1. Noninvasive Computed Tomography–based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial
- Author
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Richard A. Robb, Erin Greco, Srinivasan Rajagopalan, Kavita Garg, Fenghai Duan, Fabien Maldonado, Hrudaya Nath, Ronald A. Karwoski, Sushravya Raghunath, Brian J. Bartholmai, and Tobias Peikert
- Subjects
Pulmonary and Respiratory Medicine ,Oncology ,medicine.medical_specialty ,Lung ,medicine.diagnostic_test ,business.industry ,Nodule (medicine) ,Computed tomography ,respiratory system ,Critical Care and Intensive Care Medicine ,medicine.disease ,respiratory tract diseases ,medicine.anatomical_structure ,Internal medicine ,medicine ,Adenocarcinoma ,National Lung Screening Trial ,Radiology ,Personalized medicine ,medicine.symptom ,Lung cancer ,business ,Lung cancer screening - Abstract
Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification.Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes.Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into...
- Published
- 2015
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