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Li F, Qi L, Cheng S, Liu J, Chen J, Cui S, Dong S, Wang J. Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study. Insights Imaging 2024; 15:109. [PMID: 38679659 PMCID: PMC11056350 DOI: 10.1186/s13244-024-01678-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 03/22/2024] [Indexed: 05/01/2024] Open
Abstract
OBJECTIVE To determine whether quantitative parameters of detector-derived dual-layer spectral computed tomography (DLCT) can reliably identify epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC). METHODS Patients with NSCLC who underwent arterial phase (AP) and venous phase (VP) DLCT between December 2021 and November 2022 were subdivided into the mutated and wild-type EGFR groups following EGFR mutation testing. Their baseline clinical data, conventional CT images, and spectral images were obtained. Iodine concentration (IC), iodine no water (INW), effective atomic number (Zeff), virtual monoenergetic images, the slope of the spectral attenuation curve (λHU), enhancement degree (ED), arterial enhancement fraction (AEF), and normalized AEF (NAEF) were measured for each lesion. RESULTS Ninety-two patients (median age, 61 years, interquartile range [51, 67]; 33 men) were evaluated. The univariate analysis indicated that IC, normalized IC (NIC), INW and ED for the AP and VP, as well as Zeff and λHU for the VP were significantly associated with EGFR mutation status (all p < 0.05). INW(VP) showed the best diagnostic performance (AUC, 0.892 [95% confidence interval {CI}: 0.823, 0.960]). However, neither AEF (p = 0.156) nor NAEF (p = 0.567) showed significant differences between the two groups. The multivariate analysis showed that INW(AP) and NIC(VP) were significant predictors of EGFR mutation status, with the latter showing better performance (p = 0.029; AUC, 0.897 [95% CI: 0.816, 0.951] vs. 0.774 [95% CI: 0.675, 0.855]). CONCLUSION Quantitative parameters of DLCT can help predict EGFR mutation status in patients with NSCLC. CRITICAL RELEVANCE STATEMENT Quantitative parameters of DLCT, especially NIC(VP), can help predict EGFR mutation status in patients with NSCLC, facilitating appropriate and individualized treatment for them. KEY POINTS Determining EGFR mutation status in patients with NSCLC before starting therapy is essential. Quantitative parameters of DLCT can predict EGFR mutation status in NSCLC patients. NIC in venous phase is an important parameter to guide individualized treatment selection for NSCLC patients.
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Affiliation(s)
- Fenglan Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China
| | - Linlin Qi
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China
| | - Sainan Cheng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China
| | - Jianing Liu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China
| | - Jiaqi Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China
| | - Shulei Cui
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China
| | - Shushan Dong
- Clinical Science, Philips Healthcare, Beijing, China
| | - Jianwei Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, Chaoyang District, 100021, China.
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Huo B, Manos D, Xu Z, Matheson K, Chun S, Fris J, Wallace AMR, French DG. Screening Criteria Evaluation for Expansion in Pulmonary Neoplasias (SCREEN). Semin Thorac Cardiovasc Surg 2022; 35:769-780. [PMID: 35878739 DOI: 10.1053/j.semtcvs.2022.06.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 06/06/2022] [Indexed: 12/14/2022]
Abstract
The SCREEN study investigated screening eligibility and survival outcomes between heavy smokers and light-or-never-smokers with lung cancer to determine whether expanded risk factor analysis is needed to refine screening criteria. SCREEN is a retrospective study of 917 lung cancer patients diagnosed between 2005 and 2018 in Nova Scotia, Canada. Screening eligibility was determined using the National Lung Screening Trial (NSLT) criteria. Mortality risk between heavy smokers and light-or-never-smokers was compared using proportional-hazards models. The median follow-up was 2.9 years. The cohort was comprised of 179 (46.1%) female heavy smokers and 306 (57.8%) female light-or-never-smokers. Light-or-never-smokers were more likely to have a diagnosis of adenocarcinoma [n=378 (71.6%)] compared to heavy smokers [n=234 (60.5%); P< 0.001]. Heavy smokers were more frequently diagnosed with squamous cell carcinoma [n=111 (28.7%)] compared to light-or-never-smokers, [n=100 (18.9%); P< 0.001]. Overall, 36.9% (338) of patients met NLST screening criteria. There was no difference in 5-year survival between light-or-never-smokers and heavy smokers [55.2% (338) vs 58.5% (529); P = 0.408; HR 1.06, 95% CI 0.80-1.40; P = 0.704]. Multivariate analysis showed that males had an increased mortality risk [HR 2.00 (95% CI 1.57-2.54); P< 0.001]. Half of lung cancer patients were missed with the conventional screening criteria. There were more curable, stage 1 tumors among light-or-never-smokers. Smoking status and age alone may be insufficient predictors of lung cancer risk and prognosis. Expanded risk factor analysis is needed to refine lung cancer screening criteria.
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Affiliation(s)
- Bright Huo
- Faculty of Medicine, Dalhousie University, Halifax, NS, Canada
| | - Daria Manos
- Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada
| | - Zhaolin Xu
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
| | - Kara Matheson
- Research Methods Unit, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Samuel Chun
- Department of Urology, Dalhousie University, Halifax, NS, Canada
| | - John Fris
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
| | - Alison M R Wallace
- Department of Pathology, Dalhousie University, Halifax, NS, Canada; Division of Thoracic Surgery, Department of Surgery, Dalhousie University, Halifax, NS, Canada
| | - Daniel G French
- Division of Thoracic Surgery, Department of Surgery, Dalhousie University, Halifax, NS, Canada.
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Establishment and Evaluation of EGFR Mutation Prediction Model Based on Tumor Markers and CT Features in NSCLC. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:8089750. [PMID: 35422977 PMCID: PMC9005305 DOI: 10.1155/2022/8089750] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/02/2022] [Accepted: 03/16/2022] [Indexed: 01/07/2023]
Abstract
Background Lung cancer has become one of the leading causes of cancer deaths worldwide. EGFR gene mutation has been reported in up to 60% of Asian populations and is currently one of the main targets for genotype-targeted therapy for NSCLC. Objective The objective is to determine if a complex model combining serum tumor makers and computed tomographic (CT) features can predict epidermal growth factor receptor (EGFR) mutation with higher accuracy. Material and Methods. Retrospective analysis of the data of patients diagnosed with in nonsmall cell lung cancer (NSCLC) by EGFR gene testing was carried out in the Department of Thoracic Surgery, Jinan Central Hospital. Multivariate logistic regression analysis was used to determine the independent predictors of EGFR mutations, and logistic regression prediction models were developed. The subject operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated to assess the accuracy and clinical application of the EGFR mutation prediction model. Results Logistic regression analysis identified the predictive factors of EGFR mutation including nonsmoking, high expression level of Carcinoembryonic Antigen (CEA), low expression level of cytokeratin 19 fragments (CYFRA21-1), and subsolid density containing ground-glass opacity (GGO) component. Using the results of multivariate logistic regression analysis, we built a statistically determined clinical prediction model. The AUC of the complex prediction model increased significantly from 0.735 to 0.813 (p = 0.014) when CT features are added and from 0.612 to 0.813 (p < 0.001) when serum variables are added. When P was 0.441, the sensitivity was 86.7% and the specificity was 65.8%. Conclusion A complex model combining serum tumor makers and CT features is more accurate in predicting EGFR mutation status in NSCLC patients than using either serum variables or imaging features alone. Our finding for EGFR mutation is urgently needed and helpful in clinical practice.
