JNM: Virtual fly-through bronchoscopy provides effective diagnostic tool
Till A. Heusner, MD, of the University of Dusseldorf in Dusseldorf, Germany, and colleagues sought to investigate several facets of the virtual bronchoscopy technique, including the smallest bronchus diameter accessible, the time it takes to display images and the most effective approaches to use. The study was one of the first studies dealing with a virtual bronchoscopy program that integrates functional information and anatomical data.
Current PET/CT scanners are capable of providing high-resolution CT and PET datasets that make it possible to generate virtual fly-throughs, but previous pilot studies proved their feasibility, not their diagnostic accuracy, according to the authors.
To determine effectiveness, researchers performed whole-body 18F-FDG PET/CT scans on 61 consecutive NSCLC patients. From the data collected, virtual bronchoscopies were reconstructed and diagnostic accuracy of detection of regional lymph node metastases was evaluated using 18F-FDG PET/CT scans as a standard of reference.
Results from the virtual fly-through bronchoscopy showed the diagnostic accuracy was 81 percent, with a mean duration from the start of the virtual 18F-FDG PET/CT bronchoscopy tool until image display of 22 seconds. The mean smallest diameter of accessible bronchi was 3 mm.
The authors also found that a high maximum standardized uptake value (SUV), high mean SUV, large small-axis diameter and short distance to the airways aided in detection of lymph node metastases. Diagnostic accuracy remained high even in relatively small airways in the periphery of the lung.
Based on the results of the study, the authors concluded that using 18F-FDG PET/CT to detect lymph node metastases is “at least comparable to that of [endobronchial ultrasound].”
In the future, the software may be used as a complement to PET/CT to virtually visualize the bronchial system before interventional procedures, to plan optical bronchoscopies and define regions where a bronchoscopy-guided biopsy may be most promising for sampling of malignant tissue, according to the researchers.