Preliminary clinical experience with a robot-assisted system in preoperative hookwire localization of pulmonary nodules: a prospective pilot study
Year: 2025
Type: article
Study design: Clinical Trial
Abstract: Accurate preoperative localization is critical for the surgical resection of small pulmonary nodules, yet conventional CT-guided hookwire placement remains operator-dependent and technically demanding. This prospective study evaluated the clinical performance of a robot-assisted navigation system for CT-guided preoperative hookwire localization of pulmonary nodules. The trial enrolled 60 patients scheduled for localization followed by VATS. Primary endpoints included first-attempt puncture success rate, needle placement accuracy, localization success rate, procedure duration, number of punctures, radiation dose, and complication rate, with subgroup analyses by lesion characteristic and patient positioning. The first-attempt puncture success rate was 100.0%, with an median needle placement accuracy of 5.7 mm (IQR 4.2-7.9). Localization success was achieved in 94.8% of nodules (55/58). The median procedure duration was 16.6 min (14.0-22.9), and the median radiation dose was 281.2 mGy·cm (227.1-365.8). The overall complication rate was 5.2% (3/58). Accuracy was consistent across subgroups, although lower lobe lesions and prone positioning were associated with longer procedure times, and prone positioning also increased radiation exposure, without compromising accuracy. These findings demonstrate the feasibility, precision, and safety of this system, supporting its potential to standardize and improve preoperative localization in thoracic surgery. Trial registration: Registry: https://www.chictr.org.cn/ , TRN: ChiCTR2500095919, Registration date: January 15, 2025.
Source: Journal of Robotic Surgery
Authors: Pengfei Li, Wenheng Zheng, Zheng Wang, Xueling Zhang, Zhuang Tong, Liang Zhang, Hehuan Yao, Chenlei Zhang, Gebang Wang, Yu Liu, Zheyu Liu, Yegang Ma, Weiguo Xie, Bingding Huang, Hongxu Liu
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,090
Award: G7065746366
OpenAlex ID: W4415149772
