1
|
Azour L, Oh AS, Prosper AE, Toussie D, Villasana-Gomez G, Pourzand L. Subsolid Nodules: Significance and Current Understanding. Clin Chest Med 2024; 45:263-277. [PMID: 38816087 DOI: 10.1016/j.ccm.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Subsolid nodules are heterogeneously appearing and behaving entities, commonly encountered incidentally and in high-risk populations. Accurate characterization of subsolid nodules, and application of evolving surveillance guidelines, facilitates evidence-based and multidisciplinary patient-centered management.
Collapse
Affiliation(s)
- Lea Azour
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Box 957437, 757 Westwood Plaza, Los Angeles, CA 90095-7437, USA.
| | - Andrea S Oh
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Box 957437, 757 Westwood Plaza, Los Angeles, CA 90095-7437, USA
| | - Ashley E Prosper
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Box 957437, 757 Westwood Plaza, Los Angeles, CA 90095-7437, USA
| | - Danielle Toussie
- Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, 660 1st Avenue, New York, NY 10016, USA
| | - Geraldine Villasana-Gomez
- Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, 660 1st Avenue, New York, NY 10016, USA
| | - Lila Pourzand
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Box 957437, 757 Westwood Plaza, Los Angeles, CA 90095-7437, USA
| |
Collapse
|
2
|
Chen Q, Cheng J, Wang L, Lv X, Hu J. Primary lung cancer in children and adolescents. J Cancer Res Clin Oncol 2024; 150:225. [PMID: 38695944 PMCID: PMC11065912 DOI: 10.1007/s00432-024-05750-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 04/11/2024] [Indexed: 05/05/2024]
Abstract
PURPOSE Primary lung cancer is extremely rare in children and adolescents. The aim of this study is to clarify clinical features and outcomes of primary lung cancer in children and adolescents. METHODS Young patients (aged ≤ 20 years) diagnosed as primary lung cancer between 2012 and 2023 were retrospective reviewed. According to radiological appearance of the nodules, they were divided into solid nodule (SN) group and ground glass opacity (GGO) group. RESULTS A total of 74 patients were identified, with a median age at diagnosis of 18 years old (range: 11-20), including 7 patients in SN group and 67 patients in GGO group. In the GGO group, none of the nodules enlarged or changed during an average surveillance period of 10.8 months before surgery, except one. Wedge resection was the most common procedure (82.1%), followed by segmentectomy (16.4%) and lobectomy (1.5%). Histopathological analysis revealed that 64.2% of GGO nodules were adenocarcinoma in situ and minimally invasive adenocarcinomas, while the remaining 35.8% were invasive adenocarcinomas. Mutational analysis was performed in nine patients, with mutations identified in all cases. After a mean follow-up period of 1.73 ± 1.62 years, two patients in the SN group died due to multiple distant metastases, while all patients in the GGO group survived without recurrence. The overall survival (100%) of the GGO group was significantly higher than SN group (66.7%). CONCLUSIONS Primary lung cancer in children and adolescents are rare and histopathological heterogeneous. Persistent GGO nodules may indicate early-stage lung adenocarcinoma in children and adolescents.
Collapse
Affiliation(s)
- Qiuming Chen
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Jun Cheng
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Luming Wang
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiayi Lv
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jian Hu
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| |
Collapse
|
3
|
Chang YC, Chen PT, Hsieh MS, Huang YS, Ko WC, Lin MW, Hsu HH, Chen JS, Chang YC. Discrimination of invasive lung adenocarcinoma from Lung-RADS category 2 nonsolid nodules through visual assessment: a retrospective study. Eur Radiol 2024; 34:3453-3461. [PMID: 37914975 DOI: 10.1007/s00330-023-10317-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 09/11/2023] [Accepted: 09/24/2023] [Indexed: 11/03/2023]
Abstract
OBJECTIVES Invasive adenocarcinomas (IADs) have been identified among nonsolid nodules (NSNs) assigned as Lung Imaging Reporting and Data System (Lung-RADS) category 2. This study used visual assessment for differentiating IADs from noninvasive lesions (NILs) in this category. METHODS This retrospective study included 222 patients with 242 NSNs, which were resected after preoperative computed tomography (CT)-guided dye localization. Visual assessment was performed by using the lung and bone window (BW) settings to classify NSNs into BW-visible (BWV) and BW-invisible (BWI) NSNs. In addition, nodule size, shape, border, CT attenuation, and location were evaluated and correlated with histopathological results. Logistic regression was performed for multivariate analysis. A p value of < 0.05 was considered statistically significant. RESULTS A total of 242 NSNs (mean diameter, 7.6 ± 2.8 mm), including 166 (68.6%) BWV and 76 (31.4%) BWI NSNs, were included. IADs accounted for 31% (75) of the nodules. Only 4 (5.3%) IADs were identified in the BWI group and belonged to the lepidic-predominant (n = 3) and acinar-predominant (n = 1) subtypes. In univariate analysis for differentiating IADs from NILs, the nodule size, shape, CT attenuation, and visual classification exhibited statistical significance. Nodule size and visual classification were the significant predictors for IAD in multivariate analysis with logistic regression (p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of visual classification in IAD prediction were 94.7%, 43.1%, 42.8%, and 94.7%, respectively. CONCLUSIONS The window-based visual classification of NSNs is a simple and objective method to discriminate IADs from NILs. CLINICAL RELEVANCE STATEMENT The present study shows that using the bone window to classify nonsolid nodules helps discriminate invasive adenocarcinoma from noninvasive lesions. KEY POINTS • Evidence has shown the presence of lung adenocarcinoma in Lung-RADS category 2 nonsolid nodules. • Nonsolid nodules are classified into the bone window-visible and the bone window-invisible nonsolid nodules, and this classification differentiates invasive adenocarcinoma from noninvasive lesions. • The Lung-RADS category 2 nonsolid nodules are unlikely invasive adenocarcinoma if they show nonvisualization in the bone window.
Collapse
Affiliation(s)
- Yu-Chien Chang
- Department of Medical Imaging, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Po-Ting Chen
- Department of Medical Imaging, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Min-Shu Hsieh
- Department of Pathology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yu-Sen Huang
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Wei-Chun Ko
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Mong-Wei Lin
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsao-Hsun Hsu
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Jin-Shing Chen
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yeun-Chung Chang
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan.
- Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan.
| |
Collapse
|
4
|
Chuang H, Yun L, Jiang-Ping L, Li L, Liang-Shan L, Ting-Yuan L, Qing-HUa L, He-Nan L, Dong-Yuan L, Xue-Quan H. Predicting subsolid pulmonary nodules before percutaneous needle biopsy: a comparison of artificial neural network and biopsy results. Clin Radiol 2024; 79:e453-e461. [PMID: 38160104 DOI: 10.1016/j.crad.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 11/24/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
AIM To establish an artificial neural network (ANN) model to predict subsolid nodules (SSNs) before percutaneous core-needle biopsy (PCNB). The results of the two methods were compared to provide guidance on the treatment of SSNs. MATERIALS AND METHODS This was a single-centre retrospective study using data from 1,459 SSNs between 2013 and 2021. The ANN was developed using data from patients who underwent surgery following computed tomography (CT) (SFC) and validated using data from patients who underwent surgery following biopsy (SFB). The prediction results of the ANN for the PCNB group and the histopathological results obtained after biopsy were compared with the histopathological results of lung nodules in the same group after surgery. Additionally, the choice of predictors for PCNB was analysed using multivariate analysis. RESULTS There was no significant difference between the accuracies of the ANN and PCNB in the SFB group (p=0.086). The sensitivity of PCNB was lower than that of the ANN (p=0.000), but the specificity was higher (p=0.001). PCNB had better diagnostic ability than the ANN. The incidence of precursor lesions and non-neoplastic lesions in the SFB group was lower than that in the SFC group (p=0.000). A history of malignant tumours, size (2-3 cm), volume (>400 cm3) and mean CT value (≥-450 HU) are important factors for selecting PCNB. CONCLUSIONS Both ANN and PCNB have comparable accuracy in diagnosing SSNs; however, PCNB has a slightly higher diagnostic ability than ANN. Selecting appropriate patients for PCNB is important for maximising the benefit to SSN patients.
