Establishment and validation of a model for predicting infiltration of pulmonary subsolid nodules by circulating tumor cells combined with imaging features_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

MA Xiang ^1,2,3 , LIN Ruijiang ^2,3 , MA Minjie ^2,3 , CAO Xiong ^2,3 , LIANG Qiuhao ^1,2,3 , HAN Zhiwei ^1,2,3 , XU Shangqing ^2,3 ,  HAN Biao ^1,2,3

1. The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, P. R. China;
2. Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, P. R. China;
3. Major in R & D and Application of Key Technologies in Thoracic Surgery Gansu International Science and Technology Cooperation Base, Lanzhou, 730000, P. R. China;

Corresponding author：

HAN Biao, Email: hanbiao66@163.com

Keywords：

Pulmonary subsolid nodules; clinical radiological features; circulating tumor cells; tumor invasiveness

DOI：

10.7507/1007-4848.202204041

Video：

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Objective To evaluate the clinical radiological features combined with circulating tumor cells (CTCs) in the diagnosis of invasiveness evaluation of subsolid nodules in lung cancers. Methods Clinical data of 296 patients from the First Hospital of Lanzhou University between February 2019 and February 2021 were retrospectively included. There were 130 males and 166 females with a median age of 62.00 years. Patients were randomly divided into a training set and an internal validation set with a ratio of 3 : 1 by random number table method. The patients were divided into two groups: a preinvasive lesion group (atypical adenomatoid hyperplasia and adenocarcinoma in situ) and an invasive lesion group (microinvasive adenocarcinoma and invasive adenocarcinoma). Independent risk factors were selected by regression analysis of training set and a Nomogram prediction model was constructed. The accuracy and consistency of the model were verified by the receiver operating characteristic curve and calibration curve respectively. Subgroup analysis was conducted on nodules with different diameters to further verify the performance of the model. Specific performance metrics, including sensitivity, specificity, positive predictive value, negative predictive value and accuracy at the threshold were calculated. Results Independent risk factors selected by regression analysis for subsolid nodules were age, CTCs level, nodular nature, lobulation and spiculation. The Nomogram prediction mode provided an area under the curve (AUC) of 0.914 (0.872, 0.956), outperforming clinical radiological features model AUC [0.856 (0.794, 0.917), P=0.003] and CTCs AUC [0.750 (0.675, 0.825), P=0.001] in training set. C-index was 0.914, 0.894 and corrected C-index was 0.902, 0.843 in training set and internal validation set, respectively. The AUC of the prediction model in training set was 0.902 (0.848, 0.955), 0.913 (0.860, 0.966) and 0.873 (0.730, 1.000) for nodule diameter of 5-20 mm, 10-20 mm and 21-30 mm, respectively. Conclusion The prediction model in this study has better diagnostic value, and is more effective in clinical diagnosis of diseases.

Citation： MA Xiang, LIN Ruijiang, MA Minjie, CAO Xiong, LIANG Qiuhao, HAN Zhiwei, XU Shangqing, HAN Biao. Establishment and validation of a model for predicting infiltration of pulmonary subsolid nodules by circulating tumor cells combined with imaging features. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2023, 30(2): 198-204. doi: 10.7507/1007-4848.202204041 Copy

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8.	刘佳, 李文武, 黄勇, 等. 表现为磨玻璃密度结节的肺腺癌浸润前病变与微浸润腺癌的多排螺旋CT影像学征象及其鉴别诊断价值. 中华肿瘤杂志, 2015, 37(8): 611-616.
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13.	Wilshire CL, Louie BE, Horton MP, et al. Comparison of outcomes for patients with lepidic pulmonary adenocarcinoma defined by 2 staging systems: A North American experience. J Thorac Cardiovasc Surg, 2016, 151(6): 1561-1568.
14.	何花, 胡文滕, 蔺瑞江, 等. CT特征联合肿瘤标志物预测肺磨玻璃结节肿瘤浸润性的回顾性队列研究. 中国胸心血管外科临床杂志, 2022, 29(9): 1113-1119.
15.	Zhai Y, Hui Z, Men Y, et al. Combined neat model for the prognosis of postoperative stage Ⅲ-N2 non-small cell lung cancer. Thorac Cancer, 2020, 11(9): 2610-2617.
16.	Yoshimura A, Uchino J, Hasegawa K, et al. Carcinoembryonic antigen and CYFRA 21-1 responses as prognostic factors in advanced non-small cell lung cancer. Transl Lung Cancer Res, 2019, 8(3): 227-234.
17.	Tomita M, Ayabe T, Maeda R, et al. Serum carcinoembryonic antigen level predicts cancer-specific outcomes of resected non-small cell lung cancer with interstitial pneumonia. World J Oncol, 2018, 9(5-6): 136-140.
18.	陈耿春, 李阳, 邱士军. 肺部小结节与浸润性肺癌的影像学相关性研究. 现代诊断与治疗, 2018, 29(24): 4010-4012.
19.	单文莉, 周围, 孔丹, 等. 肺腺癌CT征象与病理组织学亚型及分化程度的对照研究. 临床放射学杂志, 2019, 38(12): 2312-2316.
20.	黄海峡, 徐国厚, 左翔, 等. CT特征联合癌胚抗原对磨玻璃结节的浸润前和浸润性鉴别诊断价值的研究. 中国CT和MRI杂志, 2020, 18(10): 29-33.
21.	Miao Y, Zhang J, Zou J, et al. Correlation in histological subtypes with high resolution computed tomography signatures of early stage lung adenocarcinoma. Transl Lung Cancer Res, 2017, 6(1): 14-22.

