Computer Aided Nodule Analysis and Risk Yield (CANARY) characterization of adenocarcinoma: radiologic biopsy, risk stratification and future directions

Adenocarcinoma of the lung encompasses a varied spectrum of disease with differing behavior, ranging from indolent lesions with essentially 100% post-resection disease-free survival (DFS) to aggressive cancer with poor outcomes despite early and appropriate surgery even in stage 1 disease (1,2). With implementation of the United States Preventative Services Task Force recommendation to screen high risk patients for lung cancer (3) we expect to identify more early-stage cancers—particularly from the adenocarcinoma spectrum (4). Computer Aided Nodule Analysis and Risk Yield (CANARY) is an automated quantitative CT analysis software that allows risk stratification of pulmonary nodules within the adenocarcinoma spectrum (5). Developed at Mayo Clinic, Rochester, MN, CANARY lung nodule characteristics have been shown to predict consensus histopathology (6). Further stratification of the type and volume of whole-nodule CANARY features has been shown to strongly correlate with post-resection DFS (7,8). Therefore, CANARY offers a noninvasive method of risk-stratifying these diverse tumors that may aid in clinical decision making and potentially surgical planning. In the case of multifocal adenocarcinoma of the lung, optimal surgical sequencing based on potential aggressiveness of each tumor may be considered. In this review we will detail CANARY’s development, role, validation and potential for clinical use. Lastly we will explore additional roles for CANARY and planned studies. We detail studies from our lab group that are works in progress, planned for submission or presently existing in abstract form. Please see Table 1 for a brief synopsis of published studies on CANARY to date