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Cheng S, Guan T, Zhu L, Zheng Y, Li F. A study on the correlation between histopathological subtypes of solitary invasive pulmonary adenocarcinoma and preoperative CT imaging features. Int J Radiat Res 2025; 23 (3) :543-549 URL: http://ijrr.com/article-1-6528-en.html
The General Hospital of Western Theater Command, Chengdu, 610000, China , qras510@163.com
Abstract: (565 Views)
Background: Lung adenocarcinoma exhibits considerable heterogeneity in histological subtypes, which are closely associated with prognosis. This study aimed to investigate the correlation between preoperative chest computed tomography (CT) features and histopathological subtypes of solitary invasive pulmonary adenocarcinoma, with the goal of establishing predictive imaging markers. Materials and Methods: A retrospective analysis was conducted on 187 patients with solitary invasive pulmonary adenocarcinoma (≤3.0 cm), categorized into three groups based on the 2015 WHO classification: G1 (lepidic predominant, n=77), G2 (papillary/acinar predominant, n=65), and G3 (micropapillary/solid predominant, n=45). CT characteristics—including lesion size, CT attenuation values, ground-glass opacity, solid component ratio, lobulation, spiculation, pleural traction, and vascular signs—were analyzed. Multivariate logistic regression and predictive modeling were used to identify independent imaging predictors for each subtype. Results: Significant differences were found among the three groups in CT values, lesion size, solid component proportion, spiculation, lobulation, and pleural traction (p<0.05). Vascular invasion and air space dissemination were significantly more frequent in G3 (p<0.001 and p=0.009, respectively). Multivariate analysis identified ground-glass opacity, CT value, burr sign, and lesion size as independent predictors for G1; vascular sign and size for G2; and gender (female), lobulation, and pleural traction for G3. The predictive model for G1 showed excellent diagnostic performance with an AUC of 0.986. Conclusion: Preoperative CT features correlate significantly with histopathological subtypes of lung adenocarcinoma. Distinct imaging patterns can serve as non-invasive predictors, aiding in preoperative risk stratification and individualized treatment planning for patients with pulmonary nodules.
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