Collapse
Affiliation(s)
- H Chuang
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - L Yun
- Department of Cancer Centre, Da-ping Hospital, Army Medical University, Chongqing, China
| | - L Jiang-Ping
- Department of Interventional, Three Gorges Hospital of Chongqing University, Chongqing, China
| | - L Li
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - L Liang-Shan
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - L Ting-Yuan
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - L Qing-HUa
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - L He-Nan
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - L Dong-Yuan
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China
| | - H Xue-Quan
- Department of Nuclear Medicine (Treatment Centre of Minimally Invasive Intervention and Radioactive Particles), First Affiliated Hospital of Army Medical University, Chongqing, China.
| |
Collapse
|
5
|
Xue M, Li R, Wang K, Liu W, Liu J, Li Z, Chen G, Zhang H, Tian H. Construction and validation of a predictive model of invasive adenocarcinoma in pure ground-glass nodules less than 2 cm in diameter. BMC Surg 2024; 24:56. [PMID: 38355554 PMCID: PMC10868041 DOI: 10.1186/s12893-024-02341-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024] Open
Abstract
OBJECTIVES In this study, we aimed to develop a multiparameter prediction model to improve the diagnostic accuracy of invasive adenocarcinoma in pulmonary pure glass nodules. METHOD We included patients with pulmonary pure glass nodules who underwent lung resection and had a clear pathology between January 2020 and January 2022 at the Qilu Hospital of Shandong University. We collected data on the clinical characteristics of the patients as well as their preoperative biomarker results and computed tomography features. Thereafter, we performed univariate and multivariate logistic regression analyses to identify independent risk factors, which were then used to develop a prediction model and nomogram. We then evaluated the recognition ability of the model via receiver operating characteristic (ROC) curve analysis and assessed its calibration ability using the Hosmer-Lemeshow test and calibration curves. Further, to assess the clinical utility of the nomogram, we performed decision curve analysis. RESULT We included 563 patients, comprising 174 and 389 cases of invasive and non-invasive adenocarcinoma, respectively, and identified seven independent risk factors, namely, maximum tumor diameter, age, serum amyloid level, pleural effusion sign, bronchial sign, tumor location, and lobulation. The area under the ROC curve was 0.839 (95% CI: 0.798-0.879) for the training cohort and 0.782 (95% CI: 0.706-0.858) for the validation cohort, indicating a relatively high predictive accuracy for the nomogram. Calibration curves for the prediction model also showed good calibration for both cohorts, and decision curve analysis showed that the clinical prediction model has clinical utility. CONCLUSION The novel nomogram thus constructed for identifying invasive adenocarcinoma in patients with isolated pulmonary pure glass nodules exhibited excellent discriminatory power, calibration capacity, and clinical utility.
Collapse
Affiliation(s)
- Mengchao Xue
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Rongyang Li
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Kun Wang
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Wen Liu
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Junjie Liu
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Zhenyi Li
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Guanqing Chen
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Huiying Zhang
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China
| | - Hui Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Lixia District, Jinan, Shandong Province, China.
| |
Collapse
|
6
|
Zhang R, Wei Y, Wang D, Chen B, Sun H, Lei Y, Zhou Q, Luo Z, Jiang L, Qiu R, Shi F, Li W. Deep learning for malignancy risk estimation of incidental sub-centimeter pulmonary nodules on CT images. Eur Radiol 2023:10.1007/s00330-023-10518-1. [PMID: 38114849 DOI: 10.1007/s00330-023-10518-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 09/18/2023] [Accepted: 11/11/2023] [Indexed: 12/21/2023]
Abstract
OBJECTIVES To establish deep learning models for malignancy risk estimation of sub-centimeter pulmonary nodules incidentally detected by chest CT and managed in clinical settings. MATERIALS AND METHODS Four deep learning models were trained using CT images of sub-centimeter pulmonary nodules from West China Hospital, internally tested, and externally validated on three cohorts. The four models respectively learned 3D deep features from the baseline whole lung region, baseline image patch where the nodule located, baseline nodule box, and baseline plus follow-up nodule boxes. All regions of interest were automatically segmented except that the nodule boxes were additionally manually checked. The performance of models was compared with each other and that of three respiratory clinicians. RESULTS There were 1822 nodules (981 malignant) in the training set, 806 (416 malignant) in the testing set, and 357 (253 malignant) totally in the external sets. The area under the curve (AUC) in the testing set was 0.754, 0.855, 0.928, and 0.942, respectively, for models derived from baseline whole lung, image patch, nodule box, and the baseline plus follow-up nodule boxes. When baseline models externally validated (follow-up images not available), the nodule-box model outperformed the other two with AUC being 0.808, 0.848, and 0.939 respectively in the three external datasets. The resident, junior, and senior clinicians achieved an accuracy of 67.0%, 82.5%, and 90.0%, respectively, in the testing set. The follow-up model performed comparably to the senior clinician. CONCLUSION The deep learning algorithms solely mining nodule information can efficiently predict malignancy of incidental sub-centimeter pulmonary nodules. CLINICAL RELEVANCE STATEMENT The established models may be valuable for supporting clinicians in routine clinical practice, potentially reducing the number of unnecessary examinations and also delays in diagnosis. KEY POINTS • According to different regions of interest, four deep learning models were developed and compared to evaluate the malignancy of sub-centimeter pulmonary nodules by CT images. • The models derived from baseline nodule box or baseline plus follow-up nodule boxes demonstrated sufficient diagnostic accuracy (86.4% and 90.4% in the testing set), outperforming the respiratory resident (67.0%) and junior clinician (82.5%). • The proposed deep learning methods may aid clinicians in optimizing follow-up recommendations for sub-centimeter pulmonary nodules and may lead to fewer unnecessary diagnostic interventions.
Collapse
Affiliation(s)
- Rui Zhang
- Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
- General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ying Wei
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai, China
| | - Denian Wang
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Bojiang Chen
- Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Lei
- General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
| | - Qing Zhou
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai, China
| | - Zhuang Luo
- Department of Pulmonary and Critical Care Medicine, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Li Jiang
- Department of Respiratory and Critical Care Medicine, the Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Rong Qiu
- Department of Respiratory and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, China
| | - Feng Shi
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai, China.
| | - Weimin Li
- Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
| |
Collapse
|
7
|
Ma ZJ, Ma ZX, Sun YL, Li DC, Jin L, Gao P, Li C, Li M. Prediction of subsolid pulmonary nodule growth rate using radiomics. BMC Med Imaging 2023; 23:177. [PMID: 37936095 PMCID: PMC10629176 DOI: 10.1186/s12880-023-01143-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/27/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND Pulmonary nodule growth rate assessment is critical in the management of subsolid pulmonary nodules (SSNs) during clinical follow-up. The present study aimed to develop a model to predict the growth rate of SSNs. METHODS A total of 273 growing SSNs with clinical information and 857 computed tomography (CT) scans were retrospectively analyzed. The images were randomly divided into training and validation sets. All images were categorized into fast-growth (volume doubling time (VDT) ≤ 400 days) and slow-growth (VDT > 400 days) groups. Models for predicting the growth rate of SSNs were developed using radiomics and clinical features. The models' performance was evaluated using the area under the curve (AUC) values for the receiver operating characteristic curve. RESULTS The fast- and slow-growth groups included 108 and 749 scans, respectively, and 10 radiomics features and three radiographic features (nodule density, presence of spiculation, and presence of vascular changes) were selected to predict the growth rate of SSNs. The nomogram integrating radiomics and radiographic features (AUC = 0.928 and AUC = 0.905, respectively) performed better than the radiographic (AUC = 0.668 and AUC = 0.689, respectively) and radiomics (AUC = 0.888 and AUC = 0.816, respectively) models alone in both the training and validation sets. CONCLUSION The nomogram model developed by combining radiomics with radiographic features can predict the growth rate of SSNs more accurately than traditional radiographic models. It can also optimize clinical treatment decisions for patients with SSNs and improve their long-term management.