1. Imielinski M, Berger AH, Hammerman PS, et al. Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell, 2012, 150(6): 1107-1120.
2. 方三高, 陈真伟, 魏建国. 2021年第5版WHO胸部肿瘤分类. 诊断病理学杂志, 2021, 28(7): 591-593, 607.
3. Li Q, Dai J, Zhang P, et al. Management of pulmonary ground glass nodules: Less is more. Ann Thorac Surg, 2021, 112(1): 1-2.
4. 郑慧, 李建玉, 王珊, 等. 基于肺磨玻璃结节CT征象的诊断模型列线图评估肺癌浸润性. 放射学实践, 2021, 36(4): 470-474.
5. Godoy MC, Sabloff B, Naidich DP. Subsolid pulmonary nodules: Imaging evaluation and strategic management. Curr Opin Pulm Med, 2012, 18(4): 304-312.
6. Seidelman JL, Myers JL, Quint LE. Incidental, subsolid pulmonary nodules at CT: Etiology and management. Cancer Imaging, 2013, 13(3): 365-373.
7. 孟庆成, 贾丙鑫, 张建伟, 等. 微浸润型肺腺癌的高分辨率CT表现. 中国医学影像学杂志, 2013, 21(7): 536-538, 542.
8. 刘佳, 李文武, 黄勇, 等. 表现为磨玻璃密度结节的肺腺癌浸润前病变与微浸润腺癌的多排螺旋CT影像学征象及其鉴别诊断价值. 中华肿瘤杂志, 2015, 37(8): 611-616.
9. Syrigos K, Fiste O, Charpidou A, et al. Circulating tumor cells count as a predictor of survival in lung cancer. Crit Rev Oncol Hematol, 2018, 125: 60-68.
10. Wang J, Wang K, Xu J, et al. Prognostic significance of circulating tumor cells in non-small-cell lung cancer patients: A meta-analysis. PLoS One, 2013, 8(11): e78070.
11. Gao Y, Ni X, Guo H, et al. Single-cell sequencing deciphers a convergent evolution of copy number alterations from primary to circulating tumor cells. Genome Res, 2017, 27(8): 1312-1322.
12. Yin W, Zhu J, Ma B, et al. Overcoming obstacles in pathological diagnosis of pulmonary nodules through circulating tumor cell enrichment. Small, 2020, 16(25): e2001695.
13. Wilshire CL, Louie BE, Horton MP, et al. Comparison of outcomes for patients with lepidic pulmonary adenocarcinoma defined by 2 staging systems: A North American experience. J Thorac Cardiovasc Surg, 2016, 151(6): 1561-1568.
14. 何花, 胡文滕, 蔺瑞江, 等. CT特征联合肿瘤标志物预测肺磨玻璃结节肿瘤浸润性的回顾性队列研究. 中国胸心血管外科临床杂志, 2022, 29(9): 1113-1119.
15. Zhai Y, Hui Z, Men Y, et al. Combined neat model for the prognosis of postoperative stage Ⅲ-N2 non-small cell lung cancer. Thorac Cancer, 2020, 11(9): 2610-2617.
16. Yoshimura A, Uchino J, Hasegawa K, et al. Carcinoembryonic antigen and CYFRA 21-1 responses as prognostic factors in advanced non-small cell lung cancer. Transl Lung Cancer Res, 2019, 8(3): 227-234.
17. Tomita M, Ayabe T, Maeda R, et al. Serum carcinoembryonic antigen level predicts cancer-specific outcomes of resected non-small cell lung cancer with interstitial pneumonia. World J Oncol, 2018, 9(5-6): 136-140.
18. 陈耿春, 李阳, 邱士军. 肺部小结节与浸润性肺癌的影像学相关性研究. 现代诊断与治疗, 2018, 29(24): 4010-4012.
19. 单文莉, 周围, 孔丹, 等. 肺腺癌CT征象与病理组织学亚型及分化程度的对照研究. 临床放射学杂志, 2019, 38(12): 2312-2316.
20. 黄海峡, 徐国厚, 左翔, 等. CT特征联合癌胚抗原对磨玻璃结节的浸润前和浸润性鉴别诊断价值的研究. 中国CT和MRI杂志, 2020, 18(10): 29-33.
21. Miao Y, Zhang J, Zou J, et al. Correlation in histological subtypes with high resolution computed tomography signatures of early stage lung adenocarcinoma. Transl Lung Cancer Res, 2017, 6(1): 14-22.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Establishment and validation of a model for predicting infiltration of pulmonary subsolid nodules by circulating tumor cells combined with imaging features

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