Pulmonary subsolid nodules: value of semi-automatic measurement in diagnostic accuracy, diagnostic reproducibility and nodule classification agreement
- 123 Downloads
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.
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.
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).
Semi-automatic effective diameter measurement offers an opportunity to improve diagnostic accuracy and reproducibility as well as the classification reproducibility of SSNs.
• 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.
KeywordsCarcinoma, non-small-cell lung Multidetector computed tomography Diagnosis, computer-assisted Dimensional measurement accuracy Observer variation
Area under the curve
Volume CT dose index
Diameter of solid portion
Diameter of subsolid nodule
Invasive pulmonary adenocarcinoma
Lung CT Screening Reporting and Data System
Minimally invasive adenocarcinomas
Solid proportion within a nodule
Percentage relative difference
Receiver operating characteristic curve
Size-specific dose estimate
Compliance with ethical standards
The scientific guarantor of this publication is Chang Min Park.
Conflict of interest
The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was waived by the Institutional Review Board.
Institutional Review Board approval was obtained.
Study subjects or cohorts overlap
Part of the study population (36/89) had participated in a previous published study .
• diagnostic study
• performed at one institution
- 13.Cohen JG, Goo JM, Yoo RE et al (2016) The effect of late-phase contrast enhancement on semiautomatic software measurements of CT attenuation and volume of part-solid nodules in lung adenocarcinomas. Eur Radiol 85:1174–1180Google Scholar
- 14.American Association of Physicists in Medicine (2011) Size-specific dose estimates (SSDE) in pediatric and adult body CT examinations. Task Group. American Association of Physicists in Medicine, College Park, p 204Google Scholar
- 18.de Hoop B, Gietema H, van Ginneken B, Zanen P, Groenewegen G, Prokop M (2009) A comparison of six software packages for evaluation of solid lung nodules using semi-automated volumetry: what is the minimum increase in size to detect growth in repeated CT examinations. Eur Radiol 19:800–808CrossRefPubMedGoogle Scholar
- 32.American College of Radiology (2014) Lung CT Screening Reporting and Data System (Lung-RADS). American College of Radiology. Available via www.acr.org/Quality-Safety/Resources/LungRADS. Accessed 15 Oct 2016