Dual artificial intelligence-assisted diagnosis and treatment for patients with multiple primary lung cancer
- VernacularTitle:双人工智能在多原发肺癌诊治中的应用
- Author:
Rongqiang CAI
1
;
Kaize ZHONG
2
,
3
;
Jikuan LIU
2
,
3
;
Xin LI
1
;
Baoxiang PEI
2
,
3
;
Kang ZHANG
2
,
3
Author Information
1. School of Clinical Medicine, Jining Medical University, Jining, 272000, Shandong, P.R.China
2. Department of Thoracic Surgery, Jining No.1 People&rsquo
3. s Hospital, Jining, 272000, Shandong, P.R.China
- Publication Type:Journal Article
- Keywords:
Artificial intelligence;
multiple primary lung cancer;
three dimensional computed tomographic bronchoangiography (3D-CTBA);
segmentectomy
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2021;28(05):510-513
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of artificial intelligence (AI) diagnostic imaging system and three dimensional computed tomographic bronchoangiography (3D-CTBA) surgical planning system in the management of multiple primary lung cancer (MPLC). Methods The clinical data of 53 patients with MPLC treated surgically in our hospital from January 2018 to August 2020 were retrospectively analyzed, including 16 males and 37 females, with a median age of 60 (39-75) years. The patients' preoperative CT was analyzed by AI and manually, and the data of patients who underwent 3D-CTBA were compiled to evaluate the value of AI and 3D-CTBA in the diagnosis and treatment of MPLC, respectively. Results The sensitivity of AI screening for MPLC was 84.91%. The sensitivity (91.90% vs. 83.78%) and accuracy (85.60% vs. 84.00%) of AI diagnosis of high-risk MPLC infiltrative lesions were better than those of manual diagnosis. 3D-CTBA was used for planning the surgery in 12 patients, and the intraoperative situation was generally consistent with the reconstructed results. Conclusion AI is of high value in identifying infiltrative lesions of MPLC. 3D-CTBA reconstruction of anatomical structures is accurate and can guide preoperative planning.
