Endobronchial Ultrasound Image Simulation for Image-Guided Bronchoscopy

Background/Objective: Accurate disease diagnosis and staging are essential for patients suspected of having lung cancer. The state-of-the-art minimally invasive tools used by physicians to perform these operations are bronchoscopy, for navigating the lung airways, and endobronchial ultrasound (EBUS), for localizing suspect extraluminal cancer lesions. While new image-guided systems enable accurate bronchoscope navigation close to a lesion, no means exists for guiding the final EBUS localization of an extraluminal lesion. We propose an EBUS simulation method to assist with EBUS localization. Methods: The method draws on a patient's chest computed-tomography (CT) scan to model the ultrasound signal propagation through the tissue media. The method, which is suitable for simulating EBUS images for both radial-probe and convex-probe EBUS devices, entails three steps: 1) image preprocessing, which generates a 2D CT equivalent of the EBUS scan plane; 2) EBUS scan-line computation, which models ultrasound transmission to map the CT plane into a preliminary simulated EBUS image; and 3) image post-processing, which increases realism by introducing simulated EBUS imaging effects and artifacts. Results: Results show that the method produces simulated EBUS images that strongly resemble images generated live by a real device and compares favorably to an existing ultrasound simulation method. It also produces images at a rate greater than real time (i.e., $>$53 frames/sec). We also demonstrate a successful integration of the method into an image-guided EBUS bronchoscopy system. Conclusion/Significance: The method is effective and practical for procedure planning/preview and follow-on live guidance of EBUS bronchoscopy.

Automated summary

This study proposes a method to assist with EBUS localization by simulating EBUS images. The method utilizes a patient's chest CT scan to model the ultrasound signal propagation, generating simulated EBUS images that closely resemble those produced by a real device. Experimental results demonstrate the effectiveness and practicality of the method, which can generate images at a rate greater than real time and has been successfully integrated into an image-guided EBUS bronchoscopy system.