Robotic-Assisted Navigation Bronchoscopy as a Paradigm Shift in Peripheral Lung Access
- PMID: 33547938
- DOI: 10.1007/s00408-021-00421-1
Robotic-Assisted Navigation Bronchoscopy as a Paradigm Shift in Peripheral Lung Access
Abstract
Introduction: The sensitivity of suspicious lung nodules biopsied by currently available techniques is suboptimal. Robotic-assisted navigation bronchoscopy (RANB) is a novel method for biopsying lung nodules. Our study objective was to determine the sensitivity for malignancy and overall diagnostic accuracy for RANB when combined with cone beam CT (CBCT) for secondary confirmation.
Methods: 52 consecutive patients were prospectively enrolled. Demographic data, nodule characteristics, procedural information, and follow-up results were obtained.
Results: Mean patient age was 66, with the majority Caucasian (73%) females (65%) with a similar number of never (46%) and former (46%) smokers. 15 patients had a history of cancer and 3 had a prior thoracic surgery. 59 total nodules were included as 7 patients had two nodules biopsied. Mean nodule diameter was < 2 cm in all dimension with the majority solid (41, 70%) and located in the upper lobes (left: 22, 37%; right: 17, 29%). Bronchus sign was absent (32, 54%) or present (27, 46%) in a similar number. All nodules were successfully reached with nine (15%) requiring minor directional changes after initial cone beam CT. A tissue diagnosis was obtained in 83% (49/59) of biopsied nodules, with malignancy (31, 65%) most common. Including all biopsy results and follow-up imaging, we obtained an 84% (31/37) procedural sensitivity for malignancy and an overall 86% (51/59) diagnostic yield.
Conclusion: RANB with CBCT increases sensitivity for malignancy and diagnostic accuracy of lung nodule biopsies. Combining these modalities has the potential to shift the diagnostic approach to pulmonary nodules.
Keywords: Cone beam CT; Lung cancer; Lung nodule; Robotic bronchoscopy.
References
-
- Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Dicker D, et al. (2015) The global burden of cancer 2013 [published correction appears in JAMA Oncol. 1(5):690. Jonas, Jost [corrected to Jonas, Jost B]; Tillman, Taavi [corrected to Tillmann, Taavi]]. JAMA Oncol 1(4):505–527
-
- National Cancer Institute Surveillance (2020) Epidemiology, and end results program. http://seer.cancer.gov/statfacts/html/lungb.html . Accessed 23 June 2020
-
- Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA Cancer J Clin 68(1):7–30 - DOI
-
- Torre LA, Siegel RL, Jemal A (2016) Lung cancer statistics. Adv Exp Med Biol 893:1–19 - DOI
-
- National Lung Screening Trial Research Team, Aberle DR, Adams AM et al (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365(5):395–409 - DOI
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