The combination of computed tomography features and circulating tumor cells increases the surgical prediction of visceral pleural invasion in clinical T1N0M0 lung adenocarcinoma

被引:19
作者
Shi, Jinghan [1 ]
Li, Fei [2 ]
Yang, Fujun [3 ]
Dong, Zhengwei [4 ]
Jiang, Yan [3 ]
Nachira, Dania [5 ]
Chalubinska-Fendler, Justyna [6 ]
Sio, Terence T. [7 ]
Kawaguchi, Yo [8 ]
Takizawa, Hiromitsu [9 ]
Song, Xiao [3 ]
Hu, Yang [10 ]
Duan, Liang [3 ]
机构
[1] Tongji Univ, Shanghai Pulm Hosp, Dept Endoscopy, Sch Med, Shanghai, Peoples R China
[2] Tongji Univ, Shanghai Pulm Hosp, Dept Radiol, Sch Med, Shanghai, Peoples R China
[3] Tongji Univ, Shanghai Pulm Hosp, Dept Thorac Surg, Sch Med, Shanghai, Peoples R China
[4] Tongji Univ, Shanghai Pulm Hosp, Dept Pathol, Sch Med, Shanghai, Peoples R China
[5] Fdn Polidin Univ A Gemelli, Dept Gen Thorac Surg, IRCCS, Rome, Italy
[6] Mil Inst Med, Dept Radiat Oncol, Warsaw, Poland
[7] Mayo Clin, Dept Radiat Oncol, Phoenix, AZ USA
[8] Shiga Univ Med Sci, Dept Surg, Div Gen Thorac Surg, Otsu, Shiga, Japan
[9] Tokushima Univ, Dept Thorac Endocrine Surg & Oncol, Grad Sch Biomed Sci, Kuramotocho, Tokushima, Japan
[10] Tongji Univ, Shanghai Pulm Hosp, Dept Resp & Crit Care Med, Sch Med, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Lung adenocarcinoma; visceral pleural invasion (VPI); circulating tumor cell (CTC); computed tomography (CT); thoracic surgery; 8TH EDITION; DIAGNOSTIC BIOMARKER; NODE-METASTASIS; CANCER; CLASSIFICATION;
D O I
10.21037/tlcr-21-896
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Visceral pleural invasion (VPI) is a clinical manifestation associated with a poor prognosis, and diagnosing it preoperatively is highly imperative for successful sublobar resection of these peripheral tumors. We evaluated the roles of computed tomography (CT) features and circulating tumor cells (CTCs) for improving VPI detection in patients with clinical T1N0M0 invasive lung adenocarcinoma. Methods: Three hundred and ninety-one patients were reviewed retrospectively in this study, of which 234 presented with a pleural tag or pleural contact on CT images. CTCs positive for the foliate receptors were enriched and analyzed prior to surgery. Logistic regression analyses were performed to assess the association of CT features and CTCs with VPI, and the receiver operating characteristic (ROC) curve was generated to compare the predictive power of these variables. Results: Patients mostly underwent either segmentectomies (18.9%) or lobectomies (79.0%). Only 49 of the 234 patients with pleural involvement on CT showed pathologically confirmed VPI. Multivariate logistic regression analysis revealed that CTC level >= 10.42 FU/3 mL was a significant VPI risk factor for invasive adenocarcinoma cases <= 30 mm [adjusted odds ratio (OR) =4.62, 95% confidence interval (CI): 2.05-10.44, P<0.001]. Based on CT features, subgroup analyses showed that the solid portion size was a statistically significant independent predictor of VPI for these peripheral nodules with pleural tag, while the solid portion length of the interface was an independent predictor of pleural contact. The receiver operating curve analyses showed that the combination of CTC and CT features were highly predictive of VPI [area under the curve (AUC) =0.921 for pleural contact and 0.862 for the pleural tag, respectively]. Conclusions: CTC, combined with CT features of pleural tag or pleural contact, could significantly improve VPI detection in invasive lung adenocarcinomas at clinical T1N0M0 stage prior to the patient's surgery.
引用
收藏
页码:4266 / 4280
页数:15
相关论文
共 57 条
[1]   Circulating tumor cells as a predictive biomarker in patients with small cell lung cancer undergoing chemotherapy [J].
