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目的 评估肺部结节慢性炎症对外周血循环异常细胞（CAC）及肺结节人工智能诊断系统（PNAIDS）诊断效能的影响，探讨慢性炎症是否为两种诊断工具准确性的潜在干扰因素，为优化肺结节患者的临床诊断策略提供参考。方法 收集2023年5月到2025年12月郑州大学第一附属医院经病理确诊的肺结节患者250例，分析CAC计数、CT影像特征、血液学检查结果、人口学特征及结节病理类型。采用PNAIDS评估结节性质，并比较良性与恶性结节之间，以及良性结节中慢性炎症与非慢性炎症亚组之间CAC和PNAIDS的诊断表现。同时结合血常规炎症指标进行分析，并采用受试者工作特征（ROC）曲线评价CAC与PNAIDS的诊断效能。结果CAC阳性率在良性与恶性结节之间差异有统计学意义（P=0.005）。在良性结节中，CAC阳性率在慢性炎症与非慢性炎症亚组之间差异有统计学意义（P=0.002），而PNAIDS阳性率在两组之间差异无统计学意义（P=0.225）。嗜酸性粒细胞减少患者的CAC检出率高于正常组（90.00%vs56.63%，P=0.042）。ROC分析显示，排除慢性炎症病例后CAC的诊断效能有所提高。结论 慢性炎症可能影响CAC在肺结节良恶性鉴别中的诊断表现，而对PNAIDS的影响相对有限。CAC联合PNAIDS有助于提高肺结节良恶性鉴别的诊断效能。
Abstract：Objective To evaluate the impact of chronic inflammation in pulmonary nodules on the diagnostic efficacy of circulating abnormal cells (CAC) and the pulmonary nodule with an artificial intelligence diagnostic system (PNAIDS)， and to explore whether chronic inflammation is a potential interfering factor affecting the accuracy of these two diagnostic tools， so as to provide evidence for optimizing the clinical diagnostic strategies in patients with pulmonary nodules. Methods A total of 250 patients with pathologically confirmed pulmonary nodules admitted to the First Affiliated Hospital of Zhengzhou University from May 2023 to December 2025 were included. CAC counts， CT imaging features， hematological examination results， demographic characteristics， and pathological subtypes of nodules were collected and analyzed. PNAIDS was used to judge the benign or malignant nature of pulmonary nodules. The diagnostic efficacy of CAC and PNAIDS was compared between benign and malignant nodules， as well as between chronic inflammation and non-chronic inflammation subgroups of benign nodules. Peripheral blood inflammatory markers from routine blood tests were also analyzed. Receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic efficacy of CAC and PNAIDS. Results The positive rate of CAC differed significantly between benign and malignant nodules (P = 0.005). Within benign nodules， CAC positive rates showed statistically significant differences between the chronic inflammation subgroup and non-chronic inflammation subgroup (P = 0.002)， whereas no intergroup difference in PNAIDS positive rate was found (P = 0.225). Patients with decreased eosinophil counts showed a higher CAC detection rate than those with normal eosinophil levels (90.00% vs. 56.63%， P = 0.042). ROC curve analysis showed that the diagnostic efficacy of CAC was improved after excluding cases with chronic inflammatory nodules. Conclusion Chronic inflammation may influence the diagnostic efficacy of CAC in differentiating benign and malignant pulmonary nodules， while its effect on PNAIDS appears to be limited. The combination of CAC and PNAIDS may improve the diagnostic efficacy for distinguishing benign from malignant pulmonary nodules.
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基本信息:
中图分类号:R563
引用信息:
[1]李浩楠,方晓琨,李宜真,等.肺部结节慢性炎症对外周血循环异常细胞及肺结节人工智能诊断系统诊断效能的影响[J].诊断病理学杂志().
基金信息:
国家自然科学基金（81570204）; 河南省中青年卫生健康科技创新领军人才培养项目（YXKC2021010）
2026-08-19
2026-08-19
2026-08-19