Pulmonary subsolid nodules: value of semi-automatic measurement in diagnostic accuracy, diagnostic reproducibility and nodule classification agreement

Abstract

Objectives: We hypothesized that semi-automatic diameter measurements would improve the accuracy and reproducibility in discriminating preinvasive lesions and minimally invasive adenocarcinomas from invasive pulmonary adenocarcinomas appearing as subsolid nodules (SSNs) and increase the reproducibility in classifying SSNs.

Methods: Two readers independently performed semi-automatic and manual measurements of the diameters of 102 SSNs and their solid portions. Diagnostic performance in predicting invasive adenocarcinoma based on diameters was tested using logistic regression analysis with subsequent receiver operating characteristic curves. Inter- and intrareader reproducibilities of diagnosis and SSN classification according to Fleischner's guidelines were investigated for each measurement method using Cohen's κ statistics.

Results: Semi-automatic effective diameter measurements were superior to manual average diameters for the diagnosis of invasive adenocarcinoma (AUC, 0.905-0.923 for semi-automatic measurement and 0.833-0.864 for manual measurement; p<0.05). Reproducibility of diagnosis between the readers also improved with semi-automatic measurement (κ=0.924 for semi-automatic measurement and 0.690 for manual measurement, p=0.012). Inter-reader SSN classification reproducibility was significantly higher with semi-automatic measurement (κ=0.861 for semi-automatic measurement and 0.683 for manual measurement, p=0.022).

Conclusions: Semi-automatic effective diameter measurement offers an opportunity to improve diagnostic accuracy and reproducibility as well as the classification reproducibility of SSNs.

Key points: • Semi-automatic effective diameter measurement improves the diagnostic accuracy for pulmonary subsolid nodules. • Semi-automatic measurement increases the inter-reader agreement on the diagnosis for subsolid nodules. • Semi-automatic measurement augments the inter-reader reproducibility for the classification of subsolid nodules.

Keywords: Carcinoma, non-small-cell lung; Diagnosis, computer-assisted; Dimensional measurement accuracy; Multidetector computed tomography; Observer variation.