Aggarwal, Charu ;
Wang, Xingmei ;
Ranganathan, Anjana ;
Torigian, Drew ;
Troxel, Andrea ;
Evans, Tracey ;
Cohen, Roger B. ;
Vaidya, Bhavesh ;
Rao, Chandra ;
Connelly, Mark ;
Vachani, Anil ;
Langer, Corey ;
Albelda, Steven .
LUNG CANCER, 2017, 112 :118-125
[2]   Predictive CT Features of Visceral Pleural Invasion by T1-Sized Peripheral Pulmonary Adenocarcinomas Manifesting as Subsolid Nodules [J].
Ahn, Su Yeon ;
Park, Chang Min ;
Jeon, Yoon Kyung ;
Kim, Hyungjin ;
Lee, Jong Hyuk ;
Hwang, Eui Jin ;
Goo, Jin Mo .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2017, 209 (03) :561-566
[3]   CTC analysis: an update on technological progress [J].
Batth, Izhar S. ;
Mitra, Abhisek ;
Rood, Sierra ;
Kopetz, Scott ;
Menter, David ;
Li, Shulin .
TRANSLATIONAL RESEARCH, 2019, 212 :14-25
[4]   Survival Rates After Lobectomy, Segmentectomy, and Wedge Resection for Non-Small Cell Lung Cancer [J].
Cao, Jinlin ;
Yuan, Ping ;
Wang, Yiqing ;
Xu, Jinming ;
Yuan, Xiaoshuai ;
Wang, Zhitian ;
Lv, Wang ;
Hu, Jian .
ANNALS OF THORACIC SURGERY, 2018, 105 (05) :1483-1491
[5]   Tracking cancer progression: from circulating tumor cells to metastasis [J].
Castro-Giner, Francesc ;
Aceto, Nicola .
GENOME MEDICINE, 2020, 12 (01)
[6]   Circulating Tumor Cells: Moving Biological Insights into Detection [J].
Chen, Lichan ;
Bode, Ann M. ;
Dong, Zigang .
THERANOSTICS, 2017, 7 (10) :2606-2619
[7]   Visceral pleural invasion predict a poor survival among lung adenocarcinoma patients with tumor size ≤ 3cm [J].
Chen, Tianxiang ;
Luo, Jizhuang ;
Wang, Rui ;
Gu, Haiyong ;
Gu, Yu ;
Huang, Qingyuan ;
Wang, Yiyang ;
Zheng, Jiajie ;
Gu, Chang ;
Pan, Xufeng ;
Yang, Jun ;
Yang, Yunhai ;
Zhao, Heng .
ONCOTARGET, 2017, 8 (39) :66576-66583
[8]   Folate receptor-positive circulating tumor cells as a predictive biomarker for the efficacy of first-line pemetrexed-based chemotherapy in patients with non-squamous non-small cell lung cancer [J].
Chen, Xiaoxia ;
Zhou, Fei ;
Li, Xuefei ;
Yang, Guohua ;
Zhao, Chao ;
Li, Wei ;
Wu, Fenying ;
Yu, Jia ;
Gao, Guanghui ;
Li, Jiayu ;
Li, Aiwu ;
Ren, Shengxiang ;
Zhou, Caicun .
ANNALS OF TRANSLATIONAL MEDICINE, 2020, 8 (10)
[9]   Folate Receptor-Positive Circulating Tumor Cell Detected by LT-PCR-Based Method as a Diagnostic Biomarker for Non-Small-Cell Lung Cancer [J].
Chen, Xiaoxia ;
Zhou, Fei ;
Li, Xuefei ;
Yang, Guohua ;
Zhang, Ling ;
Ren, Shengxiang ;
Zhao, Chao ;
Deng, Qinfang ;
Li, Wei ;
Gao, Guanghui ;
Li, Aiwu ;
Zhou, Caicun .
JOURNAL OF THORACIC ONCOLOGY, 2015, 10 (08) :1163-1171
[10]   Prediction of visceral pleural invasion in lung cancer on CT: deep learning model achieves a radiologist-level performance with adaptive sensitivity and specificity to clinical needs [J].
Choi, Hyewon ;
Kim, Hyungjin ;
Hong, Wonju ;
Park, Jongsoo ;
Hwang, Eui Jin ;
Park, Chang Min ;
Kim, Young Tae ;
Goo, Jin Mo .
EUROPEAN RADIOLOGY, 2021, 31 (05) :2866-2876