High yield of bronchoscopic transparenchymal nodule access real-time image-guided sampling in a novel model of small pulmonary nodules in canines.

Abstract

BACKGROUND:

Bronchoscopic transparenchymal nodule access (BTPNA) is a novel approach to accessing pulmonary nodules. This real-time, image-guided approach was evaluated for safety, accuracy, and yield in the healthy canine model.

METHODS:

A novel, inorganic model of subcentimeter pulmonary nodules was developed, consisting of 0.25-cc aliquots of calcium hydroxylapatite (Radiesse) implanted via transbronchial access in airways seven generations beyond the main bronchi to represent targets for evaluation of accuracy and yield. Thoracic CT scans were acquired for each subject, and from these CT scans LungPoint Virtual Bronchoscopic Navigation software provided guidance to the region of interest. Novel transparenchymal nodule access software algorithms automatically generated point-of-entry recommendations, registered CT images, and real-time fluoroscopic images and overlaid guidance onto live bronchoscopic and fluoroscopic video to achieve a vessel-free, straight-line path from a central airway through parenchymal tissue for access to peripheral lesions.

RESULTS:

In a nine-canine cohort, the BTPNA procedure was performed to sample 31 implanted Radiesse targets, implanted to simulate pulmonary nodules, via biopsy forceps through a specially designed sheath. The mean length of the 31 tunnels was 35 mm (20.5-50.3-mm range). Mean tunnel creation time was 16:52 min, and diagnostic yield was 90.3% (28 of 31). No significant adverse events were noted in the status of any of the canine subjects post BTPNA, with no pneumothoraces and minimal bleeding (all bleeding events < 2 mL in volume).

CONCLUSIONS:

These canine studies demonstrate that BTPNA has the potential to achieve the high yield of transthoracic needle aspiration with the low complication profile associated with traditional bronchoscopy. These results merit further study in humans.

• Authors: Daniel H Sterman, Thomas Keast, Lav Rai, Jason Gibbs, Henky Wibowo, Jeff Draper, Felix J Herth, Gerard A Silvestri
• Journal: Chest (Chest) Vol. 147 Issue 3 Pg. 700-707 (Mar 2015) ISSN: 1931-3543 [Electronic] United States
• PMID: 25275338 (Publication Type: Evaluation Study, Journal Article)

Topics

• Algorithms
• Animals
• Bronchoscopy (methods)
• Disease Models, Animal
• Dogs
• Image-Guided Biopsy (methods)
• Solitary Pulmonary Nodule (diagnostic imaging, pathology)
• Tomography, X-Ray Computed