Gao Shang, Wang Yang, Ma Xihan, Zhou Haoying, Jiang Yiwei, Yang Kehan, Lu Liang, Wang Shiyue, Nephew Benjamin C, Fichera Loris, Fischer Gregory S, Zhang Haichong K
Department of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA 01609, USA.
Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA 01609, USA.
Biomed Opt Express. 2023 Aug 25;14(9):4914-4928. doi: 10.1364/BOE.498052. eCollection 2023 Sep 1.
This paper describes a framework allowing intraoperative photoacoustic (PA) imaging integrated into minimally invasive surgical systems. PA is an emerging imaging modality that combines the high penetration of ultrasound (US) imaging with high optical contrast. With PA imaging, a surgical robot can provide intraoperative neurovascular guidance to the operating physician, alerting them of the presence of vital substrate anatomy invisible to the naked eye, preventing complications such as hemorrhage and paralysis. Our proposed framework is designed to work with the da Vinci surgical system: real-time PA images produced by the framework are superimposed on the endoscopic video feed with an augmented reality overlay, thus enabling intuitive three-dimensional localization of critical anatomy. To evaluate the accuracy of the proposed framework, we first conducted experimental studies in a phantom with known geometry, which revealed a volumetric reconstruction error of 1.20 ± 0.71 mm. We also conducted an study by embedding blood-filled tubes into chicken breast, demonstrating the successful real-time PA-augmented vessel visualization onto the endoscopic view. These results suggest that the proposed framework could provide anatomical and functional feedback to surgeons and it has the potential to be incorporated into robot-assisted minimally invasive surgical procedures.
本文描述了一个将术中光声(PA)成像集成到微创手术系统中的框架。光声成像(PA)是一种新兴的成像方式,它将超声(US)成像的高穿透性与高光学对比度相结合。借助光声成像,手术机器人可以为手术医生提供术中神经血管引导,提醒他们注意肉眼不可见的重要基础解剖结构的存在,防止出血和瘫痪等并发症。我们提出的框架旨在与达芬奇手术系统配合使用:该框架生成的实时光声图像通过增强现实叠加技术叠加在内窥镜视频画面上,从而实现关键解剖结构的直观三维定位。为了评估所提出框架的准确性,我们首先在具有已知几何形状的模型中进行了实验研究,结果显示体积重建误差为1.20±0.71毫米。我们还通过将充满血液的管子嵌入鸡胸进行了一项研究,证明了能够成功地将实时光声增强血管可视化显示在内窥镜视图上。这些结果表明,所提出的框架可以为外科医生提供解剖学和功能反馈,并且有潜力被纳入机器人辅助微创手术过程中。