Three-dimensional mean CT attenuation value of pure and part-solid ground-glass lung nodules may predict invasiveness in early adenocarcinoma. Issue 12 (December 2019)

• Record Type: Journal Article
• Authors: Kitazawa, S.; Saeki, Y.; Kobayashi, N.; Kikuchi, S.; Goto, Y.; Sato, Y.
• Is Part Of: Clinical radiology. Volume 74:Issue 12(2019)
• Page Start: 944
• Page End: 949
• Publication Date: 2019-12
• Subjects: Medical radiology -- Periodicals; Radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiology -- Periodicals; Societies, Medical -- Periodicals; Medical radiology; Radiotherapy; Electronic journals; Periodicals; 616.0757
• DOI: 10.1016/j.crad.2019.09.130
• Languages: English
• ISSNs: 0009-9260

Abstract

Abstract : AIM: This study evaluated the relationship between three-dimensional (3D) mean computed tomography (CT) attenuation values of ground-glass nodules (GGN) and pathological invasiveness in early lung adenocarcinoma. The diagnostic accuracy of 3D CT attenuation values was compared with that of two-dimensional (2D) CT attenuation values and standardised uptake value on positron-emission tomography (PET). MATERIALS AND METHODS: Surgical and radiological data from 96 pure or part-solid GGNs of <20 mm were analysed retrospectively. Mean 2D and 3D CT attenuation values of the tumours were obtained with semi-automated volumetric software. Pathological invasiveness was diagnosed according to the International Association for the Study of Lung Cancer (IASLC))/American Thoracic Society (ATS)/European Respiratory Society (ERS) classification. Pre-invasive lesions and minimally invasive adenocarcinomas were classified as non-invasive adenocarcinoma. Univariate and multivariate analyses determined relationships between pathological invasiveness and clinical/radiological findings. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cut-off value for detecting invasive adenocarcinoma. RESULTS: A total of 66 non-invasive and 30 invasive adenocarcinoma cases between 2010 and 2016 were analysed. Univariate analysis revealed four tumour invasiveness-associated predictors: maximum diameter, SUVmax, mean 2D CT attenuation value, and mean 3D CT attenuation value (p<0.05). Multivariate analysis revealed that the maximum diameter, SUVmax, and mean 3D CT attenuation value were significant predictors of pathological invasiveness ( p= 0.023, 0.022, 0.004). The area under the ROC curve to predict invasive adenocarcinoma for mean 3D CT attenuation value was 0.838 and the cut-off value was –489 HU. CONCLUSION: The mean 3D CT attenuation value could distinguish pre-invasive lesions and minimally invasive adenocarcinoma from invasive adenocarcinoma. Highlights: Pre/minimally invasive adenocarcinoma shows GGO-dominant nodule on chest CT. Pre/minimally invasive adenocarcinomas could be candidate for sublobar resection. Accurate radiological prediction is crucial to determine the surgical procedure. Three-dimensional densitometric evaluation is helpful to predict tumor invasiveness. Mean CT value calculated by 3D-CT was well correlated with pathological features.