Poster T12 - Developing a Tool for Researching and Preventing Coronary Air Embolism

Introduction: Coronary air embolism (CAE) is a preventable high morbidity and mortality complication of coronary angiography. It occurs via the introduction of air into coronary vasculature during intravascularly performed procedures. CAE can cause cardiogenic shock and death. While use of transparent manifolds and lines aids cardiac interventionalists in detection of air within lines, an automated method for air detection in manual injection coronary angiography has not been tested. We developed a device that utilizes an industrial air-fluid sensor to actively detect segments of air in angiography lines and notify its user. We then conducted early validation testing in preparation for testing during live coronary angiography procedures.

Materials and

Methods: A Panasonic BE-A301 Series Optical Bubble Sensor was wired to an Arduino Nano V3.0 Microcontroller with a backlit digital display, speaker, battery, and start button. An OLED Display Module (SSD1306 ) was selected to display both run time and number of air segments counted. The housing for the device was designed and 3D printed (Figure 1). The programming language used was C++. The device was attached to an injection line and contrast was passed through with varying air gap sizes: 20.0 mm, 10.0 mm, 5.0 mm, and 1.0 mm. The syringe was mounted onto a motorized injector. The contrast was injected at five different velocities: 1.0 m/s, 2.0 m/s, 3.0 m/s, 4.0 m/s, and 5.0 m/s for each gap size range. Each test was repeated 100 individual times. The number of air gaps counted by the device was recorded after each run. A Clopper-Pearson analysis was conducted to determine the one-sample success rate and binomial proportion confidence interval of 95%.

Results, Conclusions, and Discussions: The detector remained functional throughout the duration of all performed tests with a total run-time of 12 hours and 48 minutes. The battery was not replaced throughout testing. The components remained thermally stable without incidents of unexpected shut down. The detector was able to sense air gaps of all tested sizes, traveling at all tested velocities.
In detecting air gaps of all sizes, the binomial success rate was above 96% (p= 0.05) at the 1.0 m/s velocity. In detecting 20.0 mm air gaps the device success rate was above 95% (p=0.05) at all velocities. In detecting 10.0 mm air gaps, success rate was above 90% for all velocities except at 5.0 m/s. In detecting 5 mm air gaps the success rate was above 74% at all velocities (p=0.05). In detecting 1.0 mm air gaps, the success rate was above 51% for all velocities (p=0.05) (Figure 2).

CAE is a preventable high-morbidity and mortality complication of a commonly performed, often life-saving procedure. We designed and built a device that can reliably detect varying sizes of air gaps traveling at different velocities within a coronary angiography injection line. Although it does not completely eliminate the risk of CAE, it may serve as a method for monitoring and prevention in the future. In its current form, it may be especially useful for research purposes, and one day for and one day possibly for training interventional fellows.

Limitations of this study include the differences between laboratory and operating room conditions. Additionally, the compressive effects of turbulent flow and travel through the tube likely influence a volume change in the air gap. In the future it may be useful to quantify this effect to better understand the performance of our device. Overall, precise and up to date values on CAE complication rates are not available in the literature. This device may serve as a research tool to better quantify this issue in virtually any setting. In the future, automated detection may lead to automated removal of air from catheters.

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