Predictors of Invasive Adenocarcinomas among Pure Ground-Glass Nodules Less Than 2 cm in Diameter

Abstract

Benign lesions, atypical adenomatous hyperplasia (AAH), and malignancies such as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA) may feature a pure ground-glass nodule (pGGN) on a thin-slide computed tomography (CT) image. According to the World Health Organization (WHO) classification for lung cancer, the prognosis of patients with IA is worse than those with AIS and MIA. It is relatively risky to perform a core needle biopsy of a pGGN less than 2 cm to obtain a reliable pathological diagnosis. The early and adequate management of patients with IA may provide a favorable prognosis. This study aimed to disclose suggestive signs of CT to accurately predict IA among the pGGNs. A total of 181 pGGNs of less than 2 cm, in 171 patients who had preoperative CT-guided localization for surgical excision of a lung nodule between December 2013 and August 2019, were enrolled. All had CT images of 0.625 mm slice thickness during CT-guided intervention to confirm that the nodules were purely ground glass. The clinical data, CT images, and pathological reports of those 171 patients were reviewed. The CT findings of pGGNs including the location, the maximal diameter in the long axis (size-L), the maximal short axis diameter perpendicular to the size-L (size-S), and the mean value of long and short axis diameters (size-M), internal content, shape, interface, margin, lobulation, spiculation, air cavity, vessel relationship, and pleural retraction were recorded and analyzed. The final pathological diagnoses of the 181 pGGNs comprised 29 benign nodules, 14 AAHs, 25 AISs, 55 MIAs, and 58 IAs. Statistical analysis showed that there were significant differences among the aforementioned five groups with respect to size-L, size-S, and size-M (p = 0.029, 0.043, 0.025, respectively). In the univariate analysis, there were significant differences between the invasive adenocarcinomas and the non-invasive adenocarcinomas with respect to the size-L, size-S, size-M, lobulation, and air cavity (p = 0.009, 0.016, 0.008, 0.031, 0.004, respectively) between the invasive adenocarcinomas and the non-invasive adenocarcinomas. The receiver operating characteristic (ROC) curve of size for discriminating invasive adenocarcinoma also revealed similar area under curve (AUC) values among size-L (0.620), size-S (0.614), and size-M (0.623). The cut-off value of 7 mm in size-M had a sensitivity of 50.0% and a specificity of 76.4% for detecting IAs. In the multivariate analysis, the presence of air cavity was a significant predictor of IA (p = 0.042). In conclusion, the possibility of IA is higher in a pGGN when it is associated with a larger size, lobulation, and air cavity. The air cavity is the significant predictor of IA.

Identification of pathological subtypes of early lung adenocarcinoma based on artificial intelligence parameters and CT signs

“…The invasiveness of GGNs is closely associated with the size and density of lung nodules. Meng et al (2021) [ 28 ] found that 2D long diameter, 2D short diameter, volume, and mean CT value could be predictive indicators of the differential diagnosis of lung adenocarcinoma, which was similar to prior studies [ 29–31 ]. In our study, the 2D mean diameter, 3D mean diameter, mean CT value, maximum CT value, and volume measured by AI were significantly different among the AAH/AIS, MIA, and IAC groups (all P <0.001), which were basically consistent with the mentioned studies above.…”

“…There are different views on the role of CT signs in differentiating pathological subtypes of lung adenocarcinoma. Hsu et al (2021) [ 29 ] reported there were significant differences between the IAC and the non-IAC with respect to lobulation, air cavity except for location, shape, interface, margin, spiculation, vessel relationship, and pleural retraction. Zhan et al (2019) [ 16 ] found that the IAC groups had a higher frequency of mixed GGNs, bubble-like appearance, spiculation, pleural indentation, different locations, and a lower frequency of clear tumor–lung interface when compared with the AIS-MIA group.…”

A predictive nomogram for lymph node metastasis in part-solid invasive lung adenocarcinoma: A complement to the IASLC novel grading system

“…Bronchial cutoff and spiculation sign on CT. cutoff, and vascular cluster, are often indicative of a high degree of malignancy and can therefore be used as predictors of poor prognosis in patients (27)(28)(29)(30)(31). In this study, we revealed that spiculation and bronchial cutoff sign on preoperative CT were independent risk factors for lymph node metastasis.…”

Correlations Between Inflammatory Cell Infiltration and Relative Density and the Boundary Manifestation of Pulmonary Non-Neoplastic Ground Glass Nodules

“… 9 , 10 Although these morphological indicators for differentiating neoplastic and non-neoplastic GGNs were not completely consistent in different studies, it is generally believed that whether the boundary is clear or not is of great value for differentiation. 4 , 10 , 11 …”