Collapse
Affiliation(s)
- Zong Jing Ma
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - Zhuang Xuan Ma
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - Ying Li Sun
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - De Chun Li
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - Liang Jin
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - Pan Gao
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - Cheng Li
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China
| | - Ming Li
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, 200040, China.
| |
Collapse
|
8
|
Wei Z, Chi J, Cao P, Jin Y, Li X, Ye X. Microwave ablation with a blunt-tip antenna for pulmonary ground-glass nodules: a retrospective, multicenter, case-control study. LA RADIOLOGIA MEDICA 2023; 128:1061-1069. [PMID: 37458905 PMCID: PMC10474204 DOI: 10.1007/s11547-023-01672-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 06/25/2023] [Indexed: 09/02/2023]
Abstract
PURPOSE A previous small-sample study verified that a blunt-tip antenna reduced hemorrhage during microwave ablation. We conducted this large-sample, multicenter, case-control study to further verify the efficacy and safety of microwave ablation with a blunt-tip antenna for ground-glass nodules. MATERIALS AND METHODS Patients with pulmonary ground-glass nodules were treated with either a sharp-tip (Group A) or blunt-tip antenna (Group B). A total of 147 and 150 patients were retrospectively allocated to Groups A and Group B, respectively. Group A patients underwent 151 procedures, and Group B patients underwent 153 procedures. We assessed the technical success, technique efficacy, and complications. RESULTS Technical success and overall technique efficacy were achieved in all patients (100%). Major complications of pneumothorax were more commonly observed in Group A than in Group B (19.7% vs. 2.0%, p < 0.001). Minor complications, such as intrapulmonary hemorrhage (2.0% vs. 9.5%, p = 0.005) and hemothorax (0.0% vs. 2.7%, p = 0.049), occurred less frequently in Group B compared to Group A. CONCLUSION In the treatment of ground-glass nodules, microwave ablation with a blunt-tip antenna had equal efficacy compared to microwave ablation with a sharp-tip antenna but had a decreased number of hemorrhage and hemothorax complications.
Collapse
Affiliation(s)
- Zhigang Wei
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, 250014, Shandong, China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Jiachang Chi
- Department of Interventional Oncology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160# Pujian Road, Shanghai, 200127, China
| | - Pikun Cao
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, 250014, Shandong, China
| | - Yong Jin
- Department of Interventional Therapy, The Second Affiliated Hospital of Soochow University, Suzhou, 215000, China.
| | - Xiaoguang Li
- Department of Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100370, China.
| | - Xin Ye
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, 250014, Shandong, China.
| |
Collapse
|
9
|
Huang W, Deng H, Li Z, Xiong Z, Zhou T, Ge Y, Zhang J, Jing W, Geng Y, Wang X, Tu W, Dong P, Liu S, Fan L. Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules. Front Oncol 2023; 13:1255007. [PMID: 37664069 PMCID: PMC10470826 DOI: 10.3389/fonc.2023.1255007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Accepted: 07/28/2023] [Indexed: 09/05/2023] Open
Abstract
Objective To develop and validate the model for predicting benign and malignant ground-glass nodules (GGNs) based on the whole-lung baseline CT features deriving from deep learning and radiomics. Methods This retrospective study included 385 GGNs from 3 hospitals, confirmed by pathology. We used 239 GGNs from Hospital 1 as the training and internal validation set; 115 and 31 GGNs from Hospital 2 and Hospital 3 as the external test sets 1 and 2, respectively. An additional 32 stable GGNs from Hospital 3 with more than five years of follow-up were used as the external test set 3. We evaluated clinical and morphological features of GGNs at baseline chest CT and extracted the whole-lung radiomics features simultaneously. Besides, baseline whole-lung CT image features are further assisted and extracted using the convolutional neural network. We used the back-propagation neural network to construct five prediction models based on different collocations of the features used for training. The area under the receiver operator characteristic curve (AUC) was used to compare the prediction performance among the five models. The Delong test was used to compare the differences in AUC between models pairwise. Results The model integrated clinical-morphological features, whole-lung radiomic features, and whole-lung image features (CMRI) performed best among the five models, and achieved the highest AUC in the internal validation set, external test set 1, and external test set 2, which were 0.886 (95% CI: 0.841-0.921), 0.830 (95%CI: 0.749-0.893) and 0.879 (95%CI: 0.712-0.968), respectively. In the above three sets, the differences in AUC between the CMRI model and other models were significant (all P < 0.05). Moreover, the accuracy of the CMRI model in the external test set 3 was 96.88%. Conclusion The baseline whole-lung CT features were feasible to predict the benign and malignant of GGNs, which is helpful for more refined management of GGNs.
Collapse
Affiliation(s)
- Wenjun Huang
- Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai, China
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong, China
- Department of Radiology, The Second People’s hospital of Deyang, Deyang, Sichuan, China
| | - Heng Deng
- School of Medicine, Shanghai University, Shanghai, China
| | - Zhaobin Li
- Department of Radiation Oncology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Zhanda Xiong
- Department of Artificial Intelligence Medical Imaging, Tron Technology, Shanghai, China
| | - Taohu Zhou
- Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai, China
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong, China
| | - Yanming Ge
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong, China
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Jing Zhang
- Department of Radiology, The Second People’s hospital of Deyang, Deyang, Sichuan, China
| | - Wenbin Jing
- Department of Radiology, The Second People’s hospital of Deyang, Deyang, Sichuan, China
| | - Yayuan Geng
- Clinical Research Institute, Shukun (Beijing) Technology Co., Ltd., Beijing, China
| | - Xiang Wang
- Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Wenting Tu
- Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Peng Dong
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong, China
| | - Shiyuan Liu
- Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Li Fan
- Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai, China
| |
Collapse
|
10
|
Liu YC, Liang CH, Wu YJ, Chen CS, Tang EK, Wu FZ. Managing Persistent Subsolid Nodules in Lung Cancer: Education, Decision Making, and Impact of Interval Growth Patterns. Diagnostics (Basel) 2023; 13:2674. [PMID: 37627933 PMCID: PMC10453827 DOI: 10.3390/diagnostics13162674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
With the popularization of lung cancer screening, many persistent subsolid nodules (SSNs) have been identified clinically, especially in Asian non-smokers. However, many studies have found that SSNs exhibit heterogeneous growth trends during long-term follow ups. This article adopted a narrative approach to extensively review the available literature on the topic to explore the definitions, rationale, and clinical application of different interval growths of subsolid pulmonary nodule management and follow-up strategies. The development of SSN growth thresholds with different growth patterns could support clinical decision making with follow-up guidelines to reduce over- and delayed diagnoses. In conclusion, using different SSN growth thresholds could optimize the follow-up management and clinical decision making of SSNs in lung cancer screening programs. This could further reduce the lung cancer mortality rate and potential harm from overdiagnosis and over management.
Collapse
Affiliation(s)
- Yung-Chi Liu
- Department of Radiology, Xiamen Chang Gung Hospital, Xiamen 361028, China;
- Department of Imaging Technology Division, Xiamen Chang Gung Hospital, Xiamen 361028, China
- Department of Healthcare Administration Department, Xiamen Chang Gung Hospital, Xiamen 361028, China
| | - Chia-Hao Liang
- Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei 112304, Taiwan;
| | - Yun-Ju Wu
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung 81362, Taiwan;
- Department of Software Engineering and Management, National Kaohsiung Normal University, Kaohsiung 80201, Taiwan
| | - Chi-Shen Chen
- Physical Examination Center, Kaohsiung Veterans General Hospital, Kaohsiung 81362, Taiwan;
| | - En-Kuei Tang
- Department of Surgery, Kaohsiung Veterans General Hospital, Kaohsiung 813414, Taiwan;
| | - Fu-Zong Wu
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung 81362, Taiwan;
- School of Medicine, College of Medicine, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
- Faculty of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
- Institute of Education, National Sun Yat-Sen University, Kaohsiung 804241, Taiwan
| |
Collapse
|
11
|
Liu S, Sun Q, Ren X. Novel strategies for cancer immunotherapy: counter-immunoediting therapy. J Hematol Oncol 2023; 16:38. [PMID: 37055849 PMCID: PMC10099030 DOI: 10.1186/s13045-023-01430-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 03/21/2023] [Indexed: 04/15/2023] Open
Abstract
The advent of immunotherapy has made an indelible mark on the field of cancer therapy, especially the application of immune checkpoint inhibitors in clinical practice. Although immunotherapy has proven its efficacy and safety in some tumors, many patients still have innate or acquired resistance to immunotherapy. The emergence of this phenomenon is closely related to the highly heterogeneous immune microenvironment formed by tumor cells after undergoing cancer immunoediting. The process of cancer immunoediting refers to the cooperative interaction between tumor cells and the immune system that involves three phases: elimination, equilibrium, and escape. During these phases, conflicting interactions between the immune system and tumor cells result in the formation of a complex immune microenvironment, which contributes to the acquisition of different levels of immunotherapy resistance in tumor cells. In this review, we summarize the characteristics of different phases of cancer immunoediting and the corresponding therapeutic tools, and we propose normalized therapeutic strategies based on immunophenotyping. The process of cancer immunoediting is retrograded through targeted interventions in different phases of cancer immunoediting, making immunotherapy in the context of precision therapy the most promising therapy to cure cancer.
