Robotic-assisted navigation system for preoperative lung nodule localization: a pilot study

Jun Liu; Yu Jiang; Rui He; Fei Cui; Yuechun Lin; Ke Xu; Weipeng Cai; Zhexue Hao; Yuan Zeng; Xiangqian Chen; Hao Zhang; Jipeng Shi; Houiam Cheong; Mengxing Dong; Kaicheng U; Xiaoyan Huang; Shunjun Jiang; Jun Huang; Wei Wang; Hengrui Liang; Xingguang Duan; Jianxing He

doi:10.21037/tlcr-23-493

Robotic-assisted navigation system for preoperative lung nodule localization: a pilot study

Transl Lung Cancer Res. 2023 Nov 30;12(11):2283-2293. doi: 10.21037/tlcr-23-493. Epub 2023 Nov 24.

Authors

Jun Liu^#¹, Yu Jiang^#¹, Rui He^#², Fei Cui^#¹, Yuechun Lin¹, Ke Xu¹, Weipeng Cai¹, Zhexue Hao¹, Yuan Zeng¹, Xiangqian Chen³, Hao Zhang³, Jipeng Shi³, Houiam Cheong³, Mengxing Dong³, Kaicheng U⁴, Xiaoyan Huang⁵, Shunjun Jiang^{1

6}, Jun Huang¹, Wei Wang¹, Hengrui Liang¹, Xingguang Duan², Jianxing He¹

Affiliations

¹ Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
² School of Mechatronical Engineering, Beijing Institute of Technology, Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, China.
³ True Health Medical Technology Co. Ltd., Hengqin, China.
⁴ Cornell University, Ithaca, NY, USA.
⁵ Departments of Radiology, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
⁶ Departments of Pharmacology, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

^# Contributed equally.

Abstract

Background: Preoperative percutaneous computed tomography (CT)-guided localization of pulmonary nodules plays a pivotal role in the diagnosis and treatment of early-stage lung cancer. However, conventional manual localization techniques have inherent limitations in achieving a high degree of accuracy. Consequently, a novel robotic-assisted navigation system was developed to attain precise localization of small lung nodules. This study aims to investigate the accuracy and safety of this system in clinical applications.

Methods: Patients with peripheral solitary pulmonary nodules measuring less than 20 mm were enrolled. The robotic-assisted navigation system generated a three-dimensional (3D) model based on the patient's CT images, determining the optimal puncture path. The robotic arm then accurately located the nodule and, following percutaneous puncture, indocyanine green (ICG) was injected. The primary outcome measure was the accuracy of pulmonary nodule localization, while secondary outcomes included the complication rate, procedural duration, and total radiation exposure.

Results: A total of 33 nodules were successfully localized using the robotic-assisted navigation system and resected through video-assisted thoracoscopic surgery (VATS). The first-pass success rate was 100%, with a median deviation of 6.1 mm [interquartile range (IQR), 2.5-7.2 mm] between the localizer and the nodule. The median localization time was 25.0 minutes, and the single and cumulative exam dose-length products (DLP) were 534.0 and 1491.0 mGy·cm, respectively. Notably, no observable complications were reported during the procedures.

Conclusions: The innovative robotic-assisted navigation system demonstrated satisfactory accuracy and holds promise for improving the percutaneous localization of lung nodules. This method represents a safe and viable alternative to traditional CT-guided manual localization techniques.

Keywords: Robotic-assisted; lung nodule; navigation system; preoperative localization; video-assisted thoracoscopic surgery (VATS).