Exploration of CT imaging features of cystic pulmonary nodules and establishment of a prediction model for benign and malignant pulmonary nodules_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

YAO Yi , HU Qiuxia , YANG Yanhui , XIE Xiaoyang , WANG Yi , LI Xiaoliang , LUO Lei ,  LI Ji

Department of Thoracic Surgery, The First People's Hospital of Neijiang, Neijiang Hospital Affiliated to Chongqing Medical University, Neijiang, 641000, Sichuan, P. R. China;

Corresponding author：

LI Ji, Email: Jimlee0832@163.com

Keywords：

Cystic lung cancer; benign and malignant diagnosis; prediction model; imaging features

DOI：

10.7507/1007-4848.202203071

Video：

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Objective To explore the CT imaging features and independent risk factors for cystic pulmonary nodules and establish a malignant probability prediction model. Methods The patients with cystic pulmonary nodules admitted to the Department of Thoracic Surgery of the First People's Hospital of Neijiang from January 2017 to February 2022 were retrospectively enrolled. They were divided into a malignant group and a benign group according to the pathological results. The clinical data and preoperative chest CT imaging features of the two groups were collected, and the independent risk factors for malignant cystic pulmonary nodules were screened out by logistic regression analysis, so as to establish a prediction model for benign and malignant cystic pulmonary nodules. Results A total of 107 patients were enrolled. There were 76 patients in the malignant group, including 36 males and 40 females, with an average age of 59.65±11.74 years. There were 31 patients in the benign group, including 16 males and 15 females, with an average age of 58.96±13.91 years. Multivariate logistic analysis showed that the special CT imaging features such as cystic wall nodules [OR=3.538, 95%CI (1.231, 10.164), P=0.019], short burrs [OR=4.106, 95%CI (1.454, 11.598), P=0.008], cystic wall morphology [OR=6.978, 95%CI (2.374, 20.505), P<0.001], and the number of cysts [OR=4.179, 95%CI (1.438, 12.146), P=0.009] were independent risk factors for cystic lung cancer. A prediction model was established: P=e^x/(1+e^x), X=–2.453+1.264×cystic wall nodules+1.412×short burrs+1.943×cystic wall morphology+1.430×the number of cysts. The area under the receiver operating charateristic curve was 0.830, the sensitivity was 82.9%, and the specificity was 74.2%. Conclusion Cystic wall nodules, short burrs, cystic wall morphology, and the number of cysts are the independent risk factors for cystic lung cancer, and the established prediction model can be used as a screening method for cystic pulmonary nodules.

Citation： YAO Yi, HU Qiuxia, YANG Yanhui, XIE Xiaoyang, WANG Yi, LI Xiaoliang, LUO Lei, LI Ji. Exploration of CT imaging features of cystic pulmonary nodules and establishment of a prediction model for benign and malignant pulmonary nodules. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2024, 31(2): 249-254. doi: 10.7507/1007-4848.202203071 Copy

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13.	李运, 陈克终, 隋锡朝, 等. 孤立性肺结节良恶性判断数学预测模型的建立. 北京大学学报(医学版), 2011, 43(3): 450-454.
14.	Scholten ET, Horeweg N, de Koning HJ, et al. Computed tomographic characteristics of interval and post screen carcinomas in lung cancer screening. Eur Radiol, 2015, 25(1): 81-88.
15.	Elia S, Loprete S, De Stefano A, et al. Does aggressive management of solitary pulmonary nodules pay off? Breathe (Sheff), 2019, 15(1): 15-23.
16.	刘富富, 李惠民, 任华, 等. 囊腔性肺癌的超高分辨率CT研究. 中国医学计算机成像杂志, 2019, 25(6): 530-534.
17.	Tan Y, Gao J, Wu C, et al. CT characteristics and pathologic basis of solitary cystic lung cancer. Radiology, 2019, 291(2): 495-501.
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19.	Shen Y, Xu X, Zhang Y, et al. Lung cancers associated with cystic airspaces: CT features and pathologic correlation. Lung Cancer, 2019, 135: 110-115.
20.	Shen Y, Zhang Y, Guo Y, et al. Prognosis of lung cancer associated with cystic airspaces: A propensity score matching analysis. Lung Cancer, 2021, 159: 111-116.
21.	Ma J, Yang YL, Wang Y, et al. Relationship between computed tomography morphology and prognosis of patients with stage Ⅰnon-small cell lung cancer. Onco Targets Ther, 2017, 10: 2249-2256.
22.	张鹏举, 李天然, 陶雪敏, 等. 磨玻璃结节早期贴壁生长为主型浸润性肺腺癌与其他病理亚型的CT特征分析. 中华放射学杂志, 2021, 55(7): 739-744.
23.	Araki T, Nishino M, Gao W, et al. Pulmonary cysts identified on chest CT: Are they part of aging change or of clinical significance? Thorax, 2015, 70(12): 1156-1162.
24.	Hohberger LA, Schroeder DR, Bartholmai BJ, et al. Correlation of regional emphysema and lung cancer: A lung tissue research consortium-based study. J Thorac Oncol, 2014, 9(5): 639-645.
25.	Ng CSH, Chu CM, Lo CK, et al. Hybrid operating room Dyna-computed tomography combined image-guided electromagnetic navigation bronchoscopy dye marking and hookwire localization video-assisted thoracic surgery metastasectomy. Interact Cardiovasc Thorac Surg, 2018, 26(2): 338-340.
26.	Fintelmann FJ, Brinkmann JK, Jeck WR, et al. Lung cancers associated with cystic airspaces: Natural history, pathologic correlation, and mutational analysis. J Thorac Imaging, 2017, 32(3): 176-188.
27.	MacMahon H, Naidich DP, Goo JM, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: From the Fleischner Society 2017. Radiology, 2017, 284(1): 228-243.
28.	Dyer SC, Bartholmai BJ, Koo CW. Implications of the updated Lung CT Screening Reporting and Data System (Lung-RADS version 1. 1) for lung cancer screening. J Thorac Dis, 2020, 12(11): 6966-6977.

