Wang Yungang, Zhang Gongsen, Yan Xianrui, Yang Guangjie, Wang Wei, Zhu Jian, Wang Linlin
School of Basic Medicine, Qingdao University, Qingdao, Shandong 266071, P. R. China.
Department of Radiation Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2025 Apr 25;42(2):237-245. doi: 10.7507/1001-5515.202304052.
This paper aims to propose a noninvasive radiotherapy patient positioning system based on structured light surface imaging, and evaluate its clinical feasibility. First, structured light sensors were used to obtain the panoramic point clouds during radiotherapy positioning in real time. The fusion of different point clouds and coordinate transformation were realized based on optical calibration and pose estimation, and the body surface was segmented referring to the preset region of interest (ROI). Then, the global-local registration of cross-source point cloud was achieved based on algorithms such as random sample consensus (RANSAC) and iterative closest point (ICP), to calculate 6 degrees of freedom (DoF) positioning deviation and provide guidance for the correction of couch shifts. The evaluation of the system was carried out based on a rigid adult phantom and volunteers' body, which included positioning error, correlation analysis, and receiver operating characteristic (ROC) analysis. Using Cone Beam CT (CBCT) as the gold standard, the maximum translation and rotation errors of this system were (1.5 ± 0.9) mm along Vrt direction (chest) and (0.7 ± 0.3) ° along Pitch direction (head and neck). The Pearson correlation coefficient between results of system outputs and CBCT verification distributed in an interval of [0.80, 0.84]. Results of ROC analysis showed that the translational and rotational AUC values were 0.82 and 0.85, respectively. In the 4D freedom accuracy test on the human body of volunteers, the maximum translation and rotation errors were (2.6 ± 1.1) mm (Vrt direction, chest and abdomen) and (0.8 ± 0.4)° (Rtn direction, chest and abdomen) respectively. In summary, the positioning system based on structured light body surface imaging proposed in this article can ensure positioning accuracy without surface markers and additional doses, and is feasible for clinical application.
本文旨在提出一种基于结构光表面成像的无创放射治疗患者定位系统，并评估其临床可行性。首先，在放射治疗定位过程中，使用结构光传感器实时获取全景点云。基于光学校准和位姿估计实现不同点云的融合与坐标变换，并参照预设的感兴趣区域（ROI）对体表进行分割。然后，基于随机抽样一致性（RANSAC）和迭代最近点（ICP）等算法实现跨源点云的全局-局部配准，以计算六自由度（DoF）定位偏差并为治疗床移位校正提供指导。基于刚性成人模体和志愿者身体对该系统进行评估，包括定位误差、相关性分析和接收器操作特性（ROC）分析。以锥形束CT（CBCT）作为金标准，该系统在垂直方向（胸部）的最大平移误差和旋转误差分别为（1.5±0.9）mm，在俯仰方向（头部和颈部）为（0.7±0.3）°。系统输出结果与CBCT验证结果之间的皮尔逊相关系数分布在[0.80, 0.84]区间内。ROC分析结果表明，平移和旋转的AUC值分别为0.82和0.85。在志愿者人体的四维自由度精度测试中，最大平移误差和旋转误差分别为（2.6±1.1）mm（垂直方向，胸部和腹部）和（0.8±0.4）°（旋转方向，胸部和腹部）。综上所述，本文提出的基于结构光体表成像的定位系统无需体表标记和额外剂量即可确保定位精度，临床应用可行。