Collapse
Affiliation(s)
- Shaochuan Liu
- Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, 300060, Tianjin, China
- Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, 300060, Tianjin, China
- Key Laboratory of Cancer Immunology and Biotherapy, 300060, Tianjin, China
- Key Laboratory of Cancer Prevention and Therapy, 300060, Tianjin, China
- Tianjin's Clinical Research Center for Cancer, 300060, Tianjin, China
- Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, 300060, Tianjin, China
| | - Qian Sun
- Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, 300060, Tianjin, China.
- Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, 300060, Tianjin, China.
- Key Laboratory of Cancer Immunology and Biotherapy, 300060, Tianjin, China.
- Key Laboratory of Cancer Prevention and Therapy, 300060, Tianjin, China.
- Tianjin's Clinical Research Center for Cancer, 300060, Tianjin, China.
- Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, 300060, Tianjin, China.
| | - Xiubao Ren
- Department of Immunology, Tianjin Medical University Cancer Institute and Hospital, 300060, Tianjin, China.
- Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, 300060, Tianjin, China.
- Key Laboratory of Cancer Immunology and Biotherapy, 300060, Tianjin, China.
- Key Laboratory of Cancer Prevention and Therapy, 300060, Tianjin, China.
- Tianjin's Clinical Research Center for Cancer, 300060, Tianjin, China.
- Department of Biotherapy, Tianjin Medical University Cancer Institute and Hospital, 300060, Tianjin, China.
| |
Collapse
|
12
|
Zhang Z, Zhou L, Min X, Li H, Qi Q, Sun C, Sun K, Yang F, Li X. Long-term follow-up of persistent pulmonary subsolid nodules: Natural course of pure, heterogeneous, and real part-solid ground-glass nodules. Thorac Cancer 2023; 14:1059-1070. [PMID: 36922372 PMCID: PMC10125786 DOI: 10.1111/1759-7714.14845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND Previous studies have suggested the applicability of three classifications of subsolid nodules (SSNs). However, few studies have unraveled the natural history of the three types of SSNs. METHODS A retrospective study from two medical centers between November 2007 and November 2017 was conducted to explore the long-term follow-up results of three different types of SSNs, which were divided into pure ground-glass nodules (pGGNs), heterogeneous ground-glass nodules (hGGNs), and real part-solid nodules (rPSNs). RESULTS A total of 306 consecutive patients, including 361 SSNs with long-term follow-up, were reviewed. The median growth times of pGGNs, hGGNs, and rPSNs were 7.7, 6.0, and 2.0 years, respectively. For pGGNs, the median period of development into rPSNs was 4.6 years, while that of hGGNs was 1.8 years, and the time from pGGNs to hGGNs was 3.1 years (p < 0.05). In SSNs with an initial lung window consolidation tumor ratio (LW-CTR) >0.5 and mediastinum window (MW)-CTR >0.2, all cases with growth were identified within 5 years. Meanwhile, in SSNs whose LW-CTR and MW-CTR were 0, it took over 5 years to detect nodular growth. Pathologically, 90.6% of initial SSNs with LW-CTR >0 were invasive carcinomas (invasive adenocarcinoma and micro-invasive adenocarcinoma). Among patients with rPSNs in the initial state, 100.0% of the final pathological results were invasive carcinoma. Cox regression showed that age (p = 0.038), initial maximal diameter (p < 0.001), and LW-CTR (p = 0.002) were independent risk factors for SSN growth. CONCLUSIONS pGGNs, hGGNs, and rPSNs have significantly different natural histories. Age, initial nodule diameter, and LW-CTR are important risk factors for SSN growth.
Collapse
Affiliation(s)
- Zhedong Zhang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.,Thoracic Oncology Institute, Peking University People's Hospital, Beijing, China
| | - Lixin Zhou
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.,Thoracic Oncology Institute, Peking University People's Hospital, Beijing, China
| | - Xianjun Min
- Department of Thoracic Surgery, AMHT Group Aerospace 731 Hospital, Beijing, People's Republic of China
| | - Hao Li
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.,Thoracic Oncology Institute, Peking University People's Hospital, Beijing, China
| | - Qingyi Qi
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Chao Sun
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Kunkun Sun
- Department of Pathology, Peking University People's Hospital, Beijing, China
| | - Fan Yang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.,Thoracic Oncology Institute, Peking University People's Hospital, Beijing, China
| | - Xiao Li
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.,Thoracic Oncology Institute, Peking University People's Hospital, Beijing, China
| |
Collapse
|
13
|
Computed tomography radiomics in growth prediction of pulmonary ground-glass nodules. Eur J Radiol 2023; 159:110684. [PMID: 36621209 DOI: 10.1016/j.ejrad.2022.110684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 12/02/2022] [Accepted: 12/28/2022] [Indexed: 01/02/2023]
Abstract
PURPOSE Individualized follow-up of pulmonary ground-glass nodules (GGNs) remains challenging in clinical practice. Accurate prediction of the growth or long-term stability of persistent GGNs is essential to optimize the follow-up intervals. METHODS In this retrospective study, 253 patients with 1115 computed tomography (CT) images were recruited. In total, 1115 CT images were randomized into training (70%) and validation sets (30%). We developed models for the growth or long-term stable prediction of GGNs using radiomics and clinical features. We evaluated the prediction accuracy of the models using receiver operating characteristic (ROC) curve analysis, and the areas under the curve (AUCs) were established. The ROC curves of the models were compared using the DeLong method. RESULTS The growth and stable groups contained 535 and 580 GGNs, respectively. Traditional radiographic features have limited value in the prediction of growth or long-term stability of GGNs. The prediction nomogram model combining radiomics and clinical features (size, location, and age) yielded the best AUC in both the training and validation sets (AUC = 0.843 and 0.824, respectively). The radiomics model outperformed the clinical model in both sets (AUC: 0.836 vs 0.772 and 0.818 vs 0.735, respectively). The radiomics signature and nomogram model achieved similar AUCs (Delong test, training set: P = 0.09; validation set: P = 0.37). CONCLUSIONS We developed and validated a nomogram model combining radiomics signature, size, age, and location to predict the growth or long-term stability of GGNs. The model achieved good performance and may provide a basis for the improvement of follow-up management of GGNs.
Collapse
|
14
|
Xiao R, Ma Y, Li H, Li X, Sun Z, Qi Q, Yin P, Yang F, Qiu M. Lung adenocarcinoma manifesting as subsolid nodule potentially represents tumour in the equilibrium phase of immunoediting. Immunology 2023; 168:290-301. [PMID: 35503794 DOI: 10.1111/imm.13489] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 04/09/2022] [Indexed: 01/17/2023] Open
Abstract
Lung adenocarcinomas manifesting as subsolid nodules (SSN-LUADs) possess distinct dormant behaviour. This study was designed to compare the immune landscapes of normal lungs (nLungs), SSN-LUADs and LUADs manifesting as solid nodules (SN-LUADs) so as to better understand the status of anti-tumour immunity in SSN-LUADs. Mass cytometry by time-of-flight analysis was performed on 299, 570 single cells from nLung, SSN-LUAD and SN-LUAD tissues. The immune cells were identified by phenotype, and the percentages of different immune cell subclusters were compared between SSN-LUADs, SN-LUADs and nLungs. Elevated percentage of CD8+ T cells were identified in SSN-LUADs compared with in nLungs and SN-LUADs. Elevated CD56bright NK cells and decreased CD56dim NK cells were identified in both SSN-LUADs and SN-LUADs compared with in nLungs. The immune landscape of SSN-LUAD fits the theory of equilibrium phase of immunoediting, thus functional adaptive anti-tumour immunity but impaired innate anti-tumour immunity potentially contributes to the maintaining of its dormant behaviour.
