New AI Use Case for Detecting COVID-19 with CT Scans

The American College of Radiology has released an artificial intelligence (AI) use case designed to aid diagnosis of COVID-19 using CT scans of the chest, according to Psychology Today.

Having a way to quickly identify patterns in patient imaging can help in determining if the patient has COVID-19. Artificial intelligence deep learning is well suited to detect patterns in complex data that may be overlooked by the human eye.

The ACR Science Institute constructed the AI use case based on data from a retrospective study of the chest CT scans of 121 symptomatic COVID-19 patients conducted by the Icahn School of Medicine at Mount Sinai, New York, New York, along with researchers from various hospitals in China, that was published in Radiology on February 20, 2020.

The study identified certain common characteristics that present in the imaging of COVID-19 over time. Namely, the researchers found that the “hallmarks of COVID-19 infection on imaging were bilateral and peripheral ground-glass and consolidative pulmonary opacities,” and that with increased time after the onset of symptoms, the CT’s findings occurred more frequently. These findings include consolidation, linear opacities, “crazy-paving” pattern, the “reverse halo” sign, bilateral and peripheral disease, and greater total lung involvement.