Division of Pulmonology, Department of Internal Medicine, Allergy and Critical Care Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea.
Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea.
PLoS One. 2023 Mar 10;18(3):e0281690. doi: 10.1371/journal.pone.0281690. eCollection 2023.
Detection of early lung cancer using chest radiograph remains challenging. We aimed to highlight the benefit of using artificial intelligence (AI) in chest radiograph with regard to its role in the unexpected detection of resectable early lung cancer.
Patients with pathologically proven resectable lung cancer from March 2020 to February 2022 were retrospectively analyzed. Among them, we included patients with incidentally detected resectable lung cancer. Because commercially available AI-based lesion detection software was integrated for all chest radiographs in our hospital, we reviewed the clinical process of detecting lung cancer using AI in chest radiographs.
Among the 75 patients with pathologically proven resectable lung cancer, 13 (17.3%) had incidentally discovered lung cancer with a median size of 2.6 cm. Eight patients underwent chest radiograph for the evaluation of extrapulmonary diseases, while five underwent radiograph in preparation of an operation or procedure concerning other body parts. All lesions were detected as nodules by the AI-based software, and the median abnormality score for the nodules was 78%. Eight patients (61.5%) consulted a pulmonologist promptly on the same day when the chest radiograph was taken and before they received the radiologist's official report. Total and invasive sizes of the part-solid nodules were 2.3-3.3 cm and 0.75-2.2 cm, respectively.
This study demonstrates actual cases of unexpectedly detected resectable early lung cancer using AI-based lesion detection software. Our results suggest that AI is beneficial for incidental detection of early lung cancer in chest radiographs.
使用胸部 X 线摄影检测早期肺癌仍然具有挑战性。我们旨在强调人工智能（AI）在胸部 X 线摄影中的作用，即其在意外检测可切除的早期肺癌方面的益处。
回顾性分析 2020 年 3 月至 2022 年 2 月期间经病理证实为可切除肺癌的患者。其中，我们纳入了意外发现的可切除肺癌患者。由于我们医院所有的胸部 X 光片都集成了商用的基于 AI 的病灶检测软件，因此我们回顾了使用胸部 X 光片 AI 检测肺癌的临床过程。
在 75 例经病理证实为可切除肺癌的患者中，13 例（17.3%）为意外发现的肺癌，中位肿瘤大小为 2.6cm。8 例患者因评估肺外疾病而行胸部 X 光检查，5 例患者在准备其他部位手术或操作时进行 X 光检查。所有病灶均被 AI 软件检测为结节，结节的平均异常评分中位数为 78%。8 例患者（61.5%）在同一天拍摄胸部 X 光片时，即在收到放射科医生正式报告之前，立即咨询了肺病专家。部分实性结节的总直径和浸润直径分别为 2.3-3.3cm 和 0.75-2.2cm。
本研究展示了使用基于 AI 的病灶检测软件意外检测到的可切除早期肺癌的实际病例。我们的结果表明，AI 有助于在胸部 X 光片中意外检测早期肺癌。