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Predicting EGFR mutation status in lung adenocarcinoma presenting as ground-glass opacity: utilizing radiomics model in clinical translation. Eur Radiol 2022; 32:5869-5879. [DOI: 10.1007/s00330-022-08673-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 10/23/2021] [Accepted: 11/12/2021] [Indexed: 12/19/2022]
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Ortiz AFH, Camacho TC, Vásquez AF, del Castillo Herazo V, Neira JGA, Yepes MM, Camacho EC. Clinical and CT patterns to predict EGFR mutation in patients with non-small cell lung cancer: A systematic literature review and meta-analysis. Eur J Radiol Open 2022; 9:100400. [PMID: 35198656 PMCID: PMC8844749 DOI: 10.1016/j.ejro.2022.100400] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 01/29/2022] [Accepted: 02/01/2022] [Indexed: 12/16/2022] Open
Abstract
Purpose This study aims to determine if the presence of specific clinical and computed tomography (CT) patterns are associated with epidermal growth factor receptor (EGFR) mutation in patients with non-small cell lung cancer. Methods A systematic literature review and meta-analysis was carried out in 6 databases between January 2002 and July 2021. The relationship between clinical and CT patterns to detect EGFR mutation was measured and pooled using odds ratios (OR). These results were used to build several mathematical models to predict EGFR mutation. Results 34 retrospective diagnostic accuracy studies met the inclusion and exclusion criteria. The results showed that ground-glass opacities (GGO) have an OR of 1.86 (95%CI 1.34 −2.57), air bronchogram OR 1.60 (95%CI 1.38 – 1.85), vascular convergence OR 1.39 (95%CI 1.12 – 1.74), pleural retraction OR 1.99 (95%CI 1.72 – 2.31), spiculation OR 1.42 (95%CI 1.19 – 1.70), cavitation OR 0.70 (95%CI 0.57 – 0.86), early disease stage OR 1.58 (95%CI 1.14 – 2.18), non-smoker status OR 2.79 (95%CI 2.34 – 3.31), female gender OR 2.33 (95%CI 1.97 – 2.75). A mathematical model was built, including all clinical and CT patterns assessed, showing an area under the curve (AUC) of 0.81. Conclusions GGO, air bronchogram, vascular convergence, pleural retraction, spiculated margins, early disease stage, female gender, and non-smoking status are significant risk factors for EGFR mutation. At the same time, cavitation is a protective factor for EGFR mutation. The mathematical model built acts as a good predictor for EGFR mutation in patients with lung adenocarcinoma. GGO, air bronchogram, vascular convergence, pleural retraction, and spiculated margins, are risk factors for EGFR mutation. Early disease stage, female gender and non-smoking status are risk factors for EGFR mutation. Cavitation is a protective factor for EGFR mutation.
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Affiliation(s)
- Andrés Felipe Herrera Ortiz
- Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
- Universidad El Bosque, Bogotá, Colombia
- Corresponding author at: Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia.
| | | | - Andrés Francisco Vásquez
- Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
- Universidad El Bosque, Bogotá, Colombia
| | | | | | - María Mónica Yepes
- Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
- Universidad El Bosque, Bogotá, Colombia
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An W, Fan W, Zhong F, Wang B, Wang S, Gan T, Tian S, Liao M. Development and Validation of a Concise Prediction Scoring System for Asian Lung Cancer Patients with EGFR Mutation Before Treatment. Technol Cancer Res Treat 2022; 21:15330338221078732. [PMID: 35234540 PMCID: PMC8894628 DOI: 10.1177/15330338221078732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Purpose We aimed to determine the epidermal growth factor receptor
(EGFR) genetic profile of lung cancer in Asians, and
develop and validate a non-invasive prediction scoring system for
EGFR mutation before treatment. Methods This
was a single-center retrospective cohort study using data of patients with lung
cancer who underwent EGFR detection (n = 1450) from December
2014 to October 2020. Independent predictors were filtered using univariate and
multivariate logistic regression analyses. According to the weight of each
factor, a prediction scoring system for EGFR mutation was
constructed. The model was internally validated using bootstrapping techniques
and temporally validated using prospectively collected data (n = 210) between
November 2020 and June 2021.Results In 1450 patients with lung
cancer, 723 single mutations and 51 compound mutations were observed in
EGFR. Thirty-nine cases had two or more synchronous gene
mutations. We developed a scoring system according to the independent clinical
predictors and stratified patients into risk groups according to their scores:
low-risk (score <4), moderate-risk (score 4-8), and high-risk (score >8)
groups. The C-statistics of the scoring system model was 0.754 (95% CI
0.729-0.778). The factors in the validation group were introduced into the
prediction model to test the predictive power of the model. The results showed
that the C-statistics was 0.710 (95% CI 0.638-0.782). The Hosmer–Lemeshow
goodness-of-fit showed that χ2 = 6.733, P = 0.566.
Conclusions The scoring system constructed in our study may be
a non-invasive tool to initially predict the EGFR mutation
status for those who are not available for gene detection in clinical
practice.
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Affiliation(s)
- Wenting An
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Wei Fan
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Feiyang Zhong
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Binchen Wang
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Shan Wang
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Tian Gan
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Sufang Tian
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Meiyan Liao
- 89674Zhongnan Hospital of Wuhan University, Wuhan, China
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Li Q, He XQ, Fan X, Luo TY, Huo JW, Huang XT. Computed Tomography Morphological Classification of Lung Adenocarcinoma and Its Correlation with Epidermal Growth Factor Receptor Mutation Status: A Report of 1075 Cases. Int J Gen Med 2021; 14:3687-3698. [PMID: 34321914 PMCID: PMC8312332 DOI: 10.2147/ijgm.s316344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 06/21/2021] [Indexed: 12/18/2022] Open
Abstract
Background Many delayed diagnoses of lung adenocarcinoma (LADC) are identified due to poor understanding of protean imaging findings. Moreover, clarifying the relationship between computed tomography (CT) morphological classification and epidermal growth factor receptor (EGFR) mutations of LADC might inform therapeutic decision-making while obtaining pathological specimens is difficult. Here, we retrospectively analyzed CT manifestations of LADC and investigated the morphological classification of tumors in relation to EGFR mutation status. Methods We included 1075 LADC patients undergoing chest CT and EGFR genotype examinations from January 2013 to January 2019. CT morphological characteristics of tumors were carefully evaluated and their correlation with EGFR mutation status was analyzed using the chi-squared test. Results Tumors were divided into eight types: I (peripheral solid nodule/mass; 526/1075, 48.93%), II (central solid nodule/mass; 220/1075, 20.47%), III (subsolid nodule/mass; 92/1075, 8.56%), IV (focal consolidation; 32/1075, 2.98%), V (cystic airspace; 14/1075, 1.30%), VI (multiple lesions with similar appearances to I–V; 85/1075, 7.91%), VII (diffuse consolidation; 53/1075, 4.93%), VIII (occult lesion usually obscured by nonobstructive atelectasis; 53/1075, 4.93%). Type III and IV tumors were more frequent in patients with EGFR mutation, whereas type II and VII tumors were more common in patients without EGFR mutation (all P < 0.05). However, we did not identify any significant associations between other tumor types and EGFR mutation status (all P > 0.05). Among patients with type VI tumors, EGFR mutation status was closely related to tumor density (all P < 0.05). Furthermore, type VII tumors were associated with 19 deletion mutation positive and non-L858R mutation positive (all P < 0.05). Conclusion LADC can be categorized into eight types based on CT imaging. Improving our understanding of the morphological classification and correlation with EGFR mutation status may contribute to the accurate diagnosis of LADC, while suggesting the presence of underlying EGFR genetic mutations.
