Computer-Aided Nodule Detection and Volumetry to Reduce Variability Between Radiologists in the Interpretation of Lung Nodules at Low-Dose Screening Computed Tomography

Abstract

Objective: The aim of this study was to evaluate whether a computer-aided diagnosis (CAD) system improves interobserver agreement in the interpretation of lung nodules at low-dose computed tomography (CT) screening for lung cancer. Materials and Methods: Baseline low-dose screening CT examinations from 134 participants enrolled in the National Lung Screening Trial were reviewed by 7 chest radiologists. All participants consented to the use of their deidentified images for research purposes. Screening results were classified as positive when noncalcified nodules larger than 4 mm in diameter were present. Follow-up evaluation was recommended according to the nodule diameter: 4 mm or smaller, more than 4 to 8 mm, and larger than 8 mm. When multiple nodules were present, recommendations were based on the largest nodule. Readers initially assessed the nodule presence visually and measured the average nodule diameter manually. Revision of their decisions after reviewing the CAD marks and size measurement was allowed. Interobserver agreement evaluated using multirater kappa statistics was compared between initial assessment and that with CAD. Results: Multirater kappa values for the positivity of the screening results and follow-up recommendations were improved from moderate (kappa = 0.53-0.54) at initial assessment to good (kappa = 0.66-0.67) after reviewing CAD results. The average percentage of agreement between reader pairs on the positivity of screening results and follow-up recommendations per case was also increased from 77% and 72% at initial assessment to 84% and 80% with CAD, respectively. Conclusion: Computer-aided diagnosis may improve the reader agreement on the positivity of screening results and follow-up recommendations in the assessment of low-dose screening CT.