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Updated: Jul 30, 2025
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
CT-based three-dimensional invasiveness analysis of adenocarcinoma presenting as pure ground-glass nodules
Jieun Oh1, Zhe Piao2, Hyun Jin Cho3
1Center for Advanced Medical Computing and Analysis, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Background:
We invest computed tomography (CT) image differences between non-invasive adenocarcinomas (NIAs) and invasive adenocarcinomas (IAs) presenting as pure ground glass nodules (GGNs).
Methods:
From 2013 to 2019, 48 pure GGNs were surgically resected in 45 patients. Of these, 40 were pathologically diagnosed as non-small cell lung cancers (NSCLCs). We assessed them using the Synapse Vincent (Fujifilm Co., Ltd., Tokyo, Japan) three-dimensional (3D) analysis system; we drew histograms of the CT densities. We calculated the maximum, minimum, means, and standard deviations of the densities. The proportions of GGNs of high CT density were compared between the two groups. The diagnostic performance was investigated via receiver operating curve (ROC) analysis.
Results:
Of the 40 pure GGNs, 20 were NIAs (4 adenocarcinomas in situ and 16 minimally IAs) and 20 IAs. Significant correlations were evident between histological invasiveness and the maximum and mean CT densities and the standard deviation. Neither the nodule volume nor the minimum CT density significantly predicted invasiveness. A CT volume density proportion >-300 Hounsfield units optimally predicted the invasiveness of pure GGNs; the cutoff was 5.41% with a sensitivity of 85% and a specificity of 95%.
Conclusions:
CT density reflected the invasiveness of pure GGNs. A CT volume proportion density >-300 Hounsfield units may significantly predict histological invasiveness.