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Affiliation(s)
- Qi Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Xiao-Qun He
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Xiao Fan
- Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, People's Republic of China
| | - Tian-You Luo
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Ji-Wen Huo
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Xing-Tao Huang
- Department of Radiology, University of Chinese Academy of Sciences Chongqing Renji Hospital (Fifth People's Hospital of Chongqing), Chongqing, 400062, People's Republic of China
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Primary metabolic tumor volume from 18F-FDG PET/CT associated with epidermal growth factor receptor mutation in lung adenocarcinoma patients. Nucl Med Commun 2021; 41:1210-1217. [PMID: 32815896 DOI: 10.1097/mnm.0000000000001274] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
PURPOSE To explore the potential parameters from F-FDG PET/CT that might be associated with the epidermal growth factor receptor (EGFR) gene mutation status in lung adenocarcinoma (ADC) patients. METHODS Data of the test cohort of 191 patients and the validation cohort of 55 patients with newly diagnosed ADC were retrospectively reviewed. All patients underwent F-FDG PET/CT scans and EGFR mutation tests prior to treatment. The metabolic parameters obtained from F-FDG PET/CT combining with clinical characteristics were analyzed by using univariate and multivariate logistic regression analyses. Then two cohorts were enrolled to validate the predictive model by area under the receiver-operating characteristic curve (AUC), respectively. RESULTS EGFR mutation-positive was seen of 33.0% (63/191) and 32.7% (18/55) in two cohorts, respectively. In univariate analysis, female, nonsmokers, metabolic parameters of primary tumor [mean standardized uptake value, metabolic tumor volume (pMTV), and total lesion glycolysis], non-necrosis of primary tumor, and serum tumor markers [carbohydrate antigen 19-9, squamous cell carcinoma antigen, and precursor of gastrin releasing peptide (proGRP)] were significantly relevant with EGFR mutation. In multivariate analysis with adjustment of age and TNM stage, pMTV (<8.13 cm), proGRP (≥38.44 pg/ml) and women were independent significant predictors for EGFR mutation. The AUC for the predictive value of these factors was 0.739 [95% confidence interval (CI) 0.665-0.813] in the cohort of 191 patients and 0.716 (95% CI 0.567-0.865) in the cohort of 55 patients, respectively. CONCLUSION Low pMTV (<8.13 cm) was an independent predictor and could be integrated with women and high proGRP (≥38.44 pg/ml) to enhance the discriminability on the EGFR mutation status in ADC patients.
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Dang Y, Wang R, Qian K, Lu J, Zhang H, Zhang Y. Clinical and radiological predictors of epidermal growth factor receptor mutation in nonsmall cell lung cancer. J Appl Clin Med Phys 2020; 22:271-280. [PMID: 33314737 PMCID: PMC7856515 DOI: 10.1002/acm2.13107] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 10/26/2020] [Accepted: 10/30/2020] [Indexed: 01/06/2023] Open
Abstract
Purpose To determine the prognostic factors of epidermal growth factor receptor (EGFR) mutation status in a group of patients with nonsmall cell lung cancer (NSCLC) by analyzing their clinical and radiological features. Materials and methods Patients with NSCLC who underwent EGFR mutation detection between 2014 and 2017 were included. Clinical features and general imaging features were collected, and radiomic features were extracted from CT data by 3D Slicer software. Prognostic factors of EGFR mutation status were selected by least absolute shrinkage and selection operator (LASSO) logistic regression analysis, and receiver operating characteristic (ROC) curves were drawn for each prediction model of EGFR mutation. Results A total of 118 patients were enrolled in this study. The smoking index (P = 0.028), pleural retraction (P = 0.041), and three radiomic features were significantly associated with EGFR mutation status. The areas under the ROC curve (AUCs) for prediction models of clinical features, general imaging features, and radiomic features were 0.284, 0.703, and 0.815, respectively, and the AUC for the combined prediction model of the three models was 0.894. Finally, a nomogram was established for individualized EGFR mutation prediction. Conclusions The combination of radiomic features with clinical features and general imaging features can enable discrimination of EGFR mutation status better than the use of any group of features alone. Our study may help develop a noninvasive biomarker to identify EGFR mutation status by using a combination of the three group features.
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Affiliation(s)
- Yutao Dang
- Department of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.,Department of Thoracic Surgery, Shijingshan Hospital of Beijing City, Shijingshan Teaching Hospital of Capital Medical University, Beijing, China
| | - Ruotian Wang
- Department of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kun Qian
- Department of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Haixiang Zhang
- Center for Applied Mathematics, Tianjin University, Tianjin, China
| | - Yi Zhang
- Department of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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Choi Y, Kim KH, Jeong BH, Lee KJ, Kim H, Kwon OJ, Kim J, Choi YL, Lee HY, Um SW. Clinicoradiopathological features and prognosis according to genomic alterations in patients with resected lung adenocarcinoma. J Thorac Dis 2020; 12:5357-5368. [PMID: 33209369 PMCID: PMC7656340 DOI: 10.21037/jtd-20-1716] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background We investigated the clinicoradiopathological features and prognosis according to genomic alterations in patients with surgically resected lung adenocarcinoma. Methods Patients who underwent surgical resection for pathologic stage I, II, or IIIA lung adenocarcinoma between 2009 and 2016 and for whom results regarding EGFR mutation, ALK immunohistochemistry (IHC), and KRAS mutation were available were included. Clinicoradiopathological characteristics, genomic alterations, and disease-free survival were analyzed retrospectively. Results Of 164 patients, 86 (52.4%) were female and 94 (57.3%) were never-smokers. The most common imaging patterns were part-solid lesion (67.7%) followed by solid (26.2%) and non-solid (6.1%) lesions. EGFR mutation, ALK IHC, and KRAS mutation were positive in 95 (57.9%), 9 (5.5%), and 11 (6.7%) patients, respectively. EGFR mutation positivity was associated with female sex, never-smoker, subsolid pattern on radiological examination, and acinar or papillary predominant histologic subtype. ALK IHC positivity was associated with longer maximal diameter, advanced stage, solid pattern on radiological examination, solid predominant histologic subtype, and distant metastasis during follow-up. KRAS mutation positivity was associated with male sex, smoker, solid pattern on radiological examination, and invasive mucinous adenocarcinoma on histologic analysis. In multivariable analysis, ALK IHC positivity and lymph node involvement were independently associated with recurrence. However, solidity was not an independent risk factor for recurrence. Conclusions Genomic alterations are associated with clinicoradiopathologic features in patients with resected lung adenocarcinoma. Identifying genomic alterations could help to predict the prognosis of early-stage lung adenocarcinoma.
