This novel tip-tracked EMN system incorporating both ENB and EMTTNA can guide biopsy and FM placement with a high degree of success and with a low complication rate. Multicentered prospective trials are required to develop algorithmic approaches to combine ENB and EMTTNA into a single procedure.
Background: Screen detected and incidental pulmonary nodules are increasingly common. Current guidelines recommend tissue sampling of solid nodules >8 mm. Bronchoscopic biopsy poses the lowest risk but is paired with the lowest diagnostic yield when compared to CT-guided biopsy or surgery. A need exists for a safe, mobile, low radiation dose, intra-procedural method to localize biopsy instruments within target nodules. This retrospective cross sectional reader feasibility study evaluates the ability of clinicians to identify pulmonary nodules using a prototype carbon nanotube radiation enabled stationary digital chest tomosynthesis system.Methods: Patients with pulmonary nodules on prior CT imaging were recruited and consented for imaging with stationary digital chest tomosynthesis. Five pulmonologists of varying training levels participated as readers. Following review of patient CT and a thoracic radiologist's interpretation of nodule size and location the readers were tasked with interpreting the corresponding tomosynthesis scan to identify the same nodule found on CT.Results: Fifty-five patients were scanned with stationary digital chest tomosynthesis. The median nodule size was 6 mm (IQR =4-13 mm). Twenty nodules (37%) were greater than 8 mm. The radiation entrance dose for s-DCT was 0.6 mGy. A significant difference in identification of nodules using s-DCT was seen for nodules <8 vs. ≥8 mm in size (57.7% vs. 90.9%, CI: −0.375, −0.024; P<0.001). Inter-reader agreement was fair, and better for nodules ≥8 mm [0.278 (SE =0.043)].
Conclusions:With system and carbon nanotube array optimization, we hypothesize the detection rate for nodules will improve. Additional study is needed to evaluate its use in target and tool co-localization and target biopsy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.