1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2021, 71(3): 209-249.
2. 郭俊唐, 梁朝阳, 初向阳, 等. 薄壁空洞性肺癌: 24例病例分析及文献回顾. 中国肺癌杂志, 2014, 17(7): 553-556.
3. Anderson HJ, Pierce JW. Carcinoma of the bronchus presenting as thin-walled cysts. Thorax, 1954, 9(2): 100-105.
4. Farooqi AO, Cham M, Zhang L, et al. Lung cancer associated with cystic airspaces. AJR Am J Roentgenol, 2012, 199(4): 781-786.
5. Watanabe Y, Kusumoto M, Yoshida A, et al. Surgically resected solitary cavitary lung adenocarcinoma: Association between clinical, pathologic, and radiologic findings and prognosis. Ann Thorac Surg, 2015, 99(3): 968-974.
6. 赫捷, 李霓, 陈万青, 等. 中国肺癌筛查与早诊早治指南(2021, 北京). 中华肿瘤杂志, 2021, 43(3): 243-268.
7. National Comprehensive Cancer Network. NCCN clinical practice guidelines in oncology: Lung cancer screening version 1.2021. https://www.nccn.org/. [Accessed on 2022-02-10].
8. Xue XY, Liu YX, Wang KF, et al. Computed tomography for the diagnosis of solitary thin-walled cavity lung cancer. Clin Respir J, 2015, 9(4): 392-398.
9. Meyer M, Vliegenthart R, Henzler T, et al. Management of progressive pulmonary nodules found during and outside of CT lung cancer screening studies. J Thorac Oncol, 2017, 12(12): 1755-1765.
10. Swensen SJ, Silverstein MD, Ilstrup DM, et al. The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules. Arch Intern Med, 1997, 157(8): 849-855.
11. Gould MK, Ananth L, Barnett PG, et al. A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules. Chest, 2007, 131(2): 383-388.
12. McWilliams A, Tammemagi MC, Mayo JR, et al. Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med, 2013, 369(10): 910-919.
13. 李运, 陈克终, 隋锡朝, 等. 孤立性肺结节良恶性判断数学预测模型的建立. 北京大学学报(医学版), 2011, 43(3): 450-454.
14. Scholten ET, Horeweg N, de Koning HJ, et al. Computed tomographic characteristics of interval and post screen carcinomas in lung cancer screening. Eur Radiol, 2015, 25(1): 81-88.
15. Elia S, Loprete S, De Stefano A, et al. Does aggressive management of solitary pulmonary nodules pay off? Breathe (Sheff), 2019, 15(1): 15-23.
16. 刘富富, 李惠民, 任华, 等. 囊腔性肺癌的超高分辨率CT研究. 中国医学计算机成像杂志, 2019, 25(6): 530-534.
17. Tan Y, Gao J, Wu C, et al. CT characteristics and pathologic basis of solitary cystic lung cancer. Radiology, 2019, 291(2): 495-501.
18. Jung W, Cho S, Yum S, et al. Stepwise disease progression model of subsolid lung adenocarcinoma with cystic airspaces. Ann Surg Oncol, 2020, 27(11): 4394-4403.
19. Shen Y, Xu X, Zhang Y, et al. Lung cancers associated with cystic airspaces: CT features and pathologic correlation. Lung Cancer, 2019, 135: 110-115.
20. Shen Y, Zhang Y, Guo Y, et al. Prognosis of lung cancer associated with cystic airspaces: A propensity score matching analysis. Lung Cancer, 2021, 159: 111-116.
21. Ma J, Yang YL, Wang Y, et al. Relationship between computed tomography morphology and prognosis of patients with stage Ⅰnon-small cell lung cancer. Onco Targets Ther, 2017, 10: 2249-2256.
22. 张鹏举, 李天然, 陶雪敏, 等. 磨玻璃结节早期贴壁生长为主型浸润性肺腺癌与其他病理亚型的CT特征分析. 中华放射学杂志, 2021, 55(7): 739-744.
23. Araki T, Nishino M, Gao W, et al. Pulmonary cysts identified on chest CT: Are they part of aging change or of clinical significance? Thorax, 2015, 70(12): 1156-1162.
24. Hohberger LA, Schroeder DR, Bartholmai BJ, et al. Correlation of regional emphysema and lung cancer: A lung tissue research consortium-based study. J Thorac Oncol, 2014, 9(5): 639-645.
25. Ng CSH, Chu CM, Lo CK, et al. Hybrid operating room Dyna-computed tomography combined image-guided electromagnetic navigation bronchoscopy dye marking and hookwire localization video-assisted thoracic surgery metastasectomy. Interact Cardiovasc Thorac Surg, 2018, 26(2): 338-340.
26. Fintelmann FJ, Brinkmann JK, Jeck WR, et al. Lung cancers associated with cystic airspaces: Natural history, pathologic correlation, and mutational analysis. J Thorac Imaging, 2017, 32(3): 176-188.
27. MacMahon H, Naidich DP, Goo JM, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: From the Fleischner Society 2017. Radiology, 2017, 284(1): 228-243.
28. Dyer SC, Bartholmai BJ, Koo CW. Implications of the updated Lung CT Screening Reporting and Data System (Lung-RADS version 1. 1) for lung cancer screening. J Thorac Dis, 2020, 12(11): 6966-6977.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Exploration of CT imaging features of cystic pulmonary nodules and establishment of a prediction model for benign and malignant pulmonary nodules

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