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Affiliation(s)
- Yeonseok Choi
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ki-Hwan Kim
- Department of Radiology, Myongji Hospital, Goyang, South Korea
| | - Byeong-Ho Jeong
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Kyung-Jong Lee
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hojoong Kim
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - O Jung Kwon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jhingook Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yoon-La Choi
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ho Yun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Sang-Won Um
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
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Aye PS, Tin Tin S, McKeage MJ, Khwaounjoo P, Cavadino A, Elwood JM. Development and validation of a predictive model for estimating EGFR mutation probabilities in patients with non-squamous non-small cell lung cancer in New Zealand. BMC Cancer 2020; 20:658. [PMID: 32664868 PMCID: PMC7362551 DOI: 10.1186/s12885-020-07162-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Accepted: 07/09/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Targeted treatment with Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) is superior to systemic chemotherapy in non-small cell lung cancer (NSCLC) patients with EGFR gene mutations. Detection of EGFR mutations is a challenge in many patients due to the lack of suitable tumour specimens for molecular testing or for other reasons. EGFR mutations are more common in female, Asian and never smoking NSCLC patients. METHODS Patients were from a population-based retrospective cohort of 3556 patients diagnosed with non-squamous non-small cell lung cancer in northern New Zealand between 1 Feb 2010 and 31 July 2017. A total of 1694 patients were tested for EGFR mutations, of which information on 1665 patients was available for model development and validation. A multivariable logistic regression model was developed based on 1176 tested patients, and validated in 489 tested patients. Among 1862 patients not tested for EGFR mutations, 129 patients were treated with EGFR-TKIs. Their EGFR mutation probabilities were calculated using the model, and their duration of benefit and overall survival from the start of EGFR-TKI were compared among the three predicted probability groups: < 0.2, 0.2-0.6, and > 0.6. RESULTS The model has three predictors: sex, ethnicity and smoking status, and is presented as a nomogram to calculate EGFR mutation probabilities. The model performed well in the validation group (AUC = 0.75). The probability cut-point of 0.2 corresponds 68% sensitivity and 78% specificity. The model predictions were related to outcome in a group of TKI-treated patients with no biopsy testing available (n = 129); in subgroups with predicted probabilities of < 0.2, 0.2-0.6, and > 0.6, median overall survival times from starting EGFR-TKI were 4.0, 5.5 and 18.3 months (p = 0.02); and median times remaining on EGFR-TKI treatment were 2.0, 4.2, and 14.0 months, respectively (p < 0.001). CONCLUSION Our model may assist clinical decision making for patients in whom tissue-based mutation testing is difficult or as a supplement to mutation testing.
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Affiliation(s)
- Phyu Sin Aye
- Epidemiology and Biostatistics, University of Auckland, B507, 22-30 Park Ave, Grafton, Auckland, 1072, New Zealand.
| | - Sandar Tin Tin
- Epidemiology and Biostatistics, University of Auckland, B507, 22-30 Park Ave, Grafton, Auckland, 1072, New Zealand
| | - Mark James McKeage
- Pharmacology and Clinical Pharmacology, University of Auckland, Auckland, New Zealand
- Auckland Cancer Society Research Centre, University of Auckland, Auckland, New Zealand
| | | | - Alana Cavadino
- Epidemiology and Biostatistics, University of Auckland, B507, 22-30 Park Ave, Grafton, Auckland, 1072, New Zealand
| | - J Mark Elwood
- Epidemiology and Biostatistics, University of Auckland, B507, 22-30 Park Ave, Grafton, Auckland, 1072, New Zealand
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12
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Nair JKR, Saeed UA, McDougall CC, Sabri A, Kovacina B, Raidu BVS, Khokhar RA, Probst S, Hirsh V, Chankowsky J, Van Kempen LC, Taylor J. Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer. Can Assoc Radiol J 2020; 72:109-119. [PMID: 32063026 DOI: 10.1177/0846537119899526] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and 18F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor receptor (EGFR) mutations. METHODS Fifty patients diagnosed with NSCLC between 2011 and 2015 and with known EGFR mutation status were retrospectively identified. Texture features extracted from pretreatment CT and FDG PET-CT images by manual contouring of the primary tumor were used to develop multivariate logistic regression (LR) models to predict EGFR mutations in exon 19 and exon 20. RESULTS An LR model evaluating FDG PET-texture features was able to differentiate EGFR mutant from wild type with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.87, 0.76, 0.66, and 0.71, respectively. The model derived from CT texture features had an AUC, sensitivity, specificity, and accuracy of 0.83, 0.84, 0.73, and 0.78, respectively. FDG PET-texture features that could discriminate between mutations in EGFR exon 19 and 21 demonstrated AUC, sensitivity, specificity, and accuracy of 0.86, 0.84, 0.73, and 0.78, respectively. Based on CT texture features, the AUC, sensitivity, specificity, and accuracy were 0.75, 0.81, 0.69, and 0.75, respectively. CONCLUSION Non-small cell lung cancer texture analysis using FGD-PET and CT images can identify tumors with mutations in EGFR. Imaging signatures could be valuable for pretreatment assessment and prognosis in precision therapy.
