Virtual bronchoscopic navigation and guided radial endobronchial ultrasound for peripheral pulmonary lesions: harmonizing modalities to optimize accuracy
Peripheral pulmonary lesions (PPLs) present a significant diagnostic challenge due to their location beyond the reach of traditional bronchoscopy. With lung cancer being the leading cause of cancer-related mortality worldwide, accurate and early diagnosis of PPLs is crucial. Virtual bronchoscopic navigation (VBN) combined with radial endobronchial ultrasound (R-EBUS) has emerged as a promising technique to enhance the diagnostic yield for these lesions. This retrospective observational study evaluated the diagnostic yield of VBN-guided R-EBUS in patients with PPLs identified on computed tomography. The study included nine patients who underwent VBN-guided R-EBUS biopsy sampling. Patient demographics, lesion characteristics, and procedural outcomes were analyzed using descriptive and inferential statistics. The mean age of the patients was 57.33 years, with a mean lesion size of 3.24 cm. The diagnostic yield of VBN-guided R-EBUS was 77.7% (95% confidence interval: 68.5-85.8%). Non-small cell carcinoma was the most frequent histopathological diagnosis (55.5%). Complications included bleeding in two patients (22.2%) and bronchospasm in one patient (11.1%), all managed conservatively. VBN-guided R-EBUS provides high diagnostic accuracy and a low risk of complications in patients with PPLs.
Authors
- Sonam Spalgais (ORCID: https://orcid.org/0000-0001-7116-2486)
- Vidushi Rathi (ORCID: https://orcid.org/0000-0003-0432-2624)
- Parul Mrigpuri
- Divyendu Sharma
- Nitin Goel (ORCID: https://orcid.org/0000-0001-5155-8985)
- Sidharth Raj Yadav
- Balakrishnan Menon
- Raj Kumar
Institutions
- University of Delhi (IN)
Publication Details
- Journal
- Monaldi Archives for Chest Disease
- Published
- 2025-01-29
- DOI
- https://doi.org/10.4081/monaldi.2025.3223
- Citations
- 3
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.56