AI model identifies high-risk lung cancer in nonsmokers

In this study, the researchers externally validated the model in a separate group of never-smokers who underwent routine outpatient chest x-rays from 2013 to 2014. The primary outcome was six-year incident lung cancer, identified using International Classification of Disease codes. Risk scores were then converted to low, moderate, and high-risk groups based on externally derived risk thresholds. Of 17,407 patients (mean age 63 years) included in the study, 28% were deemed high risk by the deep learning model, and 2.9% of these patients later had a diagnosis of lung cancer, according to the findings. In addition, the high-risk group well exceeded the 1.3% six-year risk threshold where lung cancer screening CT is recommended by National Comprehensive Cancer Network (NCCN) guidelines.An example of a patient frontal chest x-ray showing a subtle nodular opacity (arrow) identified by AI in the right middle lung zone. Axial, noncontrast, low-dose chest CT scan shows a 1.1-cm solid nodule (arrow) in the right lower lobe. Image courtesy of Anika Walia, Boston University Moreover, after adjusting for age, sex, race, previous lower respiratory tract infection, and prevalent chronic obstructive pulmonary disease, there was still a 2.1 times greater risk of developing lung cancer in the high-risk group compared with the low-risk group. “A major advantage to our approach is that it only requires a single chest x-ray image, which is one of the most common tests in medicine and widely a...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: 2023 Source Type: news