Ultrasonic bubble detection and tracking using spatial coherence and motion modeling
Limited options exist to improve oxygenation in patients with acute hypoxic respiratory failure. We are developing an intravascular oxygenator catheter capable of delivering a clinically significant amount of oxygen directly into the bloodstream of patients. With high oxygen flux diffusing into the blood, bubbles can form, so a critical goal of the device design is minimizing the risk of gas embolism. We demonstrate the use of ultrafast ultrasound imaging, coherence beamforming, and image processing to address the unmet need of bubble quantification in a benchtop flow circuit during oxygenation. We measured the increase in dissolved oxygen due to flux through our non-porous hollow fiber membranes under hyperbaric conditions. The Verasonics Vantage 256 ultrasound scanner and L22-14 linear array transducer were used for high frame rate imaging (4 to 20 kHz) in 100 ms bursts to detect bubble formation in water during operation. The transducer was placed distal to the device to monitor both along the direction of flow and in cross-section. Using the recorded channel data we performed mid-lag spatial coherence processing to isolate bubbles from background signal and noise. We demonstrate an image processing pipeline including thresholding and blob analysis to identify bubble locations in each frame and a motion model to pair these observations into tracks of individual bubbles during the observation period. We found no significant increase in bubble counts throughout 30 minutes of oxygenation using the device. We also explore the use of temporal filtering methods such as median filtering and directional filtering, and image processing such as non-local means filtering.
