Yan Hui, Dai Jian-Rong
Cancer Hospital Chinese Academy of Medical Sciences.
J Appl Clin Med Phys. 2016 Mar 8;17(2):174-193. doi: 10.1120/jacmp.v17i2.5999.
Digital Tomosynthesis (DTS) is an image modality in reconstructing tomographic images from two-dimensional kV projections covering a narrow scan angles. Comparing with conventional cone-beam CT (CBCT), it requires less time and radiation dose in data acquisition. It is feasible to apply this technique in patient positioning in radiotherapy. To facilitate its clinical application, a software tool was developed and the reconstruction processes were accelerated by graphic process-ing unit (GPU). Two reconstruction and two registration processes are required for DTS application which is different from conventional CBCT application which requires one image reconstruction process and one image registration process. The reconstruction stage consists of productions of two types of DTS. One type of DTS is reconstructed from cone-beam (CB) projections covering a narrow scan angle and is named onboard DTS (ODTS), which represents the real patient position in treatment room. Another type of DTS is reconstructed from digitally reconstructed radiography (DRR) and is named reference DTS (RDTS), which represents the ideal patient position in treatment room. Prior to the reconstruction of RDTS, The DRRs are reconstructed from planning CT using the same acquisition setting of CB projections. The registration stage consists of two matching processes between ODTS and RDTS. The target shift in lateral and longitudinal axes are obtained from the matching between ODTS and RDTS in coronal view, while the target shift in longitudinal and vertical axes are obtained from the matching between ODTS and RDTS in sagittal view. In this software, both DRR and DTS reconstruction algorithms were implemented on GPU environments for acceleration purpose. The comprehensive evaluation of this software tool was performed including geometric accuracy, image quality, registration accuracy, and reconstruction efficiency. The average correlation coefficient between DRR/DTS generated by GPU-based algorithm and CPU-based algorithm is 0.99. Based on the measurements of cube phantom on DTS, the geometric errors are within 0.5 mm in three axes. For both cube phantom and pelvic phantom, the registration errors are within 0.5 mm in three axes. Compared with reconstruction performance of CPU-based algorithms, the performances of DRR and DTS reconstructions are improved by a factor of 15 to 20. A GPU-based software tool was developed for DTS application for patient positioning of radiotherapy. The geometric and registration accuracy met the clinical requirement in patient setup of radiotherapy. The high performance of DRR and DTS reconstruction algorithms was achieved by the GPU-based computation environments. It is a useful software tool for researcher and clinician in evaluating DTS application in patient positioning of radiotherapy.
数字断层合成(DTS)是一种通过覆盖狭窄扫描角度的二维千伏投影重建断层图像的成像方式。与传统锥形束CT(CBCT)相比,它在数据采集时所需时间更少,辐射剂量更低。将该技术应用于放射治疗中的患者定位是可行的。为便于其临床应用,开发了一种软件工具,并通过图形处理单元(GPU)加速重建过程。DTS应用需要两个重建和两个配准过程,这与传统CBCT应用不同,传统CBCT应用需要一个图像重建过程和一个图像配准过程。重建阶段包括生成两种类型的DTS。一种类型的DTS是从覆盖狭窄扫描角度的锥形束(CB)投影重建而来,称为机载DTS(ODTS),它代表治疗室中患者的实际位置。另一种类型的DTS是从数字重建射线照相(DRR)重建而来,称为参考DTS(RDTS),它代表治疗室中患者的理想位置。在重建RDTS之前,使用与CB投影相同的采集设置从计划CT重建DRR。配准阶段包括ODTS和RDTS之间的两个匹配过程。在冠状视图中ODTS和RDTS之间的匹配可获得横向和纵向轴上的目标偏移,而在矢状视图中ODTS和RDTS之间的匹配可获得纵向和垂直轴上的目标偏移。在该软件中,为加速目的,DRR和DTS重建算法均在GPU环境中实现。对该软件工具进行了全面评估,包括几何精度、图像质量、配准精度和重建效率。基于GPU的算法和基于CPU的算法生成的DRR/DTS之间的平均相关系数为0.99。基于在DTS上对立方体模型的测量,三个轴上的几何误差在0.5毫米以内。对于立方体模型和盆腔模型,三个轴上的配准误差均在0.5毫米以内。与基于CPU的算法的重建性能相比,DRR和DTS重建性能提高了15至20倍。开发了一种基于GPU的软件工具用于DTS在放射治疗患者定位中的应用。几何和配准精度满足放射治疗患者摆位的临床要求。基于GPU的计算环境实现了DRR和DTS重建算法的高性能。它是研究人员和临床医生评估DTS在放射治疗患者定位中应用的有用软件工具。