中国现代医学杂志2026，Vol.36Issue(11)：97-102,6.DOI:10.3969/j.issn.1005-8982.2026.11.014
基于增强CT影像的人工智能模型在肺腺癌浸润性评估中的诊断价值
Diagnostic value of an artificial intelligence model based on contrast-enhanced CT imaging in the assessment of lung adenocarcinoma invasiveness
摘要
Abstract
Objective To investigate the diagnostic value of an artificial intelligence(AI)model based on contrast-enhanced CT imaging in the assessment of lung adenocarcinoma invasiveness.Methods Patients who visited Suzhou Municipal Hospital between January 2022 and January 2025,presented with pulmonary nodules on chest CT scans,and were scheduled for surgical resection were enrolled as the study subjects.All patients underwent contrast-enhanced CT scans preoperatively,and the scanned images were immediately imported into an AI-assisted diagnostic system for analysis.The system automatically generated the predicted probability of whether the nodule was an invasive lung adenocarcinoma,along with quantitative parameters.Using postoperative pathological diagnosis as the gold standard,the preoperative predictive efficacy of AI-assisted contrast-enhanced CT scans for assessing the invasiveness of lung adenocarcinoma was evaluated.Results Among 141 patients confirmed with lung adenocarcinoma by surgery,the invasive group accounted for 68.09%(96/141).The comparisons of age,BMI,gender composition,smoking history rate,drinking history rate,residential composition,educational level composition,and kurtosis between the invasive and non-invasive groups showed no statistically significant differences(P>0.05).In contrast,comparisons of volume,mass,maximum CT value,minimum CT value,standard deviation of CT value,maximum cross-sectional area,3D longest diameter,average long-short axis diameter,and the quantitative parameter entropy in the invasive group showed statistically significant differences(P<0.05),with all values higher in the invasive group than in the non-invasive group.Among the 141 patients,96 were classified as invasive.Conventional contrast-enhanced CT detected positivity in 79 cases,while AI-assisted contrast-enhanced CT detected positivity in 92 cases.The sensitivity of contrast-enhanced CT scan for diagnosing the invasiveness of lung adenocarcinoma was 82.29%(95%CI:0.732,0.893)(79/96),the specificity was 75.56%(95%CI:0.605,0.871)(34/45),and the accuracy was 80.14%(95%CI:0.726,0.861)(113/141).The sensitivity of AI-assisted contrast-enhanced CT for detecting the invasiveness of lung adenocarcinoma was 95.83%(95%CI:0.897,0.989)(92/96),the specificity was 88.89%(95%CI:0.759,0.963)(40/45),and the accuracy was 93.62%(95%CI:0.880,0.970)(132/141).Conclusion The combination of artificial intelligence and contrast-enhanced CT enables the accurate quantification of parameters related to pulmonary nodules,thereby improving the accuracy,sensitivity,and specificity in the diagnosis of lung adenocarcinoma invasiveness.关键词
肺腺癌/肺结节浸润性/人工智能/增强CT扫描/诊断效能Key words
lung adenocarcinoma/invasiveness of pulmonary nodules/artificial intelligence/contrast-enhanced CT scan/diagnostic efficacy分类
医药卫生引用本文复制引用
刘晓斐,陈孟露,武悦..基于增强CT影像的人工智能模型在肺腺癌浸润性评估中的诊断价值[J].中国现代医学杂志,2026,36(11):97-102,6.基金项目
安徽省自然科学基金(2308085QH291) （2308085QH291）