Collapse
Affiliation(s)
- Rongxin Xiao
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Yi Ma
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Hao Li
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Xiao Li
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Zewen Sun
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Qingyi Qi
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Ping Yin
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Fan Yang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Mantang Qiu
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| |
Collapse
|
15
|
He Y, Xiong Z, Tian D, Zhang J, Chen J, Li Z. Natural progression of persistent pure ground-glass nodules 10 mm or smaller: long-term observation and risk factor assessment. Jpn J Radiol 2023; 41:605-616. [PMID: 36607551 DOI: 10.1007/s11604-022-01382-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/26/2022] [Indexed: 01/07/2023]
Abstract
PURPOSE Semi-automatic segmentation was used to investigate the natural progression of pure ground-glass nodules (pGGNs) of 5-10 mm in long-term follow-up and to analyze independent risk factors for subsequent growth. MATERIALS AND METHODS A total of 154 pGGNs of 5-10 mm from 132 patients with 698 follow-up CT scans were retrospectively identified. Subsequently, enrolled pGGNs were semiautomatically segmented on initial and follow-up CT to obtain diameter, density and volume, thus calculating mass, volume doubling time (VDT), and mass doubling time (MDT). Kaplan‒Meier analysis and multivariate Cox proportional risk regression were performed to explore independent predictors of pGGN growth. We analyzed growth differences among different pathological results of pGGNs confirmed by surgery. The prognosis was analyzed using the total diameter or solid size of the nodules on the last preoperative CT. RESULTS Among the 85 (55.2%) pGGNs with growth, 5.9%, 51.8%, and 80.0% showed growth within 1, 3, and 5 years, respectively. The median VDT and MDT were 1206.4 (range 349.8-5134.4) days and 1161.3 (range 339.4-6630.4) days, respectively. The multivariate Cox risk regression analysis showed that mean CT attenuation (m-CTA) [hazard ratio (HR) = 2.098, p = 0.010] and roundness index (HR = 1.892, p = 0.021) were independent risk factors for pGGN growth. In total, 67.6% of surgically resected and growing pGGNs were invasive non-mucinous adenocarcinoma (IA), including 2 cases of endpoint events, showing a PSN with solid components of 5.6 mm and a solid nodule with a diameter of 19.9 mm. CONCLUSIONS pGGNs of 5-10 mm showed an indolent clinical course. Follow-up CT imaging of pGGNs in the latter half of the first two years should be a rational management strategy. Small pGGNs with a larger overall m-CTA and roundness index on baseline CT are more likely to grow.
Collapse
Affiliation(s)
- Yifan He
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Zhongshan, Xigang District, Dalian, 116011, China
| | - Ziqi Xiong
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Zhongshan, Xigang District, Dalian, 116011, China
| | - Di Tian
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Zhongshan, Xigang District, Dalian, 116011, China
| | - Jingyu Zhang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Zhongshan, Xigang District, Dalian, 116011, China
| | - Jianzhou Chen
- Shanghai United Imaging Intelligence, Co., Ltd., Shanghai, China
| | - Zhiyong Li
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Zhongshan, Xigang District, Dalian, 116011, China.
| |
Collapse
|
16
|
Zhang Z, Yin F, Kang S, Tuo X, Zhang X, Han D. Dual-layer spectral detector CT (SDCT) can improve the detection of mixed ground-glass lung nodules. J Cancer Res Clin Oncol 2023:10.1007/s00432-022-04543-8. [PMID: 36595045 PMCID: PMC9808726 DOI: 10.1007/s00432-022-04543-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 12/16/2022] [Indexed: 01/04/2023]
Abstract
BACKGROUND Mixed ground-glass lung nodules are a high-risk factor for lung adenocarcinoma. This study aimed to analyze the value of SDCT electron density imaging in the detection of mixed ground-glass lung nodules (GGNs). METHOD 150 patients with GGNs confirmed by chest SDCT and surgical pathology were retrospectively analyzed. GGNs were screened by two senior radiologists by the double-blind method based on conventional CT and SDCT electron density images. Average CT values and electron density (ED) values of GGNs were measured for all, solid and ground-glass. RESULT Thirty pGGN cases determined by conventional CT were found to be mGGN on electron density images, including 23 in the invasive adenocarcinoma group (detection rate of 35.38%), which was significantly higher than that of the PGL group (14.89%, P < 0.05). In electron density images, average CT values and ED values in the PGL and invasive adenocarcinoma groups with pGGNs were no difference. The average CT value and ED value were significantly higher in the mGGN invasive adenocarcinoma group compared with the PGL group (P < 0.05). Meanwhile, ROC curve analysis of average CT value and ED value revealed AUC values for mGGN infiltration of 0.759 and 0.752. CONCLUSION SDCT can improve GGN visualization and increase the detection rate of mGGN compared with conventional CT. Attention should be paid to invasive adenocarcinoma for lung GGNs detected as mGGNs with high average CT value or ED value.
Collapse
Affiliation(s)
- Zhenghua Zhang
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Fang Yin
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shaolei Kang
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiaoyu Tuo
- Pathology Department, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | | | - Dan Han
- Medical Imaging Department, First Affiliated Hospital of Kunming Medical University, Kunming, China.
| |
Collapse
|
17
|
Wu L, Gao C, Kong N, Lou X, Xu M. The long-term course of subsolid nodules and predictors of interval growth on chest CT: a systematic review and meta-analysis. Eur Radiol 2023; 33:2075-2088. [PMID: 36136107 PMCID: PMC9935651 DOI: 10.1007/s00330-022-09138-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 07/26/2022] [Accepted: 09/02/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVES To calculate the pooled incidence of interval growth after long-term follow-up and identify predictors of interval growth in subsolid nodules (SSNs) on chest CT. METHODS A search of MEDLINE (PubMed), Cochrane Library, Web of Science Core Collection, and Embase was performed on November 08, 2021, for relevant studies. Patient information, CT scanner, and SSN follow-up information were extracted from each included study. A random-effects model was applied along with subgroup and meta-regression analyses. Study quality was assessed by the Newcastle-Ottawa scale, and publication bias was assessed by Egger's test. RESULTS Of the 6802 retrieved articles, 16 articles were included and analyzed, providing a total of 2898 available SSNs. The pooled incidence of growth in the 2898 SSNs was 22% (95% confidence interval [CI], 15-29%). The pooled incidence of growth in the subgroup analysis of pure ground-glass nodules was 26% (95% CI: 12-39%). The incidence of SSN growth after 2 or more years of stability was only 5% (95% CI: 3-7%). An initially large SSN size was found to be the most frequent risk factor affecting the incidence of SSN growth and the time of growth. CONCLUSIONS The pooled incidence of SSN growth was as high as 22%, with a 26% incidence reported for pure ground-glass nodules. Although the incidence of growth was only 5% after 2 or more years of stability, long-term follow-up is needed in certain cases. Moreover, the initial size of the SSN was the most frequent risk factor for growth. KEY POINTS • Based on a meta-analysis of 2898 available subsolid nodules in the literature, the pooled incidence of growth was 22% for all subsolid nodules and 26% for pure ground-glass nodules. • After 2 or more years of stability on follow-up CT, the pooled incidence of subsolid nodule growth was only 5%. • Given the incidence of subsolid nodule growth, management of these lesions with long-term follow-up is preferred.
Collapse
Affiliation(s)
- Linyu Wu
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, China
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, China
| | - Chen Gao
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, China
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, China
| | - Ning Kong
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, China
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, China
| | - Xinjing Lou
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, China
| | - Maosheng Xu
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), 54 Youdian Road, Hangzhou, China.
