Abstract Rationale Supraclavicular lymph node (SCLN) fine-needle aspiration (FNA) can provide a minimally invasive route for tissue diagnosis and staging in patients with suspected malignancy. This procedure is traditionally performed by interventional radiologists, but it may be safely incorporated into pulmonary practice as part of lung cancer evaluation. We aimed to describe our initial experience with pulmonologist-performed ultrasound (US)-guided FNA of SCLN and axillary lymph nodes. Methods We retrospectively reviewed nine consecutive cases of US-guided FNA of SCLN or axillary lymph nodes performed by a pulmonologist at a single Veterans Affairs Medical Center between 2022 and 2025. Data collected included patient demographics, comorbidities, indication, node characteristics, procedural details, cytologic diagnosis, complications, and downstream clinical impact. Rapid on-site cytologic evaluation (ROSE) and final cytology were recorded. Descriptive statistics were used. Results Nine male patients (median age 73 years, range 66-83) underwent US-guided FNA; 78% were current or former smokers, and 67% were outpatients. Median node size was 20.9 mm (range 5-60 mm). All procedures were technically successful with no immediate complications. Adequate cytology was obtained in all nine cases (100% adequacy). Eight (89%) revealed malignancy, including non-small cell lung carcinoma (3), small cell carcinoma (2), colon adenocarcinoma (2), and melanoma (1). Six patients (67%) had stage IV disease. Use of this approach avoided additional invasive procedures (EBUS or robotic bronchoscopy) in all diagnostic cases. Median time from imaging to diagnosis was 7 days, and median time from biopsy to treatment decision was 7 days. Conclusions Pulmonologist-performed US-guided FNA of supraclavicular and axillary lymph nodes is feasible, safe, and highly diagnostic. This approach can expedite staging and management while reducing the need for more invasive procedures. Incorporating peripheral node assessment into pulmonary practice may streamline lung cancer diagnostic workflows within multidisciplinary teams. This abstract is funded by: No funding
Castillo et al. (Fri,) studied this question.