Artificial intelligence predicts risk for lung cancer from chest x-rays

Digital & Innovation: A deep learning model, a form of artificial intelligence (AI), was more accurate than the current clinical standard at predicting a person’s 12-year risk of developing lung cancer.

The model’s predictions are based on chest radiograph images (CXRs) and basic demographic data (age, sex, and current smoking status) commonly available in electronic health records (EHRs). The findings are published in Annals of Internal Medicine.

Lung cancer screening with chest computed tomography (CT) scans can prevent lung cancer death. However, Medicare’s current standard to determine who is eligible for lung cancer screening CT misses most lung cancers. Furthermore, lung cancer screening participation is poor, with an estimated less than 5 percent of screening-eligible persons being screened.

Researchers from Massachusetts General Hospital developed a convolutional neural network (CXR-LC) that predicts long-term incident lung cancer based on a chest x-ray image using 41,856 people from a large multicenter trial of lung cancer screening with chest x-rays (Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial).

The final model was validated in 5,615 additional PLCO participants and 5,493 persons from a second trial, the National Lung Screening Trial (NLST). The deep learning model performed better than the Medicare lung cancer screening criteria, the current clinical standard, missing 31% fewer lung cancers while screening the same number of people.