投影中重建体积图像并提取三维肿瘤运动信息。我们使用具有规律呼吸模式的数字呼吸体模验证了其可行性。在本工作中，我们提供了改进算法的详细描述和全面评估。该算法通过结合呼吸运动预测进行了改进。准确性与效率在1）数字呼吸体模，2）物理呼吸体模，以及3）五名肺癌患者身上进行了评估。这些评估案例包括与训练数据集不同的规律和不规律呼吸模式。对于具有规律和不规律呼吸的数字呼吸体模，平均三维肿瘤定位误差小于1毫米。在NVIDIA Tesla C1060 GPU卡上，从每个投影进行三维肿瘤定位的平均计算时间在0.19到0.26秒之间，对于规律和不规律呼吸，这比之前报告的结果提高了约10%。对于物理呼吸体模，在同一GPU卡上，规律和不规律呼吸的平均计算时间分别为0.13秒和0.16秒，平均肿瘤定位误差低于1毫米。对于五名肺癌患者，轴向和切向方向的平均肿瘤定位误差均低于2毫米。在同一GPU卡上的平均计算时间在0.26到0.34秒之间。 显示英文摘要

摘要： Recently we have developed an algorithm for reconstructing volumetric images and extracting 3D tumor motion information from a single x-ray projection. We have demonstrated its feasibility using a digital respiratory phantom with regular breathing patterns. In this work, we present a detailed description and a comprehensive evaluation of the improved algorithm. The algorithm was improved by incorporating respiratory motion prediction. The accuracy and efficiency were then evaluated on 1) a digital respiratory phantom, 2) a physical respiratory phantom, and 3) five lung cancer patients. These evaluation cases include both regular and irregular breathing patterns that are different from the training dataset. For the digital respiratory phantom with regular and irregular breathing, the average 3D tumor localization error is less than 1 mm. On an NVIDIA Tesla C1060 GPU card, the average computation time for 3D tumor localization from each projection ranges between 0.19 and 0.26 seconds, for both regular and irregular breathing, which is about a 10% improvement over previously reported results. For the physical respiratory phantom, an average tumor localization error below 1 mm was achieved with an average computation time of 0.13 and 0.16 seconds on the same GPU card, for regular and irregular breathing, respectively. For the five lung cancer patients, the average tumor localization error is below 2 mm in both the axial and tangential directions. The average computation time on the same GPU card ranges between 0.26 and 0.34 seconds.