PURPOSE: Electromagnetic navigational bronchoscopy(EMNB) is a new technology used to access peripheral lung nodules and mediastinal lymph nodes. Though the bronchoscope is the core component of this procedure, there are many aspects to this technology that may be foreign to even an experienced bronchoscopist. The purpose of this study was to determine whether there was a “learning curve” associated with proficiency in this technology.
METHODS: All patients undergoing diagnostic EMNB for peripheral nodules and/or mediastinal lymph nodes, from September 2004 until October 2006 were included in this analysis. Patients were placed into three successive groups (A, B, or C), based upon the chronological time they had their procedure. Yield was recorded for each patient. A positive yield is defined as either a biopsy with a definitive histologic diagnosis, or a negative biopsy subsequently confirmed by surgical biopsy or stable serial radiographs. A negative yield is defined as the inability to navigate to a nodule or a false negative result.
RESULTS: There were 48 biopsy sites in 43 patients. The average target size was 23mm+/−12mm; there was no significant difference in size between the three groups. Group A had a diagnostic yield of 58.8%; Group B 87.5% and Group C 93.3%. The difference in yield between Groups C and A was statistically significant (p=0.02), as well as the difference between Groups B and A (p=0.05). There was no significant difference between Groups B and C.
CONCLUSION: Using diagnostic yield as a surrogate, there is a learning curve for EMNB. This may be due to several factors, including real-time 3D airway analysis, processing of multi-planar radiographic imaging, and/or incorporation of navigational feedback data into the procedure. These skill sets are unique to this technology, and can result in an initial yield impedance. Our data suggest that once these skill sets are mastered, diagnostic yield improves and remains maximized.
CLINICAL IMPLICATIONS: Awareness that a learning curve exists, and the possible reasons for it, can aide in the creation and optimization of an EMNB program.
DISCLOSURE: Joseph Cicenia, None.