Clinical application of artificial intelligence to lung nodules diagnosis in regional medical center
10.7507/1007-4848.202102021
- VernacularTitle:区域医疗中心人工智能辅助诊断肺结节的临床应用
- Author:
Yutong XING
1
;
Jiancheng LIU
1
;
Baichen SUN
1
;
Lingling HONG
1
;
Xiaojun ZHANG
1
;
Jianqian FU
1
;
Guojun GENG
2
,
3
;
Zhenlong LI
1
;
Jie JIANG
2
,
3
Author Information
1. Multidisciplinary Team for Lung Nodules, Xiamen Fifth Hospital, Xiamen, 361101, Fujian, P.R.China
2. 1. Multidisciplinary Team for Lung Nodules, Xiamen Fifth Hospital, Xiamen, 361101, Fujian, P.R.China
3. 2. Department of Thoracic Surgery, First Affiliated Hospital of Xiamen University, Xiamen, 361000, Fujian, P.R.China
- Publication Type:Journal Article
- Keywords:
Regional medical center;
pulmonary nodule;
artificial intelligence (AI);
auxiliary diagnosis system;
multidisciplinary team (MDT)
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2021;28(10):1178-1182
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the efficacy of artificial intelligence (AI) detection on pulmonary nodule compared with multidisciplinary team (MDT) in regional medical center. Methods We retrospectively analyzed the clinical data of 102 patients with lung nodules in the Xiamen Fifth Hospital from April to December 2020. There were 57 males and 45 females at age of 36-90 (48.8±11.6) years. The preoperative chest CT was imported into AI system to record the detected lung nodules. The detection rate of pulmonary nodules by AI system was calculated, and the sensitivity, specificity of AI in the different diagnosis of benign and malignant pulmonary was calculated and compared with manual film reading by MDT. Results A total of 322 nodules were detected by AI software system, and 305 nodules were manually detected by physicians (P<0.05). Among them, 113 pulmonary nodules were diagnosed by pathologist. Thirty-eight of 40 lung cancer nodules were AI high-risk nodules, the sensitivity was 95.0%, and 25 of 73 benign nodules were AI high-risk nodules, the specificity was 65.8%. Lung cancer nodules were correctly diagnosed by MDT, but benign nodules were still considered as lung cancer at the first diagnosis in 10 patients. Conclusion AI assisted diagnosis system has strong performance in the detection of pulmonary nodules, but it can not content itself with clinical needs in the differentiation of benign and malignant pulmonary nodules. The artificial intelligence system can be used as an auxiliary tool for MDT to detect pulmonary nodules in regional medical center.
