Learning curve of a robotic-assisted bronchoscopy system in sampling peripheral pulmonary nodules

Abstract

To the Editor: Computed tomography (CT) has been used for the screening of lung cancer in high-risk populations, with a subsequent reduction in lung cancer-related mortality.[1] However, it has also resulted in a considerable increase in the discovery of peripheral pulmonary nodules (PPNs), which require further diagnosis. Conventional bronchoscopy is used to biopsy lung tissues from the endoluminal route to ensure minimum invasion. However, reaching the periphery of the lung is challenging because of the relatively large diameter of the bronchoscope, which limits the diagnostic value of bronchoscopy for PPNs. Although various advanced bronchoscopic techniques have been developed to improve PPN diagnosis, the pooled diagnostic yield is only 70%,[2] which indicates that diagnostic accuracy can still be improved. Robotic-assisted bronchoscopy systems may be an alternative solution for addressing these limitations. The ION™ system (Intuitive Surgical, Inc., Sunnyvale, CA, USA) is a robotic-assisted bronchoscopy platform that uses shape-sensing technology, which significantly increases the ability to localize and puncture small PPNs.[3] However, few studies have evaluated the use of this system in the Chinese population. A multicenter prospective study was initiated in China and registered on the Chinese Clinical Trial Registry (ChiCTR2100049565) platform to evaluate the feasibility of using the ION™ system in PPN biopsy. The study is still ongoing. Here we report the early results of this study, specifically those obtained via the analysis of the learning curve by a single physician at a single center. The study protocol was approved by the institutional ethics committee of Shanghai Chest Hospital (No. LS2107). All patients participating in the study provided written informed consent. This prospective, single-arm study was conducted at our center between July and October 2021. This study enrolled a total of 30 patients with PPNs with a diameter ranging from 8 to 30 mm that were suspected to be malignant. All ION™ procedures were performed under general anesthesia with endotracheal intubation. A 1.4-mm radial endobronchial ultrasound (r-EBUS) mini probe was used to confirm the location of the nodule. Sampling tools, including the Flexision biopsy needle, biopsy forceps, and cytology brush, were used under fluoroscopy to collect samples. Rapid on-site evaluation was performed using the obtained samples to provide feedback to physicians and determine whether the biopsy could be stopped during the procedure. All patients were examined using fluoroscopy immediately and 1 to 4 hours after the procedure to check for pneumothorax. The total cumulative fluoroscopy time was recorded, including the total fluoroscopy time during the procedure and fluoroscopy examination time immediately after the procedure. The patients were followed up at 10 ± 3 and 30 ± 7 days after the procedure. The samples obtained via the ION™ procedures were subjected to cytological and histopathological assessments. The final diagnosis was made by the physician based on the available information until the last follow-up. The cumulative sum (CUSUM) method was used for the quantitative evaluation of the learning curve based on the operation time,[4] including registration, navigation, and total procedure time. The registration time was defined as the time from the insertion of the catheter to the time when aligning the three-dimensional plan to the patient's anatomy was completed. The navigation time was defined as the time from catheter started from the main trachea to the time when the catheter was parked and ready for r-EBUS or sampling tool insertion. The total procedure time was defined as the time from catheter insertion into the endotracheal tube to catheter removal. The CUSUM learning curve was then fitted, and the fitting model was assessed using P value and R2 coefficient. The value of the X-axis corresponding to the peak of the curve represented the minimum