Natural language processing (NLP) software use in the discovery of incidental lung cancers.
Whether chest CT scans performed routinely during emergency room (ER) visits for general medical conditions could be used to identify patients with incidental lung cancers and NLP software was used to review all CT scans obtained.
Abstract
1559Background: Low-dose computer tomography (LDCT) screening for individuals at high risk for developing lung cancer has led to earlier detection of suspicious nodules, rapid diagnosis, and a reduction in deaths due to lung cancer. Unfortunately, the majority of lung cancers are diagnosed at advanced stages where most patients will still die from their disease. We conducted a pilot study to evaluate whether chest CT scans performed routinely during emergency room (ER) visits for general medical conditions could be used to identify patients with incidental lung cancers. Methods: NLP software was used to review all CT scans obtained in 3 community-based hospital ERs in Nashville, TN and Dallas, TX from October, 2014 through December, 2015. All CT radiology reports containing key words such as: ‘nodule’, ‘opacity’, or ‘mass’ were identified by NLP software and collected by nurse navigators. Corresponding images were then reviewed by cancer center multi-disciplinary tumor boards (MDTB). Repeat imaging or bio...