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, China.
| |
Collapse
|
18
|
Rong F, Shi R, Hu L, Chen R, Wang D, Lv X, Zhao Y, Huang W, Yang Y, Zhou H, Hong K. Low-dose computed tomography for lung cancer screening in Anhui, China: A randomized controlled trial. Front Oncol 2022; 12:1059999. [PMID: 36591449 PMCID: PMC9795014 DOI: 10.3389/fonc.2022.1059999] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 11/30/2022] [Indexed: 12/15/2022] Open
Abstract
Background Lung cancer is the leading cause of cancer-related death worldwide, with risk factors such as age and smoking. Low-dose computed tomography screening can reduce lung cancer mortality. However, its effectiveness in Asian populations remains unclear. Most Asian women with lung cancer are non-smokers who have not been screened. We conducted a randomized controlled trial to evaluate the performance of low-dose computed tomography screening in a Chinese population, including high-risk smokers and non-smokers exposed to passive smoking. The baseline data are reported in this study. Methods Between May and December 2019, eligible participants were randomized in a ratio of 1:1:1 to a screening (two arms) or control cohort. Non-calcified nodules/masses with a diameter >4 mm on low-dose computed tomography were considered positive findings. Results In total, 600 patients (mean age, 59.1 ± 6.9 years) underwent low-dose computed tomography. Women accounted for 31.5% (189/600) of patients; 89.9% (170/189) were non-smokers/passive smokers. At baseline, the incidence of lung cancer was 1.8% (11/600). The incidence of lung cancer was significantly lower in smokers than in female non-smokers/passive smokers (1.0% [4/415] vs. 4.1% [7/170], respectively; P=0.017). Stage 0-I lung cancer accounted for 90.9% (10/11) of cases. Conclusions We demonstrate the importance of including active smokers and female non-smokers/passive smokers in lung cancer screening programs. Further studies are needed to explore the risk factors, and long-term cost-benefit of screening Asian non-smoking women. Clinical trial registration http://chictr.org.cn/showproj.aspx?proj=39003, identifier ChiCTR1900023197.
Collapse
|
19
|
Zhang Z, Zhou L, Yang F, Li X. The natural growth history of persistent pulmonary subsolid nodules: Radiology, genetics, and clinical management. Front Oncol 2022; 12:1011712. [PMID: 36568242 PMCID: PMC9772280 DOI: 10.3389/fonc.2022.1011712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022] Open
Abstract
The high detection rate of pulmonary subsolid nodules (SSN) is an increasingly crucial clinical issue due to the increased number of screening tests and the growing popularity of low-dose computed tomography (LDCT). The persistence of SSN strongly suggests the possibility of malignancy. Guidelines have been published over the past few years and guide the optimal management of SSNs, but many remain controversial and confusing for clinicians. Therefore, in-depth research on the natural growth history of persistent pulmonary SSN can help provide evidence-based medical recommendations for nodule management. In this review, we briefly describe the differential diagnosis, growth patterns and rates, genetic characteristics, and factors that influence the growth of persistent SSN. With the advancement of radiomics and artificial intelligence (AI) technology, individualized evaluation of SSN becomes possible. These technologies together with liquid biopsy, will promote the transformation of current diagnosis and follow-up strategies and provide significant progress in the precise management of subsolid nodules in the early stage of lung cancer.
Collapse
|
20
|
Nam JG, Goo JM. Evaluation and Management of Indeterminate Pulmonary Nodules on Chest Computed Tomography in Asymptomatic Subjects: The Principles of Nodule Guidelines. Semin Respir Crit Care Med 2022; 43:851-861. [PMID: 35803268 DOI: 10.1055/s-0042-1753474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
With the rapidly increasing number of chest computed tomography (CT) examinations, the question of how to manage lung nodules found in asymptomatic patients has become increasingly important. Several nodule management guidelines have been developed that can be applied to incidentally found lung nodules (the Fleischner Society guideline), nodules found during lung cancer screening (International Early Lung Cancer Action Program protocol [I-ELCAP] and Lung CT Screening Reporting and Data System [Lung-RADS]), or both (American College of Chest Physicians guideline [ACCP], British Thoracic Society guideline [BTS], and National Comprehensive Cancer Network guideline [NCCN]). As the radiologic nodule type (solid, part-solid, and pure ground glass) and size are significant predictors of a nodule's nature, most guidelines categorize nodules in terms of these characteristics. Various methods exist for measuring the size of nodules, and the method recommended in each guideline should be followed. The diameter can be manually measured as a single maximal diameter or as an average of two-dimensional diameters, and software can be used to obtain volumetric measurements. It is important to properly evaluate and measure nodules and familiarize ourselves with the relevant guidelines to appropriately utilize medical resources and minimize unnecessary radiation exposure to patients.
Collapse
Affiliation(s)
- Ju G Nam
- Department of Radiology, Seoul National University Hospital and College of Medicine, Seoul, Republic of Korea
| | - Jin Mo Goo
- Department of Radiology, Seoul National University Hospital and College of Medicine, Seoul, Republic of Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.,Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| |
Collapse
|
21
|
Han X, Wei Z, Zhao Z, Yang X, Ye X. Cost and effectiveness of microwave ablation versus video-assisted thoracoscopic surgical resection for ground-glass nodule lung adenocarcinoma. Front Oncol 2022; 12:962630. [PMID: 36276106 PMCID: PMC9581221 DOI: 10.3389/fonc.2022.962630] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 09/12/2022] [Indexed: 11/30/2022] Open
Abstract
Purpose To retrospectively evaluate the cost and effectiveness in consecutive patients with ground-glass nodules (GGNs) treated with video-assisted thoracoscopic surgery (VATS; i.e., wedge resection or segmentectomy) or microwave ablation (MWA). Materials and methods From May 2017 to April 2019, 204 patients who met our study inclusion criteria were treated with VATS (n = 103) and MWA (n = 101). We calculated the rate of 3-year overall survival (OS), local progression-free survival (LPFS), and cancer−specific survival (CSS), as well as the cost during hospitalization and the length of hospital stay. Results The rates of 3-year OS, LPFS, and CSS were 100%, 98.9%, and 100%, respectively, in the VATS group and 100%, 100% (p = 0.423), and 100%, respectively, in the MWA group. The median cost of VATS vs. MWA was RMB 54,314.36 vs. RMB 21,464.98 (p < 0.001). The length of hospital stay in the VATS vs. MWA group was 10.0 vs. 6.0 d (p < 0.001). Conclusions MWA had similar rates of 3-year OS, LPFS, and CSS for patients with GGNs and a dramatically lower cost and shorter hospital stay compared with VATS. Based on efficacy and cost, MWA provides an alternative treatment option for patients with GGNs.
Collapse
Affiliation(s)
- Xiaoying Han
- Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Zhigang Wei
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, China
- Cheeloo College of Medicine, Shandong University, Jinan, China
| | | | - Xia Yang
- Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- *Correspondence: Xia Yang, ; ; Xin Ye,
| | - Xin Ye
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, China
- *Correspondence: Xia Yang, ; ; Xin Ye,
| |
Collapse
|
22
|
Qu R, Tu D, Cai Y, Ping W, Fu X. Clinical features and surgical outcomes of young patients with lung adenocarcinoma manifesting as ground glass opacity. Front Oncol 2022; 12:979522. [PMID: 36185186 PMCID: PMC9515497 DOI: 10.3389/fonc.2022.979522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 08/22/2022] [Indexed: 12/04/2022] Open
Abstract
Background More and more ground glass opacity associated lung adenocarcinoma (GGO-LUAD) have been diagnosed in young patients nowadays. Our study aims to investigate the clinical features and surgical outcomes of young patients with GGO-LUAD. Methods Patients aged ≤ 40 years who were diagnosed as lung adenocarcinoma and who underwent video assisted thoracoscopic surgery (VATS) were retrospectively reviewed from January 2017 to December 2018. According to radiological appearance of the patient’s lesions, they were divided into a solid nodule (SN) group and GGO group. The pathological subtypes, surgical procedures and nodules size were analyzed, and the clinical features and prognosis were evaluated between these patients. Results A total of 165 patients were included, of which 133 were in the GGO group and 32 in the SN group. Both the GGO group and the SN group had a higher proportion of females and non-smokers. Compared with patients (15.63%) in the SN group, there are more patients (27.8%) under the age of 30 in the GGO group. Pathological findings showed 83.5% of lesions were pre-invasive lesions in the GGO group, although 16.5% of lesions were invasive adenocarcinoma, whereas in the SN group, 96.9% were invasive adenocarcinoma. The GGO group had significantly better histological characteristics and prognosis than the SN group. Perioperative complications occurred in only 6 patients, including pneumonia in one patient, pneumothorax in two patients, and prolonged air leak in three patients. No other serious complications or deaths occurred. After a median follow-up time of 41.2 ± 7.2 months (32-56), the 3-year recurrence free survival (RFS) (100%) and overall survival (OS) (100%) of the GGO group were significantly higher than those (93.42% and 96.88%) in the SN group. Conclusions Young patients with GGO-LUAD are mainly non-smokers and female. Most of these patients were early-stage with good prognosis after surgery.
