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Waiting To Inhale: GE’s AI Solution To Assess Breathing Tube Placement Gets FDA Clearance

Brett Nelson
Jay Stowe
November 29, 2021

Like many tasks in medicine, threading a breathing tube down a patient’s trachea requires skill, patience and steady hands. Insert the tube not far enough and the patient can throw up food into their lungs, causing infection; insert it too far and you might trigger a collapsed lung or cardiac arrest. Doctors often order a chest X-ray to make sure the tube is positioned right.

Now, the Food and Drug Administration has cleared for sale software developed by GE Healthcare that uses artificial intelligence (AI) to help doctors assess the placement of endotracheal tubes (ETT) and make critical adjustments faster. The AI solution, which received the FDA’s 510(k) clearance, is one of five included in GE Healthcare’s Critical Care Suite 2.0, a collection of algorithms embedded in mobile X-ray devices that can give hospitals access to AI without having to make large investments in IT infrastructure. 

Since 2020, clinicians have been intubating more patients than their usual share as the procedure has become an important tool for keeping the sickest COVID-19 patients alive using ventilators. With over 250 million COVID-19 cases worldwide, 5% to 15% require intensive care surveillance and intubation. Over the past year, GE was able to distribute its AI solution to more than 200 hospitals as part of the FDA’s COVID-19 imaging guidance. Now the new algorithm can be made available for use outside of the public health emergency.

“We saw the potential role of Critical Care Suite 2.0 in helping hospitals manage the crisis caused by the number of patients who needed ETT placements during the pandemic, requiring accelerated innovation, and we quickly worked with the FDA to make the solution available to clinicians,” says Jan Makela, president and CEO of Imaging at GE Healthcare. “We are pleased to now have the FDA’s clearance for this important solution.”

 

CCS 2.0 misplaced tube
Top and above images: A radiologist reads an X-ray scan using GE Healthcare’s Critical Care Suite 2.0 — a collection of algorithms embedded in mobile X-ray devices that give hospitals access to AI without huge investments in IT infrastructure. Images credit: GE Healthcare. 
 

 

In a typical intubation procedure, a clinician inserts the breathing tube and a radiologist studies the X-ray to confirm the tube’s positioning. Properly placed tubes stop between 3 and 7 centimeters above the carina — the point where the trachea splits into each lung. Before the arrival of AI, research in the U.S. shows that breathing tubes were poorly positioned in up to 25% of patients intubated outside of operating rooms, such as in an ER or ICU.

GE’s AI detects the end of the tube, calculates its distance from the carina and displays the data on the X-ray monitor within seconds of capturing the image. The new algorithm can calculate the vertical distance from the tip of a breathing tube to the carina to within 1 millimeter. With as many as 45% of ICU patients across the globe, including severe COVID-19 cases, requiring intubation for ventilation, this kind of instantaneous feedback can support clinicians in their work and help identify which patients need additional adjustment.

Improper positioning of an endotracheal tube can lead to various complications, including pneumothorax, a form of collapsed lung caused by tears that leak air into the space between the lung and the chest wall. As that air pocket grows, it presses on the lung, making it harder to breathe. Unfortunately, in many hospitals it can take up to eight hours for a radiologist to review the chest X-rays of a suspected pneumothorax patient, even if they are marked “STAT.” But when a patient is scanned on a device with Critical Care Suite 2.0, the system automatically analyzes images and sends an alert for cases with a suspected pneumothorax — along with the original chest X-ray — to the radiologist for review. Technologists can also be notified when a specific case deserves priority care.

“Seconds and minutes matter when dealing with a collapsed lung or assessing endotracheal tube positioning in a critically ill patient,” explains Dr. Amit Gupta, modality director of diagnostic radiography at University Hospital Cleveland Medical Center. “In several COVID-19 patient cases, the pneumothorax AI algorithm has accurately identif[ied] pneumothoraces/barotrauma in intubated COVID-19 patients, flagging them to radiologists and enabling expedited patient treatment. Altogether, this technology is … helping us operate more efficiently as a practice, without compromising diagnostic precision.”

Embedding Critical Care Suite 2.0 on a mobile X-ray device provides radiologists and technologists with a host of benefits, including speedier results, case prioritization and better quality control of the images right at the patient’s bedside.

“The pandemic has proven what we already knew: that data, AI and connectivity are central to helping frontline clinicians deliver intelligently efficient care,” says Makela.”

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