Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, 363, Dongbaekjukjeon-Daero, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16995, South Korea.
Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-Ro, Seodaemun-Gu, Seoul, 03722, South Korea.
Sci Rep. 2024 Aug 23;14(1):19624. doi: 10.1038/s41598-024-70780-1.
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from March to December 2021 were included retrospectively. The PPV was evaluated according to the true-positive (TP) and false-positive (FP) diagnosis determined by radiologists. To know the factors that might influence the results, logistic regression with generalized estimating equation was used. Among a total of 87,658 CXRs, 308 CXRs with 331 pneumothoraces from 283 patients were finally included. The overall PPV of AI about pneumothorax was 41.1% (TF:FP = 136:195). The PA view (odds ratio [OR], 29.837; 95% confidence interval [CI], 15.062-59.107), high abnormality score (OR, 1.081; 95% CI, 1.066-1.097), large amount of pneumothorax (OR, 1.005; 95% CI, 1.003-1.007), presence of ipsilateral atelectasis (OR, 3.508; 95% CI, 1.509-8.156) and a small amount of ipsilateral pleural effusion (OR, 5.277; 95% CI, 2.55-10.919) had significant effects on the increasing PPV. Therefore, PPV for pneumothorax diagnosis using AI can vary based on patients' factors, image-acquisition protocols, and the presence of concurrent lesions on CXR.
本研究评估了人工智能（AI）在检测胸部 X 线片（CXR）中气胸的阳性预测值（PPV）及其影响因素。回顾性纳入 2021 年 3 月至 12 月间由商业 AI 软件确定 CXR 存在气胸的患者。根据放射科医生确定的真阳性（TP）和假阳性（FP）诊断来评估 PPV。为了了解可能影响结果的因素，使用广义估计方程的逻辑回归进行分析。在总共 87658 张 CXR 中，最终纳入了 283 名患者的 308 张 CXR 和 331 例气胸。AI 对气胸的总体 PPV 为 41.1%（TP:FP=136:195）。PA 视图（比值比[OR]，29.837；95%置信区间[CI]，15.062-59.107）、高异常评分（OR，1.081；95%CI，1.066-1.097）、大量气胸（OR，1.005；95%CI，1.003-1.007）、同侧肺不张（OR，3.508；95%CI，1.509-8.156）和少量同侧胸腔积液（OR，5.277；95%CI，2.55-10.919）对增加的 PPV 有显著影响。因此，使用 AI 诊断气胸的 PPV 可能会因患者因素、图像采集协议以及 CXR 上同时存在的病变而有所不同。