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Affiliation(s)
- Jay Kumar Raghavan Nair
- Department of Radiology, 54473McGill University Health Centre, Montreal, Québec, Canada.,Department of Radiology, McMaster University Faculty of Health Sciences, Hamilton, Ontario, Canada.,Department of Radiology, 2129University of Calgary, Calgary, Alberta, Canada
| | - Umar Abid Saeed
- Department of Radiology, 54473McGill University Health Centre, Montreal, Québec, Canada.,Department of Radiology, 2129University of Calgary, Calgary, Alberta, Canada
| | - Connor C McDougall
- Department of Mechanical Engineering, 2129University of Calgary, Calgary, Alberta, Canada
| | - Ali Sabri
- Department of Radiology, McMaster University, Hamilton, Ontario, Canada.,Department of Radiology, Jewish General Hospital, Montreal, Québec, Canada
| | - Bojan Kovacina
- Department of Radiology, Jewish General Hospital, Montreal, Québec, Canada
| | - B V S Raidu
- Raidu Analysts and Associates, Mumbai, India
| | - Riaz Ahmed Khokhar
- Department of Radiology, 54473McGill University Health Centre, Montreal, Québec, Canada.,Department of Surgery, Khokhar Medical Centre, Rawalpindi, Pakistan
| | - Stephan Probst
- Department of Nuclear Medicine, Jewish General Hospital, Québec, Montreal, Canada
| | - Vera Hirsh
- Department of Oncology, 5620McGill University Health Centre, Montreal, Québec, Canada
| | - Jeffrey Chankowsky
- Department of Radiology, 54473McGill University Health Centre, Montreal, Québec, Canada
| | - Léon C Van Kempen
- Department of Pathology, 10173University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.,Department of Pathology, Jewish General Hospital, Montreal, Québec, Canada
| | - Jana Taylor
- Department of Radiology, 54473McGill University Health Centre, Montreal, Québec, Canada
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13
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Yoon J, Suh YJ, Han K, Cho H, Lee HJ, Hur J, Choi BW. Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas. Thorac Cancer 2020; 11:993-1004. [PMID: 32043309 PMCID: PMC7113038 DOI: 10.1111/1759-7714.13352] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 01/20/2020] [Accepted: 01/21/2020] [Indexed: 12/23/2022] Open
Abstract
Background We aimed to assess if quantitative radiomic features can predict programmed death ligand 1 (PD‐L1) expression in advanced stage lung adenocarcinoma. Methods This retrospective study included 153 patients who had advanced stage (>IIIA by TNM classification) lung adenocarcinoma with pretreatment thin section computed tomography (CT) images and PD‐L1 expression test results in their pathology reports. Clinicopathological data were collected from electronic medical records. Visual analysis and radiomic feature extraction of the tumor from pretreatment CT were performed. We constructed two models for multivariate logistic regression analysis (one based on clinical variables, and the other based on a combination of clinical variables and radiomic features), and compared c‐statistics of the receiver operating characteristic curves of each model to identify the model with the higher predictability. Results Among 153 patients, 53 patients were classified as PD‐L1 positive and 100 patients as PD‐L1 negative. There was no significant difference in clinical characteristics or imaging findings on visual analysis between the two groups (P > 0.05 for all). Rad‐score by radiomic analysis was higher in the PD‐L1 positive group than in the PD‐L1 negative group with a statistical significance (−0.378 ± 1.537 vs. −1.171 ± 0.822, P = 0.0008). A prediction model that uses clinical variables and CT radiomic features showed higher performance compared to a prediction model that uses clinical variables only (c‐statistic = 0.646 vs. 0.550, P = 0.0299). Conclusions Quantitative CT radiomic features can predict PD‐L1 expression in advanced stage lung adenocarcinoma. A prediction model composed of clinical variables and CT radiomic features may facilitate noninvasive assessment of PD‐L1 expression. Key points Significant findings of the study Quantitative CT radiomic features can help predict PD‐L1 expression, whereas none of the qualitative imaging findings is associated with PD‐L1 positivity. What this study adds A prediction model composed of clinical variables and CT radiomic features may facilitate noninvasive assessment of PD‐L1 expression.
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Affiliation(s)
- Jiyoung Yoon
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Young Joo Suh
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Kyunghwa Han
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Hyoun Cho
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Hye-Jeong Lee
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin Hur
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Byoung Wook Choi
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
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14
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Zhao W, Wu Y, Xu Y, Sun Y, Gao P, Tan M, Ma W, Li C, Jin L, Hua Y, Liu J, Li M. The Potential of Radiomics Nomogram in Non-invasively Prediction of Epidermal Growth Factor Receptor Mutation Status and Subtypes in Lung Adenocarcinoma. Front Oncol 2020; 9:1485. [PMID: 31993370 PMCID: PMC6962353 DOI: 10.3389/fonc.2019.01485] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 12/10/2019] [Indexed: 12/13/2022] Open
Abstract
Purpose: Up to 50% of Asian patients with NSCLC have EGFR gene mutations, indicating that selecting eligible patients for EGFR-TKIs treatments is clinically important. The aim of the study is to develop and validate radiomics-based nomograms, integrating radiomics, CT features and clinical characteristics, to non-invasively predict EGFR mutation status and subtypes. Materials and Methods: We included 637 patients with lung adenocarcinomas, who performed the EGFR mutations analysis in the current study. The whole dataset was randomly split into a training dataset (n = 322) and validation dataset (n = 315). A sub-dataset of EGFR-mutant lesions (EGFR mutation in exon 19 and in exon 21) was used to explore the capability of radiomic features for predicting EGFR mutation subtypes. Four hundred seventy-five radiomic features were extracted and a radiomics sore (R-score) was constructed by using the least absolute shrinkage and selection operator (LASSO) regression in the training dataset. A radiomics-based nomogram, incorporating clinical characteristics, CT features and R-score was developed in the training dataset and evaluated in the validation dataset. Results: The constructed R-scores achieved promising performance on predicting EGFR mutation status and subtypes, with AUCs of 0.694 and 0.708 in two validation datasets, respectively. Moreover, the constructed radiomics-based nomograms excelled the R-scores, clinical, CT features alone in terms of predicting EGFR mutation status and subtypes, with AUCs of 0.734 and 0.757 in two validation datasets, respectively. Conclusions: Radiomics-based nomogram, incorporating clinical characteristics, CT features and radiomic features, can non-invasively and efficiently predict the EGFR mutation status and thus potentially fulfill the ultimate purpose of precision medicine. The methodology is a possible promising strategy to predict EGFR mutation subtypes, providing the support of clinical treatment scenario.
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Affiliation(s)
- Wei Zhao
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, China.,Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Yuzhi Wu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, China
| | - Ya'nan Xu
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Yingli Sun
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Pan Gao
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Mingyu Tan
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Weiling Ma
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Cheng Li
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Liang Jin
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Yanqing Hua
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, China
| | - Ming Li
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China.,Diagnosis and Treatment Center of Small Lung Nodules of Huadong Hospital, Shanghai, China.,Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
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15
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Chen ML, Shi AH, Li XT, Wei YY, Qi LP, Sun YS. Is there any correlation between spectral CT imaging parameters and PD-L1 expression of lung adenocarcinoma? Thorac Cancer 2019; 11:362-368. [PMID: 31808285 PMCID: PMC6996992 DOI: 10.1111/1759-7714.13273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 11/15/2019] [Accepted: 11/19/2019] [Indexed: 11/30/2022] Open
Abstract
Background The aim of this study was to explore whether spectral computed tomography (CT) imaging parameters are associated with PD‐L1 expression of lung adenocarcinoma. Methods Spectral CT imaging parameters (iodine concentrations [IC] of lesion in arterial phase [ICLa] and venous phase [ICLv], normalized IC [NICa/NICv]‐normalized to the IC in the aorta, slope of the spectral HU curve [λHUa/λHUv] and enhanced monochromatic CT number [CT40keVa/v, CT70keVa/v] on 40 and 70 keV images) were analyzed in 34 prospectively enrolled lung adenocarcinoma patients with common molecular pathological markers including PD‐L1 expression detected with immunohistochemistry. Patients were divided into two groups: positive PD‐L1 expression and negative PD‐L1 expression groups. Two‐sample Mann‐Whitney U test was used to test the difference of spectral CT imaging parameters between the two groups. Results The CT40keVa (127.03 ± 37.92 vs. −54.69 ± 262.04), CT40keVv (124.39 ± 34.71 vs. −45.73 ± 238.97), CT70keVa (49.56 ± 11.76 vs. −136.51 ± 237.08) and CT70keVv (46.13 ± 15.81 vs. −133.10 ± 230.72) parameters in the positive PD‐L1 expression group of lung adenocarcinoma were significantly higher than the negative PD‐L1 expression group (all P < 0.05). There was no difference detected in IC, NIC and λHU of the arterial and venous phases between both groups (all P > 0.05). Conclusion CT40keVa, CT40keVv, CT70keVa and CT70keVv were increased in positive PD‐L1 expression. These parameters may be used to distinguish the PD‐L1 expression state of lung adenocarcinoma.
