Artificial Intelligence Enables Rapid COVID-19 Lung Imaging Analysis

The aim is to quickly detect pneumonia — and therefore better distinguish between COVID-19 patients likely to need more supportive care in the hospital and those who could be followed closely at home

The new AI capability has so far provided UC San Diego Health physicians with unique insights into more than 2,000 images. In one case, a patient in the Emergency Department who did not have any symptoms of COVID-19 underwent a chest X-ray for other reasons. Yet the AI readout of the X-ray indicated signs of early pneumonia, which was later confirmed by a radiologist. As a result, the patient was tested for COVID-19 and found to be positive for the illness.

The researchers at UC San Diego had initially developed a machine learning algorithm that allows radiologists to use AI to enhance their own abilities to spot pneumonia on chest X-rays. Trained with 22,000 notations by human radiologists, the algorithm overlays X-rays with color-coded maps that indicate pneumonia probability. More recently, the researchers applied this AI approach to 10 chest X-rays, published in medical journals, from five patients treated in China and the US for COVID-19. The algorithm consistently localized areas of pneumonia, despite the fact that the images were taken at several different hospitals, and varied considerably in technique, contrast and resolution. The AI method has now been deployed across UC San Diego Health in a clinical research study that allows any physician or radiologist to get an initial estimate regarding a patient’s likelihood of having pneumonia within minutes, at point-of-care. The researchers believe that chest X-rays are cheaper, the equipment is more portable and easier to clean, and results are returned more quickly than many other diagnostics.

“That’s where imaging can play an important role. We can quickly triage patients to the appropriate level of care, even before a COVID-19 diagnosis is officially confirmed,” said
Albert Hsiao, MD, PhD, associate professor of radiology at University of California San Diego School of Medicine and radiologist at UC San Diego Health.

“As we prepare for a potential surge in patients with COVID-19, it’s not just patient rooms and supplies that may become limited, but also physician and staff capacity,” said Christopher Longhurst, MD, chief information officer and associate chief medical officer for UC San Diego Health. “So it’s tremendously helpful to have tools that allow physicians who are not as experienced as radiologists in reading X-rays to get a quick idea of what they’re looking at, especially frontline emergency and hospital-based physicians.”

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