GE Healthcare has announced a new artificial intelligence (AI) algorithm to help clinicians assess Endotracheal Tube (ETT) placements, a necessary and important step when ventilating critically ill Covid-19 patients.
The AI solution is one of five included in GE Healthcare’s Critical Care Suite 2.0, an industry-first collection of AI algorithms embedded on a mobile x-ray device for automated measurements, case prioritization and quality control.
Research shows that up to 25 percent of patients intubated outside of the operating room have misplaced ETTs on chest x-rays, which can lead to severe complications for patients, including hyperinflation, pneumothorax, cardiac arrest and death. Moreover, as Covid-19 cases climb, with more than 50 million confirmed worldwide, anywhere from 5-15 percent require intensive care surveillance and intubation for ventilatory support.
“Today, clinicians are overwhelmed, experiencing mounting pressure as a result of an ever-increasing number of patients,” said Jan Makela, President and CEO, Imaging at GE Healthcare. “The pandemic has proven what we already knew – that data, AI and connectivity are central to helping those on the front lines deliver intelligently efficient care. GE Healthcare is not only providing new tools to help hospital staff keep up with demand without compromising diagnostic precision, but also leading the way on Covid-era advancements that will have a long-lasting impact on the industry, long after the pandemic ends.”
Up to 45% of ICU patients, including severe Covid-19 cases, receive ETT intubation for ventilation. While proper ETT placement can be difficult, Critical Care Suite 2.0 uses AI to automatically detect ETTs in chest x-ray images and provides an accurate and automated measurement of ETT positioning to clinicians within seconds of image acquisition, right on the monitor of the x-ray system.
In 94% of cases the ET Tube tip-to-Carina distance calculation is accurate to within 1.0 cm. With these measurements, clinicians can determine if the ETT is placed correctly or if additional attention is required for proper placement. The AI generated measurements – along with an image overlay – are then made accessible in a picture archiving and communication systems (PACS).
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