术前CT影像学特征诊断肺腺癌亚实性结节 脏层胸膜侵犯的价值

The Value of Preoperative CT Imaging Features in Diagnosing Visceral Pleural Invasion in Pulmonary Adenocarcinoma Manifesting as Sub-Solid Nodules

摘要: 目的：探讨术前CT影像学特征诊断肺腺癌亚实性结节(SSN)脏层胸膜侵犯(VPI)的价值。方法：回顾性分析164例经手术病理证实的SSN肺腺癌患者的临床及CT影像学特征，将患者分为VPI阳性组及VPI阴性组。比较两组的临床及CT影像学特征，通过多因素logistic回归分析确定肺腺癌发生VPI的独立危险因素。受试者工作特征曲线及曲线下面积(AUC)用于评估模型的预测效能。结果：实性百分比、结节–胸膜关系和邻近胸膜增厚是VPI的独立危险因素，基于三者结合构建的联合模型具有最高的预测效能(AUC = 0.816)，优于单一因素模型。结论：实性百分比、结节–胸膜关系和邻近胸膜增厚是SSN肺腺癌发生VPI的独立危险因素，三者联合构建的模型对SSN肺腺癌发生VPI有较好的预测效能。

Abstract: Objective: To explore the value of preoperative CT imaging features in diagnosing visceral pleural invasion (VPI) in pulmonary adenocarcinoma manifesting as sub-solid nodules (SSN). Methods: A retrospective analysis was conducted on clinical and CT imaging features from 164 patients with SSN lung adenocarcinoma confirmed by surgical pathology. Patients were divided into the VPI-positive and VPI-negative groups. The clinical and CT imaging features between the two groups were compared, and independent risk factors for VPI in lung adenocarcinoma were identified via multivariate logistic regression analysis. The predictive performance of models was evaluated using the receiver operating characteristic curve and the area under the curve (AUC). Results: The solid component percentage, nodule and pleura relationship, and adjacent pleural thickening were identified as independent risk factors for VPI. The combined model incorporating these three factors demonstrated the highest predictive efficacy (AUC = 0.816), outperforming models based on any single factor. Conclusion: The solid component percentage, nodule and pleura relationship classification, and adjacent pleural thickening were identified as independent risk factors for VPI in SSN lung adenocarcinoma. The model combining these three factors demonstrates favorable predictive performance for VPI in SSN lung adenocarcinoma.