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伴微乳头和/或实性成分肺腺癌高分辨率CT表现及其病理侵袭性的预测因素 被引量:2

High resolution CT manifestations of lung adenocarcinoma with micropapillae and/or solid components and predictors of pathological invasiveness
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摘要 目的观察伴微乳头和/或实性成分肺腺癌的高分辨率CT(HRCT)表现,分析其病理侵袭性的预测因素。方法回顾性分析208例经术后病理证实伴微乳头和/或实性成分浸润性肺腺癌患者的HRCT资料,依据HRCT显示有无气腔播散、脉管侵犯及胸膜侵犯等分为病理非侵袭性肺腺癌(PNLA)及病理侵袭性肺腺癌(PILA);采用单因素分析及二元logistic回归分析筛选伴微乳头和/或实性成分肺腺癌病理侵袭性的预测因素。结果208例中,126例PNLA(PNLA组)、82例PILA(PILA组);组间瘤肺界面、病灶胸膜下分布、支气管阳性征及胸膜凹陷征差异均有统计学意义(P均<0.05)。胸膜凹陷征及支气管阳性征为伴微乳头和/或实性成分肺腺癌病理侵袭性的独立预测因素(P均<0.05)。结论胸膜凹陷征及支气管阳性征是伴微乳头和/或实性成分肺腺癌存在病理侵袭性的独立预测因素。 Objective To observe high resolution CT(HRCT)manifestations of lung adenocarcinoma with micropapillae and/or solid components,and to analyze its predictors of pathological invasiveness.Methods HRCT data of 208 invasive lung adenocarcinoma patients with micropapillae and/or solid components confirmed by postoperative pathology were retrospectively analyzed.The patients were classified into pathological noninvasive lung adenocarcinoma(PNLA)and pathological invasive lung adenocarcinoma(PILA)according to whether spread through air space,vascular invasion and pleural invasion were observed on HRCT or not.Univariate and binary logistic regression analyses were used to screen factors related to pathologic invasiveness of lung adenocarcinoma with micropapillae and/or solid components.Results Among 208 patients,126 cases were found with PNLA(PNLA group),and 82 cases were found with PILA(PILA group).There were statistical differences of tumor lung interface,subpleural distribution of lesions,bronchial positive sign and pleural indentation between groups(all P<0.05).Bronchial positive sign and pleural indentation were both independent predictors of pathological invasiveness in lung adenocarcinoma with micropapillace and/or solid structures(both P<0.05).Conclusion Bronchial positive sign and pleural indentation were independent predictors of pathological invasiveness in lung adenocarcinoma with micropapillace and/or solid components.
作者 王芬 袁梅 朱佳佳 张腾 仲艳 徐海 俞同福 WANG Fen;YUAN Mei;ZHU Jiajia;ZHANG Teng;ZHONG Yan;XU Hai;YU Tongfu(Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China)
出处 《中国介入影像与治疗学》 北大核心 2022年第3期148-152,共5页 Chinese Journal of Interventional Imaging and Therapy
基金 国家自然科学基金青年基金(81801693)。
关键词 肺肿瘤 腺癌 体层摄影术 X线计算机 病理学 lung neoplasms adenocarcinoma tomography,X-ray computed pathology
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