Dual artificial intelligence-assisted diagnosis and treatment for patients with multiple primary lung cancer_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

CAI Rongqiang ¹ , ZHONG Kaize ² , LIU Jikuan ² , LI Xin ¹ , PEI Baoxiang ² ,  ZHANG Kang ²

1. School of Clinical Medicine, Jining Medical University, Jining, 272000, Shandong, P.R.China;
2. Department of Thoracic Surgery, Jining No.1 People’s Hospital, Jining, 272000, Shandong, P.R.China;

Corresponding author：

ZHANG Kang, Email: zhangkang917@163.com

Keywords：

Artificial intelligence; multiple primary lung cancer; three dimensional computed tomographic bronchoangiography (3D-CTBA); segmentectomy

DOI：

10.7507/1007-4848.202012051

Video：

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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.

Citation： CAI Rongqiang, ZHONG Kaize, LIU Jikuan, LI Xin, PEI Baoxiang, ZHANG Kang. Dual artificial intelligence-assisted diagnosis and treatment for patients with multiple primary lung cancer. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2021, 28(5): 510-513. doi: 10.7507/1007-4848.202012051 Copy

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9.	张逊. 人工智能辅助肺癌诊疗一体化解决方案的临床实践与展望. 中国胸心血管外科临床杂志, 2019, 26(12): 1167-1170.
10.	Detterbeck FC, Chansky K, Groome P, et al. The IASLC lung cancer staging project: Methodology and validation used in the development of proposals for revision of the stage classification of NSCLC in the forthcoming (eighth) edition of the TNM classification of lung cancer. J Thorac Oncol, 2016, 11(9): 1433-1446.
11.	Yu YC, Hsu PK, Yeh YC, et al. Surgical results of synchronous multiple primary lung cancers: Similar to the stage-matched solitary primary lung cancers? Ann Thorac Surg, 2013, 96(6): 1966-1974.
12.	Chen H, Carrot-Zhang J, Zhao Y, et al. Genomic and immune profiling of pre-invasive lung adenocarcinoma. Nat Commun, 2019, 10(1): 5472.
13.	Ma K, Zhan C, Wang S, et al. Spread through air spaces (STAS): A new pathologic morphology in lung cancer. Clin Lung Cancer, 2019, 20(2): e158-e162.158-162.
14.	Li R, Li X, Xue R, et al. Early metastasis detected in patients with multifocal pulmonary ground-glass opacities (GGOs). Thorax, 2018, 73(3): 290-292.
15.	姜格宁, 陈昶, 朱余明, 等. 上海市肺科医院磨玻璃结节早期肺腺癌的诊疗共识(第一版). 中国肺癌杂志, 2018, 21(3): 147-159.
16.	Yamashita S, Chujo M, Kawano Y, et al. Clinical impact of segmentectomy compared with lobectomy under complete video-assisted thoracic surgery in the treatment of stage Ⅰ non-small cell lung cancer. J Surg Res, 2011, 166(1): 46-51.
17.	Tsutani Y, Miyata Y, Nakayama H, et al. Oncologic outcomes of segmentectomy compared with lobectomy for clinical stage ⅠA lung adenocarcinoma: Propensity score-matched analysis in a multicenter study. J Thorac Cardiovasc Surg, 2013, 146(2): 358-364.
18.	Suzuki K, Watanabe SI, Wakabayashi M, et al. A single-arm study of sublobar resection for ground-glass opacity dominant peripheral lung cancer. J Thorac Cardiovasc Surg, 2020. [Epub ahead of print].

1. Espinoza JL, Dong LT. Artificial intelligence tools for refining lung cancer screening. J Clin Med, 2020, 9(12): 3860.
2. Moertel CG, Dockerty MB, Baggenstoss AH. Multiple primary malignant neoplasmsⅠ. Introduction and presentation of data. Cancer, 1961, 14: 221-230.
3. Martini N, Melamed MR. Multiple primary lung cancers. J Thorac Cardiovasc Surg, 1975, 70(4): 606-612.
4. Henschke CI, Yankelevitz DF, et al. Survival of patients with stage Ⅰ lung cancer detected on CT screening. N Engl J Med, 2006, 355(17): 1763-1771.
5. Shimada Y, Saji H, Otani K, et al. Survival of a surgical series of lung cancer patients with synchronous multiple ground-glass opacities, and the management of their residual lesions. Lung Cancer, 2015, 88(2): 174-180.
6. Lv J, Zhu D, Wang X, et al. The value of prognostic factors for survival in synchronous multifocal lung cancer: A retrospective analysis of 164 patients. Ann Thorac Surg, 2018, 105(3): 930-936.
7. National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 2011, 365(5): 395-409.
8. Siegel RL, Miller KD, Fuchs HE, et al. Cancer statistics, 2021. CA Cancer J Clin, 2021, 71(1): 7-33.
9. 张逊. 人工智能辅助肺癌诊疗一体化解决方案的临床实践与展望. 中国胸心血管外科临床杂志, 2019, 26(12): 1167-1170.
10. Detterbeck FC, Chansky K, Groome P, et al. The IASLC lung cancer staging project: Methodology and validation used in the development of proposals for revision of the stage classification of NSCLC in the forthcoming (eighth) edition of the TNM classification of lung cancer. J Thorac Oncol, 2016, 11(9): 1433-1446.
11. Yu YC, Hsu PK, Yeh YC, et al. Surgical results of synchronous multiple primary lung cancers: Similar to the stage-matched solitary primary lung cancers? Ann Thorac Surg, 2013, 96(6): 1966-1974.
12. Chen H, Carrot-Zhang J, Zhao Y, et al. Genomic and immune profiling of pre-invasive lung adenocarcinoma. Nat Commun, 2019, 10(1): 5472.
13. Ma K, Zhan C, Wang S, et al. Spread through air spaces (STAS): A new pathologic morphology in lung cancer. Clin Lung Cancer, 2019, 20(2): e158-e162.158-162.
14. Li R, Li X, Xue R, et al. Early metastasis detected in patients with multifocal pulmonary ground-glass opacities (GGOs). Thorax, 2018, 73(3): 290-292.
15. 姜格宁, 陈昶, 朱余明, 等. 上海市肺科医院磨玻璃结节早期肺腺癌的诊疗共识(第一版). 中国肺癌杂志, 2018, 21(3): 147-159.
16. Yamashita S, Chujo M, Kawano Y, et al. Clinical impact of segmentectomy compared with lobectomy under complete video-assisted thoracic surgery in the treatment of stage Ⅰ non-small cell lung cancer. J Surg Res, 2011, 166(1): 46-51.
17. Tsutani Y, Miyata Y, Nakayama H, et al. Oncologic outcomes of segmentectomy compared with lobectomy for clinical stage ⅠA lung adenocarcinoma: Propensity score-matched analysis in a multicenter study. J Thorac Cardiovasc Surg, 2013, 146(2): 358-364.
18. Suzuki K, Watanabe SI, Wakabayashi M, et al. A single-arm study of sublobar resection for ground-glass opacity dominant peripheral lung cancer. J Thorac Cardiovasc Surg, 2020. [Epub ahead of print].

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Dual artificial intelligence-assisted diagnosis and treatment for patients with multiple primary lung cancer

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