Medical AI startup: AI analysis can improve cancer detection
Medical AI startup — Lunit — and Massachusett General Hospital conducts medical study to showcase how AI can improve lung cancer detection
In an announcement made by Lunit — a South Korean medical artificial intelligence (AI) company — the company has reported its partnership on its latest study with Massachusett General Hospital.
In the study, the two organisations showcased that AI algorithms trained to detect pulmonary nodules can improve the detection of lung cancer on chest radiographs, following the analysis of 5,485 chest radiographs collected from participants in the National Lung Screening Trial (NLST).
“Low-dose CT is recommended for lung cancer screening because the detection of chest radiographs is challenging for radiologists due to its projectional nature of radiography,” commented Subba Digumarthy, the senior author of the study and an attending thoracic radiologist at MGH.
“However, compared with chest radiography, CT is less accessible and more expensive, exposing patients to a higher dose of radiation. This study shows that AI can provide diagnostic value to more patients by supplementing the shortcomings and maintaining the advantages of x-ray diagnosis.”
As a result of the study the two companies report that the sensitivity and specificity of AI algorithms to detect malignant pulmonary nodules were 94% and 83%, respectively.
Lunit’s Insight CXR technology — harness in this recent study — has analyses over 3mn images in over 80 countries since the technology which was CE marked in 2019, and has an accuracy of 97% to 99%, when it comes to the detection of 10 major chest diseases including lung nodules and pneumothorax.
“Through this first collaboration with the MGH research team, we are happy to validate the generalisability and accuracy of our AI approach based on NLST data,” said Brandon Suh, CEO of Lunit.
“It is a meaningful study to show Lunit INSIGHT CXR can be utilized to diagnose cancer-related nodules and detect lung cancer in earlier stages.”
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