Augmented reality‐guided positioning system for radiotherapy patients

等中心 医学 仰卧位 放射治疗 校准 头颈部癌 放射科 计算机科学 核医学 医学物理学 外科 数学 统计
作者
Chunying Li,Zhengda Lu,Mu He,Jianfeng Sui,Tao Lin,Kai Xie,Jiawei Sun,Xinye Ni
出处
期刊:Journal of Applied Clinical Medical Physics [Wiley]
卷期号:23 (3): e13516-e13516 被引量:21
标识
DOI:10.1002/acm2.13516
摘要

In modern radiotherapy, error reduction in the patients' daily setup error is important for achieving accuracy. In our study, we proposed a new approach for the development of an assist system for the radiotherapy position setup by using augmented reality (AR). We aimed to improve the accuracy of the position setup of patients undergoing radiotherapy and to evaluate the error of the position setup of patients who were diagnosed with head and neck cancer, and that of patients diagnosed with chest and abdomen cancer. We acquired the patient's simulation CT data for the three-dimensional (3D) reconstruction of the external surface and organs. The AR tracking software detected the calibration module and loaded the 3D virtual model. The calibration module was aligned with the Linac isocenter by using room lasers. And then aligned the virtual cube with the calibration module to complete the calibration of the 3D virtual model and Linac isocenter. Then, the patient position setup was carried out, and point cloud registration was performed between the patient and the 3D virtual model, such the patient's posture was consistent with the 3D virtual model. Twenty patients diagnosed with head and neck cancer and 20 patients diagnosed with chest and abdomen cancer in the supine position setup were analyzed for the residual errors of the conventional laser and AR-guided position setup. Results show that for patients diagnosed with head and neck cancer, the difference between the two positioning methods was not statistically significant (P > 0.05). For patients diagnosed with chest and abdomen cancer, the residual errors of the two positioning methods in the superior and inferior direction and anterior and posterior direction were statistically significant (t = -5.80, -4.98, P < 0.05). The residual errors in the three rotation directions were statistically significant (t = -2.29 to -3.22, P < 0.05). The experimental results showed that the AR technology can effectively assist in the position setup of patients undergoing radiotherapy, significantly reduce the position setup errors in patients diagnosed with chest and abdomen cancer, and improve the accuracy of radiotherapy.

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