The impact of lung parenchyma attenuation on nodule volumetry in lung cancer screening

Insights Imaging. 2021 Jun 25;12(1):84. doi: 10.1186/s13244-021-01027-0.

Abstract

Background: Recent recommendations for lung nodule management include volumetric analysis using tools that present intrinsic measurement variability, with possible impacts on clinical decisions and patient safety. This study was conducted to evaluate whether changes in the attenuation of the lung parenchyma adjacent to a nodule affect the performance of nodule segmentation using computed tomography (CT) studies and volumetric tools.

Methods: Two radiologists retrospectively applied two commercially available volumetric tools for the assessment of lung nodules with diameters of 5-8 mm detected by low-dose chest CT during a lung cancer screening program. The radiologists recorded the success and adequacy of nodule segmentation, nodule volume, manually and automatically (or semi-automatically) obtained long- and short-axis measurements, mean attenuation of adjacent lung parenchyma, and presence of interstitial lung abnormalities or disease, emphysema, pleural plaques, and linear atelectasis. Regression analysis was performed to identify predictors of good nodule segmentation using the volumetric tools. Interobserver and intersoftware agreement on good nodule segmentation was assessed using the intraclass correlation coefficient.

Results: In total, data on 1265 nodules (mean patient age, 68.3 ± 5.1 years; 70.2% male) were included in the study. In the regression model, attenuation of the adjacent lung parenchyma was highly significant (odds ratio 0.987, p < 0.001), with a large effect size. Interobserver and intersoftware agreement on good segmentation was good, although one software package performed better and measurements differed consistently between software packages.

Conclusion: For lung nodules with diameters of 5-8 mm, the likelihood of good segmentation declines with increasing attenuation of the adjacent parenchyma.

Keywords: Interstitial lung disease; Lung cancer screening; Segmentation; Volumetry.