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Affiliation(s)
- Mai-Lin Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology of Department, Peking University Cancer Hospital & Institute, Beijing, China
| | - An-Hui Shi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiotherapy of Department, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiao-Ting Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology of Department, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yi-Yuan Wei
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology of Department, Peking University Cancer Hospital & Institute, Beijing, China
| | - Li-Ping Qi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology of Department, Peking University Cancer Hospital & Institute, Beijing, China
| | - Ying-Shi Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology of Department, Peking University Cancer Hospital & Institute, Beijing, China
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CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis. Int J Clin Oncol 2019; 24:649-659. [PMID: 30835006 DOI: 10.1007/s10147-019-01403-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2018] [Accepted: 01/17/2019] [Indexed: 12/12/2022]
Abstract
INTRODUCTION To systematically analyze CT and clinical characteristics to find out the risk factors of epidermal growth factor receptor (EGFR) mutation in non-small cell lung cancer (NSCLC). Then the significant characteristics were used to set up a mathematic model to predict EGFR mutation in NSCLC. MATERIALS AND METHODS PubMed, Web of Knowledge and EMBASE up to August 17, 2018 were systematically searched for relevant studies that investigated the evidence of association between CT and clinical characteristics and EGFR mutation in NSCLC. After study selection, data extraction, and quality assessment, the pooled odds ratios (ORs) were calculated. Then from May 2017 to August 2018, all NSCLC received EGFR mutation examination and CT examination in our hospital were chosen to test the prediction model by receiver operating characteristic (ROC) curves. RESULTS Seventeen original studies met the inclusion criteria. The results showed that the ORs of ground-glass opacity (GGO), air bronchogram, pleural retraction, vascular convergence, smoking history, female gender were, respectively, 1.93 (P = 0.003), 2.09 (P = 0.03), 1.59 (P < 0.01), 1.61 (P = 0.001), 0.28 (P < 0.01), 0.35 (P < 0.01). The result of speculation, cavitation/bubble-like lucency, lesion shape, margin, pathological stage were, respectively, 1.19 (P = 0.32), 0.99 (P = 0.97), 0.82 (P = 0.42), 1.02 (P = 0.90), 0.77 (P = 0.30). 121 NSCLC received EGFR mutation test were included to test the prediction model. The mathematical model based on the results of meta-analysis was: 0.74 × air bronchogram + 0.46 × pleural retraction + 0.48 × vascular convergence - 1.27 × non-smoking history - 1.05 × female. The area under the ROC curve was 0.68. CONCLUSION Based on the current evidence, GGO presence, air bronchogram, pleural retraction, vascular convergence were significant risk factors of EGFR mutation in NSCLC. And the prediction model can help to predict EGFR mutation status.
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17
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Qiu X, Yuan H, Sima B. Relationship between EGFR mutation and computed tomography characteristics of the lung in patients with lung adenocarcinoma. Thorac Cancer 2018; 10:170-174. [PMID: 30516345 PMCID: PMC6360198 DOI: 10.1111/1759-7714.12928] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 11/07/2018] [Accepted: 11/10/2018] [Indexed: 01/16/2023] Open
Abstract
Background The aim of this study was to investigate the relationship between EGFR mutation and computed tomography (CT) features in patients with adenocarcinoma of the lung. Methods One hundred and ninety two lung adenocarcinoma patients who underwent surgery were retrospectively included in this study. Examination of EGFR gene mutation was performed on all resected tumor samples. The 192 recruited lung adenocarcinoma patients were divided into groups according to EGFR mutation status: patients with mutations in exons 18–21 (effective mutated, n = 61) and non‐mutated (n = 131). The clinical characteristics and lung CT imaging features of the two groups were recorded and compared. Univariate and logistic regression analysis were performed to identify the independent risk factors relevant to effective EGFR gene mutation. Results The independent risk factors relevant to effective EGFR mutation were evaluated by logistic regression test. The results indicated that female gender (odds ratio [OR] 3.23), lung CT features of lymphangitis carcinomatosa (OR 2.66), semi‐solid lesion density (OR 3.56), and spicule sign (OR 1.61) were independent risk factors relevant to EGFR mutation. Conclusion Female patients with lung CT features of lymphangitis carcinomatosa, semi‐solid lesion density, and spicule sign are more prone to harbor EGFR gene mutations and are more likely to benefit from targeted therapy.
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Affiliation(s)
- Xiaowei Qiu
- Department of Radiology, Hangzhou Red Cross Hospital, Hangzhou, China
| | - Hang Yuan
- Department of Radiology, Hangzhou Red Cross Hospital, Hangzhou, China
| | - Bin Sima
- Department of Radiology, Hangzhou Red Cross Hospital, Hangzhou, China
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Shi Z, Zheng X, Shi R, Song C, Yang R, Zhang Q, Wang X, Lu J, Yu Y, Jiang T. Score for lung adenocarcinoma in China with EGFR mutation of exon 19: Combination of clinical and radiological characteristics analysis. Medicine (Baltimore) 2018; 97:e12537. [PMID: 30235778 PMCID: PMC6160170 DOI: 10.1097/md.0000000000012537] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 08/31/2018] [Indexed: 01/17/2023] Open
Abstract
BACKGROUD The biopsy samples might be the only tumor material available for testing the EGFR mutation status in some cases, but these samples are often composed of variable ratios of tumor to normal cells. In this study, we sought to build a scoring system to predict Epidermal growth factor receptor (EGFR) exon 19 mutation in lung adenocarcinoma by clinical and radiological features. METHODS Enrolled in this study were 601 patients with lung adenocarcinoma. Qualitative evaluation of the clinical and radiological features included 25 aspects. Statistical analysis was used to assess the association of these features between the EGFR wild type and exon 19 mutation, based on a clinical scoring system built by the statistical model and the experience of the radiologists. RESULTS EGRF-exon-19-mutation was associated with the female gender [odds ratios (OR), 2.573; 95% confidence intervals (CI), 1.689-3.920], tumor maximum diameter (OR, 0.357; 95% CI, 0.235-0.542), the absence of emphysema (OR, 0.202; 95% CI, 0.110-0.368), the absence of fibrosis (OR, 0.168; 95% CI, 0.083-0.339), and pleural retraction (OR, 2.170; 95% CI, 1.434-3.285). The clinical scoring model assigned 3 points to the female gender, 2 points to small tumor maximum diameter (≤34.5 mm), 2 to the absence of emphysema, 2 to the absence of fibrosis, and 1 to the presence of pleural retraction. CONCLUSIONS The scoring system based on the statistical analysis of clinical and radiological features may be a new alternative to the prediction of EGFR mutation subtypes.
