|
|
|
| Comparative analysis of the CT, clinical, and pathological features of patients with invasive lung adenocarcinoma positive and negative for spread through air spaces |
| ZHANG Liwei1, YUAN Guiping1, FANG Juanjuan1, TENG Minmin1, SONG Dewei1, YU Bo2, SHAO Yuanwei1 |
1. Department of Imaging Center, The Second People’s Hospital of Dezhou City, Dezhou 253000 China;
2. College of Mathematics and Big Data, Dezhou University, Dezhou 253000 China |
|
|
|
|
Abstract Objective To investigate the correlations of computed tomography (CT), clinical, and pathological features in patients with invasive lung adenocarcinoma positive and negative for spread through air spaces (STAS). Methods A total of 236 patients with invasive lung adenocarcinoma confirmed by surgery and pathology were selected, including 118 patients in STAS-positive group and 118 patients in STAS-negative group. The clinical data, CT signs, and pathological features of the two groups were collected and analyzed. Results There was a correlation between age and the occurrence of STAS. The age of the positive group was higher than that of the negative group. Smoking history and family history of tumor had no correlation with the occurrence of STAS. CT features signs such as nodule type and shape, tumor-lung interface, lobulation sign, spiculation sign, vacuole/cavity, air-bronchogram, pleural indentation sign, vascular changes, mean diameter of tumor, mean diameter of solid component, and the percentage of tumor solid components were significantly different between patients with and without STAS. The incidence of STAS in patients with solid nodules and partial solid nodules was significantly higher than that in patients with ground glass nodules. Multivariate analysis showed that the percentage of tumor solid components, air-bronchogram sign, lobulation sign, and tumor-lung interface were independent risk factors for predicting the occurrence of STAS. Conclusion The clinical data and CT signs of patients with invasive lung adenocarcinoma are related to the occurrence of STAS. CT signs such as the percentage of tumor solid components, air-bronchogram, lobulation sign, and tumor-lung interface are of great significance to STAS prediction. Our findings provide an important basis for selection of personalized clinical treatment plans.
|
|
Received: 25 March 2024
|
|
|
|
|
|
[1] 郑荣寿, 陈茹, 韩冰峰, 等. 2022年中国恶性肿瘤流行情况分析[J]. 中华肿瘤杂志，2024，46（3）：221-231.
Zheng RS, Chen R, Han BF, et al. Cancer incidence and mortality in China, 2022[J]. Chin J Oncol, 2024, 46（3）: 221-231.
[2] Shiono S, Yanagawa N. Spread through air spaces is a predictive factor of recurrence and a prognostic factor in stage I lung adenocarcinoma[J]. Interact Cardiovasc Thorac Surg, 2016, 23（4）: 567-572.
[3] Morimoto J, Nakajima T, Suzuki H, et al. Impact of free tumor clusters on prognosis after resection of pulmonary adenocarcinoma[J]. J Thorac Cardiovasc Surg, 2016, 152(1): 64-72. e1. DOI: 10.1016/j.jtcvs.2016.03.088.
[4] Travis WD, Brambilla E, Nicholson AG, et al. The 2015 World Health Organization classification of lung tumors: Impact of genetic, clinical and radiologic advances since the 2004 classification[J]. J Thorac Oncol, 2015, 10（9）: 1243-1260.
[5] Kadota K, Nitadori JI, Sima CS, et al. Tumor spread through air spaces is an important pattern of invasion and impacts the frequency and location of recurrences after limited resection for small stage I lung adenocarcinomas[J]. J Thorac Oncol, 2015, 10（5）: 806-814.
[6] Mao LT, Chen H, Liang MZ, et al. Quantitative radiomic model for predicting malignancy of small solid pulmonary nodules detected by low-dose CT screening[J]. Quant Imaging Med Surg, 2019, 9（2）: 263-272.
[7] Kadota K, Kushida Y, Kagawa S, et al. Limited resection is associated with a higher risk of locoregional recurrence than lobectomy in stage I lung adenocarcinoma with tumor spread through air spaces[J]. Am J Surg Pathol, 2019, 43（8）: 1033-1041.
[8] Dai CY, Xie HK, Su H, et al. Tumor spread through air spaces (STAS): a call for more evidence[J]. J Thorac Dis, 2017, 9（10）: E951-E953.
[9] Shih AR, Mino-Kenudson M. Updates on spread through air spaces (STAS) in lung cancer[J]. Histopathology, 2020, 77（2）: 173-180.
[10] Jiang CS, Luo Y, Yuan JL, et al. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma[J]. Eur Radiol, 2020, 30（7）: 4050-4057.
[11] 孙婷婷. 周围型肺腺癌气腔播散阳性与阴性患者CT征象及病理学比较研究[D]. 大连: 大连医科大学, 2021. DOI: 10.26994/d.cnki.gdlyu.2021.000165.
