Investigating Partial Registration for Optimizing Robotic-Assisted Bronchoscopy Evaluations of Peripheral Lung Nodules (I-PROBE)
Year: 2025
Type: article
Abstract: Background: Robotic-assisted bronchoscopy has transformed the diagnostic approach to lung cancer by improving access to peripheral pulmonary lesions (PPLs). Among these platforms, shape-sensing robotic-assisted bronchoscopy (ssRAB) relies on registration techniques to align virtual airway maps with patient anatomy. However, conventional full registration may not be essential for optimal accuracy and potentially add unnecessary time. We evaluated the novel technique of partial registration and assessed its feasibility and efficacy during ssRAB. Research Question: During ssRAB, how does partial registration impact the technical accuracy in targeting PPLs compared to full registration? Study Design and Methods: A prospective comparative study was conducted on 22 patients undergoing ssRAB for tissue diagnosis of PPLs < 2 cm in size. The accuracy of lesion localization was determined by the target center distance (TCD), which is the difference between the plan's predicted target center after registration and the intraprocedural cone-beam CT target center. The mean TCD values were calculated for full and partial registration techniques and compared. Results: = .0383). In subgroup analysis, this difference was most noticeable in the posterior lung fields (10.73 vs 6.32 mm) and lower lobes (9.15 vs 6.77 mm). Interpretation: Our results indicate that partial registration offers a feasible and efficient alternative for targeting small PPLs during ssRAB. These findings suggest that the full registration may not be necessary, because partial registration demonstrates comparable lesion localization accuracy-and possibly superior in certain cases. Further research is warranted to confirm these technical advantages and to confirm whether they translate into improved diagnostic outcomes.
Source: CHEST Pulmonary
Authors: Bryce Duchman, Jaskiran K. Khosa, Liqin Xu, Niral M. Patel, Jorge A. Munoz Pineda, Keriann Van Nostrand, Russell J. Miller, Ara A. Chrissian, George Z. Cheng
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
Funder: Intuitive Surgical
OpenAlex ID: W7107857782