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Affiliation(s)
| | - Xuan Zheng
- Clinical Nutrition Department, Changhai Hospital, Second Military Medical University, Shanghai
| | | | | | - Runhong Yang
- Department of Radiology, Yanan University Affiliated Hospital, Shanxi
| | | | | | | | - Yongwei Yu
- Department of Pathology, Changhai Hospital, Second Military Medical University, Shanghai, China
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Suh YJ, Lee HJ, Kim YJ, Kim KG, Kim H, Jeon YK, Kim YT. Computed tomography characteristics of lung adenocarcinomas with epidermal growth factor receptor mutation: A propensity score matching study. Lung Cancer 2018; 123:52-59. [PMID: 30089595 DOI: 10.1016/j.lungcan.2018.06.030] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 06/13/2018] [Accepted: 06/27/2018] [Indexed: 02/04/2023]
Abstract
OBJECTIVES We investigated the relationship between computed tomography (CT) characteristics and epidermal growth factor receptor (EGFR) mutations in a large Asian cohort who received surgical resection of invasive lung adenocarcinoma. MATERIALS AND METHODS We retrospectively included 864 patients (524 with EGFR mutation and 340 with EGFR wild-type) who received surgical resections for invasive lung adenocarcinomas. After applying propensity score matching, 312 patients with mutated EGFR were matched with 312 patients with wild-type EGFR. CT characteristics, predominant histologic subtype, and CT measurement parameters (volume and estimated diameter of the total tumor and inner solid portion and ground-glass opacity [GGO] proportion) were compared within matched pairs. RESULTS Tumors in the EGFR mutation group showed higher proportions of pure ground-glass nodules (4.1% vs 1.3%), GGO-predominant (23.7% vs 14.7%), and solid-predominant part-solid nodules (37.2% vs 31.7%) CT characteristics, whereas EGFR wild-type tumors predominantly presented as pure solid nodules (34.6% vs 52.2%, P < 0.0001). EGFR mutation tumors more frequently had a lepidic-predominant subtype than did EGFR wild-type tumors (20.2% and 11.9%; P < 0.0001), and showed a smaller whole tumor size and solid portion (P < 0.0001) with a higher GGO proportion (P < 0.0001). Tumors with exon 21 missense mutations showed the highest GGO proportion and the smallest inner solid portion size, followed by tumors harboring an exon 19 deletion, compared with EGFR wild-type tumors (posthoc P < 0.01). CONCLUSION Adenocarcinomas with EGFR mutations had a higher GGO proportion than those with wild-type EGFR after matching of clinical variables. Lesions with an exon 21 mutation had a higher GGO proportion than lesions with other mutations.
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Affiliation(s)
- Young Joo Suh
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongnogu, Seoul, 03080, Republic of Korea; Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Republic of Korea
| | - Hyun-Ju Lee
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongnogu, Seoul, 03080, Republic of Korea.
| | - Young Jae Kim
- Department of Biomedical Engineering, Gachon University College of Medicine, Incheon, Republic of Korea
| | - Kwang Gi Kim
- Department of Biomedical Engineering, Gachon University College of Medicine, Incheon, Republic of Korea
| | - Heekyung Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongnogu, Seoul, 03080, Republic of Korea
| | - Yoon Kyung Jeon
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Young Tae Kim
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
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Lv J, Zhang H, Ma J, Ma Y, Gao G, Song Z, Yang Y. Comparison of CT radiogenomic and clinical characteristics between EGFR and KRAS mutations in lung adenocarcinomas. Clin Radiol 2018; 73:590.e1-590.e8. [DOI: 10.1016/j.crad.2018.01.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 01/11/2018] [Indexed: 01/26/2023]
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Abstract
Non-small cell lung cancer (NSCLC) is usually diagnosed when it is not amenable to curative surgery or radiation. Many of these patients are candidates for systemic therapy. Median survival is only approximately 10 months, and, accordingly, treatment in advanced NSCLC is evolving toward a more personalized approach with the identification of genetic abnormalities based on biomarkers. For example, gene mutations in EGFR (epidermal growth factor receptor) and ALK (anaplastic lymphoma kinase) lead to a cascade of pathways resulting in uncontrolled growth, proliferation, and survival of tumor cells. Targeted therapies are aimed at the products of these mutated genes and include agents such as erlotinib and gefitinib (in EGFR-mutant NSCLC) or crizotinib (in ALK-positive NSCLC). Antiangiogenesis agents such as bevacizumab are another category of targeted therapy that inhibits vascular endothelial growth factors. The imaging characteristics of advanced NSCLC with genetic abnormalities, the evolution of targeted therapies and their imaging manifestations will be discussed.
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Cao Y, Xu H. A new predictive scoring system based on clinical data and computed tomography features for diagnosing EGFR-mutated lung adenocarcinoma. ACTA ACUST UNITED AC 2018; 25:e132-e138. [PMID: 29719437 DOI: 10.3747/co.25.3805] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background We aimed to develop a new EGFR mutation-predictive scoring system to use in screening for EGFR-mutated lung adenocarcinomas (lacs). Methods The study enrolled 279 patients with lac, including 121 patients with EGFR wild-type tumours and 158 with EGFR-mutated tumours. The Student t-test, chi-square test, or Fisher exact test was applied to discriminate clinical and computed tomography (ct) features between the two groups. Using a principal component analysis (pca) model, we derived predictive coefficients for the presence of EGFR mutation in lac. Results The EGFR mutation-predictive score includes sex, smoking history, homogeneity, ground-glass opacity (ggo) on imaging, and the presence of pericardial effusion. The pca predictive model took this form: [Formula: see text]Model scores ranged from 79 to 147. The area under the receiver operating characteristic curve was 0.752 [95% confidence interval (ci): 0.697 to 0.801] in the lac population at the optimal cut-off value of 109, and the sensitivity and specificity were 68.4% (95% ci: 60.5% to 75.5%) and 74.4% (95% ci: 65.6% to 81.9%) respectively. Conclusions The EGFR mutation risk scoring system based on clinical data and ct features is noninvasive and user-friendly. The model appears to frame a positive predictive value and was able to determine the value of repeating a biopsy if tissue is limited.