Collapse
Affiliation(s)
- Rirong Qu
- Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dehao Tu
- Department of Thoracic Surgery, Yueyang Central Hospital, Yueyang, China
| | - Yixin Cai
- Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Ping
- Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Wei Ping, ; Xiangning Fu,
| | - Xiangning Fu
- Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Wei Ping, ; Xiangning Fu,
| |
Collapse
|
23
|
Manley CJ, Pritchett MA. Nodules, Navigation, Robotic Bronchoscopy, and Real-Time Imaging. Semin Respir Crit Care Med 2022; 43:473-479. [PMID: 36104024 DOI: 10.1055/s-0042-1747930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
The process of detection, diagnosis, and management of lung nodules is complex due to the heterogeneity of lung pathology and a relatively low malignancy rate. Technological advances in bronchoscopy have led to less-invasive diagnostic procedures and advances in imaging technology have helped to improve nodule localization and biopsy confirmation. Future research is required to determine which modality or combination of complimentary modalities is best suited for safe, accurate, and cost-effective management of lung nodules.
Collapse
Affiliation(s)
- Christopher J Manley
- Division of Pulmonary and Critical Care, Fox Chase Cancer Center, Temple University Health System, Philadelphia, Pennsylvania
| | - Michael A Pritchett
- Division of Pulmonary and Critical Care Medicine, Chest Center of the Carolinas at FirstHealth, FirstHealth of the Carolinas and Pinehurst Medical Clinic, Pinehurst, North Carolina
| |
Collapse
|
24
|
Liang X, Liu M, Li M, Zhang L. Clinical and CT Features of Subsolid Pulmonary Nodules With Interval Growth: A Systematic Review and Meta-Analysis. Front Oncol 2022; 12:929174. [PMID: 35860567 PMCID: PMC9289285 DOI: 10.3389/fonc.2022.929174] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundEstablishing risk-based follow-up management strategies is crucial to the surveillance of subsolid pulmonary nodules (SSNs). However, the risk factors for SSN growth are not currently clear. This study aimed to perform a systematic review and meta-analysis to identify clinical and CT features correlated with SSN growth.MethodsRelevant studies were retrieved from Web of Science, PubMed, Cochrane Library, and EMBASE. The correlations of clinical and CT features with SSN growth were pooled using a random-effects model or fixed-effects model depending on heterogeneity, which was examined by the Q test and I2 test. Pooled odds ratio (OR) or pooled standardized mean differences (SMD) based on univariate analyses were calculated to assess the correlation of clinical and CT features with SSN growth. Pooled ORs based on multivariate analyses were calculated to find out independent risk factors to SSN growth. Subgroup meta-analysis was performed based on nodule consistency (pure ground-glass nodule (pGGN) and part-solid nodule (PSN). Publication bias was examined using funnel plots.ResultsNineteen original studies were included, consisting of 2444 patients and 3012 SSNs. The median/mean follow-up duration of these studies ranged from 24.2 months to 112 months. Significant correlations were observed between SSN growth and eighteen features. Male sex, history of lung cancer, nodule size > 10 mm, nodule consistency, and age > 65 years were identified as independent risk factors for SSN growth based on multivariate analyses results. Eight features, including male sex, smoking history, nodule size > 10 mm, larger nodule size, air bronchogram, higher mean CT attenuation, well-defined border, and lobulated margin were detected to be significantly correlated with pGGNs growth. Smoking history showed no significant correlation with pGGN growth based on the multivariate analysis results.ConclusionsEighteen clinical and CT features were identified to be correlated with SSN growth, among which male sex, history of lung cancer, nodule size > 10 mm, nodule consistency and age > 65 years were independent risk factors while history of lung cancer was not correlated with pGGN growth. These factors should be considered when making risk-based follow-up plans for SSN patients.
Collapse
|
25
|
Fan Y, Zhou Y, Lou M, Gao Z, Li X, Yuan K. SLC6A8 is a Potential Biomarker for Poor Prognosis in Lung Adenocarcinoma. Front Genet 2022; 13:845373. [PMID: 35692837 PMCID: PMC9185669 DOI: 10.3389/fgene.2022.845373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Recent studies have demonstrated that creatine can promote tumor metastasis and has implications for immune cell function. SLC6A8 encodes a membrane protein that can transport creatine inside and outside the cell. However, there are currently no studies of SLC6A8 in lung adenocarcinoma (LUAD).Methods: In this study, the expression of SLC6A8 in LUAD was analyzed using the Oncomine database, the Cancer Genome Atlas (TCGA) database, and immunohistochemical staining analysis. Survival analysis of patients with LUAD was performed using the cBioPortal and the Kaplan-Meier Plotter websites and clinical follow-up data. An analysis of the association between SLC6A8 and the tumor immune microenvironment (TIME) of LUAD was performed through the TISIDB database and estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) algorithm. Then, based on the curated list of SLC6A8-related immunomodulators, three genes (NT5E, CD40LG, CD80) were selected to construct SLC6A8-related immune signatures to further evaluate the immune aspect of LUAD prognosis.Results: Our studies indicated that SLC6A8 was overexpressed in LUAD, and the high expression of SLC6A8 was associated with poor survival. Genetic alteration of SLC6A8 was also associated with a poorer prognosis. Furthermore, multivariate Cox analysis indicated that SLC6A8 could be used as an independent risk prognostic factor. Then, immune infiltration analysis indicated that SLC6A8 was also strongly associated with poor prognosis in the TIME of LUAD. A multivariate Cox proportional hazard model was then constructed, and was shown effective at identifying high-risk patients. Univariate and multivariate Cox analysis showed that the risk scoring of the model was an independent prognostic risk factor in LUAD.Conclusion:SLC6A8 may serve as a biomarker for poor prognosis in LUAD.
Collapse
Affiliation(s)
- Yongfei Fan
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Yong Zhou
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Ming Lou
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Zhaojia Gao
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- Heart and Lung Disease Laboratory, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Xinwei Li
- Department of Gastroenterology, Affiliated Cancer Hospital of Bengbu Medical College, Bengbu, China
| | - Kai Yuan
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- Heart and Lung Disease Laboratory, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- *Correspondence: Kai Yuan,
| |
Collapse
|
26
|
Xie S, Li S, Deng H, Han Y, Liu G, Liu Q. Application Value of PET/CT and MRI in the Diagnosis and Treatment of Patients With Synchronous Multiple Pulmonary Ground-Glass Nodules. Front Oncol 2022; 12:797823. [PMID: 35280735 PMCID: PMC8905144 DOI: 10.3389/fonc.2022.797823] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 01/21/2022] [Indexed: 11/29/2022] Open
Abstract
Background Synchronous multiple ground-glass nodules (SMGGNs) in synchronous multiple lung cancers are associated with specific imaging findings. It is difficult to distinguish whether multiple nodules are primary tumors or metastatic lesions in the lungs. The need for PET/CT and contrast-enhanced brain MRI for these patients remains unclear. This study investigated the necessity of these two imaging examinations for SMGGN patients by means of retrospective analysis. Methods SMGGN patients who were diagnosed and treated in our hospital from October 2017 to May 2020 and underwent whole-body PET/CT(Cranial excepted) and/or contrast-enhanced brain MRI+DWI were enrolled in this study. We analyzed the imaging and clinical characteristics of these patients to evaluate SMGGN patients’ need to undergo whole-body PET/CT and brain MRI examination. Results A total of 87 SMGGN patients were enrolled. 51 patients underwent whole-body PET/CT examinations and did not show signs of primary tumors in other organs, metastatic foci in other organs, or metastasis to surrounding lymph nodes. 87 patients underwent whole-brain MRI, which did not reveal brain metastases but did detect an old cerebral infarction in 23 patients and a new cerebral infarction in one patient. 87 patients underwent surgical treatment in which 219 nodules were removed. All nodules were diagnosed as adenocarcinoma or atypical adenomatous hyperplasia. No lymph node metastasis was noted. Conclusion For SMGGN patients, PET/CT and enhanced cranial MRI are unnecessary for SMGGNs patients, but from the perspective of perioperative patient safety, preoperative MRI+DWI examination is recommended for SMGGNs patients.
