A robotic system for transthoracic puncture of pulmonary nodules based on gated respiratory compensation

成像体模 医学 计算机科学 计算机视觉 过程(计算) 人工智能 放射科 操作系统
作者
Dongyuan Li,Yuxuan Mao,Puxun Tu,Haochen Shi,Weiyan Sun,Deping Zhao,Chang Chen,Xiaojun Chen,Xiaojun Chen
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier BV]
卷期号:244: 107995-107995 被引量:12
标识
DOI:10.1016/j.cmpb.2023.107995
摘要

With the urgent demands for rapid and precise localization of pulmonary nodules in procedures such as transthoracic puncture biopsy and thoracoscopic surgery, many surgical navigation and robotic systems are applied in the clinical practice of thoracic operation. However, current available positioning methods have certain limitations, including high radiation exposure, large errors from respiratory, complicated and time-consuming procedures, etc. To address these issues, a preoperative computed tomography (CT) image-guided robotic system for transthoracic puncture was proposed in this study. Firstly, an algorithm for puncture path planning based on constraints from clinical knowledge was developed. This algorithm enables the calculation of Pareto optimal solutions for multiple clinical targets concerning puncture angle, puncture length, and distance from hazardous areas. Secondly, to eradicate intraoperative radiation exposure, a fast registration method based on preoperative CT and gated respiration compensation was proposed. The registration process could be completed by the direct selection of points on the skin near the sternum using a hand-held probe. Gating detection and joint optimization algorithms are then performed on the collected point cloud data to compensate for errors from respiratory motion. Thirdly, to enhance accuracy and intraoperative safety, the puncture guide was utilized as an end effector to restrict the movement of the optically tracked needle, then risky actions with patient contact would be strictly limited. The proposed system was evaluated through phantom experiments on our custom-designed simulation test platform for patient respiratory motion to assess its accuracy and feasibility. The results demonstrated an average target point error (TPE) of 2.46±0.68 mm and an angle error (AE) of 1.49±0.45° for the robotic system. In conclusion, our proposed system ensures accuracy, surgical efficiency, and safety while also reducing needle insertions and radiation exposure in transthoracic puncture procedures, thus offering substantial potential for clinical application.
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