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Affiliation(s)
- Y Cao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, P.R.C
| | - H Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, P.R.C
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23
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Shroff GS, de Groot PM, Papadimitrakopoulou VA, Truong MT, Carter BW. Targeted Therapy and Immunotherapy in the Treatment of Non-Small Cell Lung Cancer. Radiol Clin North Am 2018; 56:485-495. [PMID: 29622080 DOI: 10.1016/j.rcl.2018.01.012] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The treatment strategy in advanced non-small cell lung cancer (NSCLC) has evolved from empirical chemotherapy to a personalized approach based on histology and molecular markers of primary tumors. Targeted therapies are directed at the products of oncogenic driver mutations. Immunotherapy facilitates the recognition of cancer as foreign by the host immune system, stimulates the immune system, and alleviates the inhibition that allows the growth and spread of cancer cells. The authors describes the role of targeted therapy and immunotherapy in the treatment of NSCLC, patterns of disease present on imaging studies, and immune-related adverse events encountered with immunotherapy.
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Affiliation(s)
- Girish S Shroff
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Patricia M de Groot
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Vassiliki A Papadimitrakopoulou
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Mylene T Truong
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Brett W Carter
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.
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24
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Jansen RW, van Amstel P, Martens RM, Kooi IE, Wesseling P, de Langen AJ, Menke-Van der Houven van Oordt CW, Jansen BHE, Moll AC, Dorsman JC, Castelijns JA, de Graaf P, de Jong MC. Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis. Oncotarget 2018; 9:20134-20155. [PMID: 29732009 PMCID: PMC5929452 DOI: 10.18632/oncotarget.24893] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 02/26/2018] [Indexed: 12/12/2022] Open
Abstract
With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including EGFR-mutations and ALK-rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.
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Affiliation(s)
- Robin W Jansen
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Paul van Amstel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Roland M Martens
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Irsan E Kooi
- Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
| | - Pieter Wesseling
- Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands.,Department of Pathology, Princess Máxima Center for Pediatric Oncology and University Medical Center Utrecht, Utrecht, The Netherlands
| | - Adrianus J de Langen
- Department of Respiratory Diseases, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Bernard H E Jansen
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Annette C Moll
- Department of Ophthalmology, VU University Medical Center, Amsterdam, The Netherlands
| | - Josephine C Dorsman
- Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
| | - Jonas A Castelijns
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Pim de Graaf
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Marcus C de Jong
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
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25
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Shi Z, Zheng X, Shi R, Song C, Yang R, Zhang Q, Wang X, Lu J, Yu Y, Liu Q, Jiang T. Radiological and Clinical Features associated with Epidermal Growth Factor Receptor Mutation Status of Exon 19 and 21 in Lung Adenocarcinoma. Sci Rep 2017; 7:364. [PMID: 28336963 PMCID: PMC5428650 DOI: 10.1038/s41598-017-00511-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Accepted: 02/28/2017] [Indexed: 11/23/2022] Open
Abstract
The exon 19 and 21 in Epidermal Growth Factor Receptor (EGFR) mutation are the most common subtype of lung adenocarcinoma, and the strongest predictive biomarker for progression-free survival and tumor response. Although some studies have shown differences in radiological features between cases with and without EFGR mutations, they lacked necessary stratification. This article is to evaluate the association of CT features between the wild type and the subtype (exon 19 and 21) of EGFR mutations in patients with lung adenocarcinoma. Of the 721 finally included patients, 132 were positive for EGFR mutation in exon 19, 140 were positive for EGFR mutation in exon 21, and 449 were EGFR wild type. EGFR mutation in exon 19 was associated with a small-maximum diameter (28.51 ± 14.07) (p < 0.0001); sex (p < 0.0001); pleural retraction (p = 0.0034); and the absence of fibrosis (p < 0.0001), while spiculated margins (p = 0.0095), subsolid density (p < 0.0001) and no smoking (p < 0.0001) were associated with EGFR mutation in exon 21. Receiver Operating Characteristic (ROC) curves suggested that the maximum Area Under the Curve (AUC) was related to the female gender (AUC = 0.636) and the absence of smoking (AUC = 0.681). This study demonstrated the radiological and clinical features could be used to prognosticate EGFR mutation subtypes in exon 19 and 21.
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Affiliation(s)
- Zhang Shi
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Xuan Zheng
- Clinical Nutrition Department, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Ruifeng Shi
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Changen Song
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Runhong Yang
- Department of Radiology, Yanan University affiliated hospital, Shanxi, China
| | - Qianwen Zhang
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Xinrui Wang
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Jianping Lu
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Yongwei Yu
- Department of Pathology, Changhai Hospital, Second Military Medical University, Shanghai, China.
| | - Qi Liu
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China.
| | - Tao Jiang
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China.
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26
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Imaging Characteristics of Driver Mutations in EGFR, KRAS, and ALK among Treatment-Naïve Patients with Advanced Lung Adenocarcinoma. PLoS One 2016; 11:e0161081. [PMID: 27518729 PMCID: PMC4982673 DOI: 10.1371/journal.pone.0161081] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 07/31/2016] [Indexed: 12/11/2022] Open
Abstract
This study aimed to identify the computed tomography characteristics of treatment-naïve patients with lung adenocarcinoma and known driver mutations in EGFR, KRAS, or ALK. Patients with advanced lung adenocarcinoma (stage IIIB-IV) and known mutations in EGFR, KRAS, or ALK were assessed. The radiological findings for the main tumor and intra-thoracic status were retrospectively analyzed in each group, and the groups' characteristics were compared. We identified 265 treatment-naïve patients with non-small-cell carcinoma, who had EGFR mutations (n = 159), KRAS mutations (n = 55), or ALK rearrangements (n = 51). Among the three groups, we evaluated only patients with stage IIIB-IV lung adenocarcinoma who had EGFR mutations (n = 126), KRAS mutations (n = 35), or ALK rearrangements (n = 47). We found that ground-glass opacity at the main tumor was significantly more common among EGFR-positive patients, compared to ALK-positive patients (p = 0.009). Lymphadenopathy was significantly more common among ALK-positive patients, compared to EGFR-positive patients (p = 0.003). Extranodal invasion was significantly more common among ALK-positive patients, compared to EGFR-positive patients and KRAS-positive patients (p = 0.001 and p = 0.049, respectively). Lymphangitis was significantly more common among ALK-positive patients, compared to EGFR-positive patients (p = 0.049). Pleural effusion was significantly less common among KRAS-positive patients, compared to EGFR-positive patients and ALK-positive patients (p = 0.046 and p = 0.026, respectively). Lung metastases were significantly more common among EGFR-positive patients, compared to KRAS-positive patients and ALK-positive patients (p = 0.007 and p = 0.04, respectively). In conclusion, EGFR mutations were associated with ground-glass opacity, KRAS-positive tumors were generally solid and less likely to metastasize to the lung and pleura, and ALK-positive tumors tended to present with lymphadenopathy, extranodal invasion, and lymphangitis. These mutation-specific imaging characteristics may be related to the biological differences between these cancers.
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