First European Experience of Shape-Sensing Robotic-Assisted Bronchoscopy: Learning Curve Analysis

Science and Research

INTRODUCTION: Shape-sensing robotic-assisted bronchoscopy (ssRAB) is an emerging approach in Europe to diagnose peripheral pulmonary nodules (PPNs). There are limited data on how quickly this new technology can be learned. METHODS: This study presents a post hoc analysis of learning curves from a single-center prospective study in which PPN were diagnosed by ssRAB combined with standalone (nonintegrated) mobile cone-beam computed tomography (mCBCT) by two experienced proceduralists both nascent to ssRAB and mCBCT. All sections of procedure times, number of mCBCT spins, and tool-in-lesion (TIL) were assessed by cumulative sum (CUSUM) analysis. RESULTS: A total of 45 patients were included in the study with biopsies attempted in 40 subjects (n = 17 proceduralist 1, n = 23 proceduralist 2), with a median (IQR) nodule size of 20.0 (17.0, 24.0) mm. Median procedure time improved for both proceduralists after case 6. Navigation time showed no learning pattern, while there were different learning patterns for parts of the procedure for both proceduralists. Proceduralist 1 had statistically significantly shorter procedure times compared to proceduralist 2, mostly due to more biopsies taken from proceduralist 2. Both proceduralists were able to obtain TIL confirmed by mCBCT from the first case and demonstrated proficiency after 8 cases. CONCLUSION: Competence in ssRAB can be achieved quickly, and procedure times decrease after a few cases. However, as learning curves vary between proceduralists, a sufficient number of cases should be considered to achieve ssRAB proficiency. Not all learning parameters, such as anesthetic or endoscopic staff learning, can be represented in statistical analyses.