ECR 2013 Rec: Non-solid, part-solid or solid? Classification of pulmonary nodules in thoracic CT by radiologists and a computer-aided diagnosis system #B0297 #SS504
B-0297 Non-solid, part-solid or solid? Classification of pulmonary nodules in thoracic CT by radiologists and a computer-aided diagnosis system
C. Jacobs, E.M. van Rikxoort, J.-M. Kuhnigk, E.T. Scholten, P.A. de Jong, C. Schaefer-Prokop, M. Prokop, B. van Ginneken | Friday, March 8, 10:30 – 12:00 / Room D1
Purpose: Classifying pulmonary nodules into solid, part-solid and non-solid is crucial for patient management. A computer algorithm is compared to a radiologist on a large data set obtained from a multi-center lung cancer screening trial.
Methods and Materials: Low-dose chest CT scans (16×0.75mm, 120-140 kVp, 30 mAs) with part-solid, non-solid, and solid nodules with a diameter between 7 and 30 mm were randomly selected from two sites participating in the Dutch-Belgian NELSON lung cancer screening trial. The set contained 137 scans, including 50 part-solid, 50 non-solid and 52 solid nodules. The nodule-type recorded in the screening database was used as a reference standard. An automated classification system for characterization of nodules was designed using morphometric features. The accuracy of the computer algorithm was evaluated in three ways: classifying nodules (1) as solid or subsolid, (2) as solid, part-solid or non-solid, and, (3) for the subsolid lesions only, as part-solid or non-solid. An experienced thoracic radiologist independently performed the same classification.
Results: The accuracy of the automated system to differentiate between solid and subsolid nodules was 0.88, compared to 0.95 for the radiologist. The computer classified the nodules as solid, part-solid or non-solid with an accuracy of 0.72 versus 0.80 for the radiologist. The software reached an accuracy of 0.71 in differentiating part-solid from non-solid nodules, where the radiologist had an accuracy of 0.77.
Conclusion: A novel automated characterization tool for pulmonary nodules shows promising performance and could aid radiologists in selecting the appropriate workup for pulmonary nodules.