Sun TT. Comparative study on CT signs and pathology of positive and negative patients with spread through air space of peripheral lung adenocarcinoma[D]. Dalian: Dalian Medical University, 2021. DOI: 10.26994/d.cnki.gdlyu.2021.000165.
[12] 孙平丽, 刘京男, 曹岚清, 等. 气腔内播散与肺腺癌患者临床病理学特征及预后之间的相关性分析[J]. 中华病理学杂志，2017，46（5）：303-308.
Sun PL, Liu JN, Cao LQ, et al. To evaluate the clinicopathologic characteristics and outcome of tumor cells spreading through air spaces in patients with adenocarcinoma of lung[J]. Chin J Pathol, 2017, 46（5）: 303-308.
[13] Li CJ, Jiang CS, Gong JS, et al. A CT-based logistic regression model to predict spread through air space in lung adenocarcinoma[J]. Quant Imaging Med Surg, 2020, 10（10）: 1984-1993.
[14] De Margerie-Mellon C, Onken A, Heidinger BH, et al. CT manifestations of tumor spread through airspaces in pulmonary adenocarcinomas presenting as subsolid nodules[J]. J Thorac Imaging, 2018, 33（6）: 402-408.
[15] 段晓蓓, 陈相猛, 黄斌豪, 等. 18F-FDG PET/CT在预测T1～2期肺腺癌气腔内播散中的临床应用[J]. 中华核医学与分子影像杂志，2022，42（5）：263-268.
Duan XP, Chen XM, Huang BH, et al. Clinical application of 18F-FDG PET/CT parameters in predicting tumor spread through air spaces in patients with lung adenocarcinomas at T1-2 stage[J]. Chin J Nucl Med Mol Imaging, 2022, 42（5）: 263-268.
[16] 邱协. 肺癌肿瘤间质细胞和气腔扩散的关系研究[D]. 苏州: 苏州大学, 2018.
Qiu X. Relationship between the stromal cells and tumor spread through air spaces in lung adenocarcinoma[D]. Suzhou: Soochow University, 2018.
[17] Warth A, Muley T, Kossakowski CA, et al. Prognostic impact of intra-alveolar tumor spread in pulmonary adenocarcinoma[J]. Am J Surg Pathol, 2015, 39（6）: 793-801.
[18] Zhang ZR, Liu Z, Feng HX, et al. Predictive value of radiological features on spread through air space in stage cIA lung adenocarcinoma[J]. J Thorac Dis, 2020, 12（11）: 6494-6504.
[19] Cha MJ, Lee HY, Lee KS, et al. Micropapillary and solid subtypes of invasive lung adenocarcinoma: clinical predictors of histopathology and outcome[J]. J Thorac Cardiovasc Surg, 2014, 147(3): 921-928. e2. DOI: 10.1016/j.jtcvs.2013.09.045.
[20] Kim SK, Kim TJ, Chung MJ, et al. Lung adenocarcinoma: CT features associated with spread through air spaces[J]. Radiology, 2018, 289（3）: 831-840.
[21] Yin QF, Wang HE, Cui HS, et al. Meta-analysis of association between CT-based features and tumor spread through air spaces in lung adenocarcinoma[J]. J Cardiothorac Surg, 2020, 15（1）: 243.
[22] Qi L, Xue K, Cai YJ, et al. Predictors of CT morphologic features to identify spread through air spaces preoperatively in small-sized lung adenocarcinoma[J]. Front Oncol, 2021, 10: 548430.
[23] 吴越, 范力文, 谭明瑜, 等. 老年肺腺癌患者肿瘤经气道播散的CT特征[J]. 中国老年学杂志, 2020, 40 (17): 3626-3629. DOI: 10.3969/j.issn.1005-9202.2020.17.014.
Wu Y, Fan LW, Tan MY, et al. CT features of tumor dissemination through the airways in elderly patients with lung adenocarcinoma[J]. Chin J Gerontol, 2020, 40(17): 3626-3629. DOI: 10.3969/j.issn.1005-9202.2020.17.014.
[24] Park CH, Kim TH, Lee S, et al. Correlation between maximal tumor diameter of fresh pathology specimens and computed tomography images in lung adenocarcinoma[J]. PLoS One, 2019, 14（1）: e0211141.
[25] Kameda K, Lu SH, Eguchi T, et al. Can tumor spread through air spaces (STAS) in lung adenocarcinomas be predicted pre- and intraoperatively[J]. J Thorac Oncol, 2017, 12（1S）: S411-S412.
|
| [1] |
GAO Xue, NIU Shiying, SONG Guohua, LI Lulu, ZHANG Xiaoyue, PAN Wentao, CAO Xuetao, ZHANG Xinhui, SUN Meili, ZHAO Guoli, ZHANG Yueying. Hydrogen therapy promotes macrophage polarization to the M2 subtype by inhibiting the NF-κB signaling pathway[J]. Chinese Journal of Radiological Health, 2024, 33(1): 33-39. |
|
|
|
|
