New Software Identifies and Stratifies Risk Posed by Lung Nodules
Volume 2, Issue 2
Researchers have developed a tool to noninvasively characterize pulmonary adenocarcinoma.
Tobias Peikert, M.D.
A multidisciplinary team of researchers at the Mayo Clinic Cancer Center has developed a new software tool to noninvasively characterize pulmonary adenocarcinoma, a common type of cancerous nodule in the lungs.
Results from a pilot study of the computer-aided nodule assessment and risk yield (CANARY) are published in an article in the April 2013 issue of the Journal of Thoracic Oncology.
Pulmonary adenocarcinoma is the most common type of lung cancer. Lung cancer is the leading cause of cancer-related deaths in the United States.
"Early detection using traditional computed tomography (CT) scans can lead to a better prognosis," said Tobias Peikert, M.D., a Mayo Clinic Cancer Center pulmonologist and senior author of the article. "However, a subgroup of the detected adenocarcinomas identified by CT may grow very slowly and may be treatable with less extensive surgery."
The computer-aided nodule assessment and risk yield can noninvasively stratify the risk lung adenocarcinomas pose by characterizing the nodule as aggressive or indolent with high-sensitivity, specificity and predictive values.
The computer-aided nodule assessment and risk yield uses data obtained from existing high-resolution diagnostic or screening CT images of pulmonary adenocarcinomas to match each pixel of the lung nodule to one of nine unique radiological exemplars. In testing, the CANARY classification of these lesions had an excellent correlation with the microscopic analysis of the surgically removed lesions that were examined by lung pathologists.
"Without effective screening, most lung cancer patients present with advanced stage disease, which has been associated with poor outcomes," Dr. Peikert said. "While CT lung cancer screening has been shown to improve patient survival, the initiation of a nationwide screening program would carry the risk of overtreatment of slow-growing tumors and would be associated with substantial health care costs. The computer-aided nodule assessment and risk yield represents a new tool to potentially address these issues."
The tool is still in the research phase and not yet available for use in patients.
How CANARY Works to Identify Tumors
Watch a video of Dr. Peikert discussing this study.