Home /Research /Shape-sensing Robotic-assisted Bronchoscopy (SS-RAB) in Sampling Peripheral Pulmonary Nodules: A Prospective, Multicenter Clinical Feasibility Study in China
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Shape-sensing Robotic-assisted Bronchoscopy (SS-RAB) in Sampling Peripheral Pulmonary Nodules: A Prospective, Multicenter Clinical Feasibility Study in China

Fangfang Xie, Quncheng Zhang, Chuanyong Mu, Qin Zhang, Huizhen Yang, Jingyu Mao, Xiaoju Zhang, Jiayuan Sun

Year
2024
Citations
1

Abstract

<bold>Background:</bold> The ION™ system is a shape-sensing robotic-assisted bronchoscopy platform developed for the diagnosis of peripheral pulmonary nodules (PPNs). However, no study has investigated its use in the Chinese population. The objective of this study was to assess the feasibility and safety of using the ION™ system to diagnose PPNs in Chinese populations. <bold>Methods:</bold> This was a prospective, multicenter study. Patients with PPNs 8 to 30 mm in diameter who met study eligibility criteria underwent ION™ procedure. The primary clinical endpoints were diagnostic yield and procedure- or device-related complications. Radial endobronchial ultrasound (rEBUS) was used to confirm lesion localization. Sampling tools including Flexision transbronchial biopsy needle, biopsy forceps, and cytology brush were used with fluoroscopy to collect samples. <bold>Results:</bold> A total of 90 PPNs from 90 eligible patients were sampled through the ION™ procedure. The median nodule size was 19.4 mm in the largest dimension. The navigation, fluoroscopy, and total procedure time was 3.5 (2.0–11.0), 3.3 (1.9–5.9), and 46.0 (34.0–73.3) min, respectively. The overall diagnostic yield was 87.8%. Nodule location, bronchus sign, and rEBUS view were associated with diagnostic yield in univariate analyses, but only rEBUS view in multivariate analyses. The overall pneumothorax rate was 1.1% and no hemorrhage occurred. <bold>Conclusions:</bold> As a new technology in the Chinese population, the ION™ system can safely biopsy PPNs with a strong diagnostic performance.

Keywords

MedicineBronchoscopyRadiologyMulticenter studyAero enginePeripheralSampling (signal processing)Computer scienceInternal medicineComputer vision

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