A common imaging test used for injuries and illnesses could have a secondary and important benefit: capturing subtle, early signs of lung cancer.
While computed tomography (CT) scans can provide important information to diagnose illnesses and conditions, these imaging tests can also reveal other unrelated issues, known as “incidental” findings, that raise questions beyond what the physicians were originally looking for.
The new Lung Nodule Program at The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (OSUCCC – James) combines the benefits of automated natural language processing tools with a subspecialized treatment team to create a system for flagging and methodically evaluating incidental lung nodule findings to capture subtle signs of lung cancer.
According to the American Cancer Society, more people die annually of lung cancer than breast, colon, and prostate cancer combined – largely due to late-stage diagnosis.
