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30 Jan 2023 - 02 Feb 2023

AI Diagnoses Lung Disease from CT Images as Accurately as Medical Specialists

By MedImaging International staff writers
Posted on 31 Jul 2022
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Image: AI performs as well as medical specialists in analyzing lung disease (Photo courtesy of Nagoya University)
Image: AI performs as well as medical specialists in analyzing lung disease (Photo courtesy of Nagoya University)

Doctors have waited a long time for an early means of diagnosing idiopathic pulmonary fibrosis, a potentially fatal disease that can scar a person’s lungs. Except for drugs that can delay the disease’s progression, established therapies do not exist. Since doctors face many difficulties diagnosing the disease, they often have to request a specialist diagnosis. In addition, many of the diagnostic techniques, such as lung biopsy, are highly invasive. These investigative measures may exacerbate the disease, increasing a patient's risk of dying. Now, researchers have developed an artificial intelligence (AI) algorithm that accurately and quickly diagnoses idiopathic pulmonary fibrosis. The algorithm makes its diagnosis based only on information from non-invasive examinations, including lung images and medical information collected during daily medical care.

In order to develop the new technology to diagnose idiopathic pulmonary fibrosis, researchers at Nagoya University (Nagoya, Japan) used AI to analyze medical data collected during normal care from patients undergoing interstitial pneumonia treatment. They found that their AI diagnosed idiopathic pulmonary fibrosis with a similar level of accuracy as a human specialist. Despite finding that their AI performed just as well as experts, the team stress that they do not see it as replacing medical professionals. Instead, they hope that specialists will use AI in medical treatment to ensure that they do not miss opportunities for early treatment. Its use would also avoid invasive procedures, such as lung biopsies, which could save lives.

“Idiopathic pulmonary fibrosis has a very poor prognosis among lung diseases,” said Taiki Furukawa, Assistant Professor of the Nagoya University Hospital. “It has been difficult to diagnose even for general respiratory physicians. The diagnostic AI developed in this study would allow any hospital to get a diagnosis equivalent to that of a specialist. For idiopathic pulmonary fibrosis, the developed diagnostic AI is useful as a screening tool, and may lead to personalized medicine by collaborating with medical specialists.”

Furukawa is excited about the possibilities: “The practical application of diagnostic AI and collaborative diagnosis with specialists may lead to a more accurate diagnosis and treatment. We expect it to revolutionize medical care.”

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