Collapse
Affiliation(s)
- Shaonan Xie
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Shaoteng Li
- Department of Diagnostic Radiology, The People's Hospital of Xingtai, Xingtai, China
| | - Huiyan Deng
- Department of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yaqing Han
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Guangjie Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Qingyi Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| |
Collapse
|
27
|
Qiu Z, Wu Q, Wang S, Chen Z, Lin F, Zhou Y, Jin J, Xian J, Tian J, Li W. Development of a deep learning-based method to diagnose pulmonary ground-glass nodules by sequential computed tomography imaging. Thorac Cancer 2022; 13:602-612. [PMID: 34994091 PMCID: PMC8841714 DOI: 10.1111/1759-7714.14305] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/17/2021] [Accepted: 12/20/2021] [Indexed: 02/05/2023] Open
Abstract
Background Early identification of the malignant propensity of pulmonary ground‐glass nodules (GGNs) can relieve the pressure from tracking lesions and personalized treatment adaptation. The purpose of this study was to develop a deep learning‐based method using sequential computed tomography (CT) imaging for diagnosing pulmonary GGNs. Methods This diagnostic study retrospectively enrolled 762 patients with GGNs from West China Hospital of Sichuan University between July 2009 and March 2019. All patients underwent surgical resection and at least two consecutive time‐point CT scans. We developed a deep learning‐based method to identify GGNs using sequential CT imaging on a training set consisting of 1524 CT sections from 508 patients and then evaluated 256 patients in the testing set. Afterwards, an observer study was conducted to compare the diagnostic performance between the deep learning model and two trained radiologists in the testing set. We further performed stratified analysis to further relieve the impact of histological types, nodule size, time interval between two CTs, and the component of GGNs. Receiver operating characteristic (ROC) analysis was used to assess the performance of all models. Results The deep learning model that used integrated DL‐features from initial and follow‐up CT images yielded the best diagnostic performance, with an area under the curve of 0.841. The observer study showed that the accuracies for the deep learning model, junior radiologist, and senior radiologist were 77.17%, 66.89%, and 77.03%, respectively. Stratified analyses showed that the deep learning model and radiologists exhibited higher performance in the subgroup of nodule sizes larger than 10 mm. With a longer time interval between two CTs, the deep learning model yielded higher diagnostic accuracy, but no general rules were yielded for radiologists. Different densities of components did not affect the performance of the deep learning model. In contrast, the radiologists were affected by the nodule component. Conclusions Deep learning can achieve diagnostic performance on par with or better than radiologists in identifying pulmonary GGNs.
Collapse
Affiliation(s)
- Zhixin Qiu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Qingxia Wu
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Shuo Wang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Zhixia Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Feng Lin
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yuyan Zhou
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Jin
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Jinghong Xian
- Department of Clinical Research, West China Hospital, Sichuan University, Chengdu, China
| | - Jie Tian
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| |
Collapse
|
28
|
Wang SX, Kim S, Marshall MB. Commentary: Practicing the philosophy of continuous improvement with virtual-assisted lung mapping 2.0. J Thorac Cardiovasc Surg 2021; 164:252-253. [PMID: 34815093 DOI: 10.1016/j.jtcvs.2021.10.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 10/22/2021] [Accepted: 10/22/2021] [Indexed: 11/19/2022]
Affiliation(s)
- Sue X Wang
- Division of Thoracic Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, Mass.
| | - SangMin Kim
- Division of Thoracic Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, Mass
| | - M Blair Marshall
- Division of Thoracic Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, Mass
| |
Collapse
|
29
|
Hu F, Huang H, Jiang Y, Feng M, Wang H, Tang M, Zhou Y, Tan X, Liu Y, Xu C, Ding N, Bai C, Hu J, Yang D, Zhang Y. Discriminating invasive adenocarcinoma among lung pure ground-glass nodules: a multi-parameter prediction model. J Thorac Dis 2021; 13:5383-5394. [PMID: 34659805 PMCID: PMC8482342 DOI: 10.21037/jtd-21-786] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 08/06/2021] [Indexed: 11/07/2022]
Abstract
Background Patients with consistent lung pure ground-glass nodules (pGGNs) have a high incidence of lung adenocarcinoma that can be classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). Regular follow-up is recommended for AIS and MIA, while surgical resection should be considered for IAC. This study sought to develop a multi-parameter prediction model to increase the diagnostic accuracy in discriminating between IAC and AIS or MIA. Methods The training data set comprised consecutive patients with lung pGGNs who underwent resection from January to December 2017 at the Zhongshan Hospital. Of the 370 resected pGGNs, 344 were pathologically confirmed to be AIS, MIA, or IAC and were included in the study. The 26 benign pGGNs were excluded. We compared differences in the clinical features (e.g., age and gender), the content of serum tumor biomarkers, the computed tomography (CT) parameters (e.g., nodule size and the maximal CT value), and the morphologic characteristics of nodules (e.g., lobulation, spiculation, pleura indentation, vacuole sign, and normal vessel penetration or abnormal vessel) between the pathological subtypes of AIS, MIA, and IAC. An abnormal vessel was defined as “vessel curve” or “vessel enlargement”. Statistical analyses were performed using the chi-square test, analysis of variance (ANOVA), and rank test. The IAC prediction model was constructed via a multivariate logistical regression. Our prediction model for lung pGGNs was further validated in a data set comprising consecutive patients from multiple medical centers in China from July to December 2018. In total, 345 resected pGGNs were pathologically diagnosed as lung adenocarcinoma in the validation data set. Results In the training data set, patients with pGGNs ≥10 mm in size had a high incidence (74.5%) of IAC. The maximal CT value of IAC [–416.1±121.2 Hounsfield unit (HU)] was much higher than that of MIA (–507.7±138.0 HU) and AIS (–602.6±93.3 HU) (P<0.001). IAC was more common in pGGNs that displayed any of the following CT manifestations: lobulation, spiculation, pleura indentation, vacuole sign, and vessel abnormality. The IAC prediction model was constructed using the parameters that were assessed as risk factors (i.e., the nodule size, maximal CT value, and CT signs). The receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of this model for diagnosing IAC was 0.910, which was higher than that of the AUC for nodule size alone (0.891) or the AUC for the maximal CT value alone (0.807) (P<0.05, respectively). A multicenter validation data set was used to validate the performance of our prediction model in diagnosing IAC, and our model was found to have an AUC of 0.883, which was higher than that of the AUC of 0.827 for the module size alone model or the AUC of 0.791 for the maximal CT value alone model (P<0.05, respectively). Conclusions Our multi-parameter prediction model was more accurate at diagnosing IAC than models that used only nodule size or the maximal CT value alone. Thus, it is an efficient tool for identifying the IAC of malignant pGGNs and deciding if surgery is needed.
Collapse
Affiliation(s)
- Fuying Hu
- Department of Pulmonary and Critical Care Medicine, The First People's Hospital, Tianmen, China.,Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Haihua Huang
- Department of Thoracic Surgery, Shanghai General Hospital, Jiaotong University, Shanghai, China
| | - Yunyan Jiang
- Department of Pulmonary and Critical Care Medicine, People's Hospital, Yuxi, China
| | - Minxiang Feng
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Wang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Min Tang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yi Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xianhua Tan
- Department of Radiology, The Fifth Hospital of Wuhan, Wuhan, China
| | - Yalan Liu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chen Xu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ning Ding
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chunxue Bai
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jie Hu
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Dawei Yang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yong Zhang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| |
Collapse
|
30
|
Kim YW, Kwon BS, Lim SY, Lee YJ, Park JS, Cho YJ, Yoon HI, Lee KW, Lee JH, Chung JH, Ji E, Lee CT. Lung cancer probability and clinical outcomes of baseline and new subsolid nodules detected on low-dose CT screening. Thorax 2021; 76:980-988. [PMID: 33859050 PMCID: PMC8461405 DOI: 10.1136/thoraxjnl-2020-215107] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 01/25/2021] [Accepted: 01/26/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Limited data are available regarding the management of subsolid nodules detected on lung cancer screening with low-dose CT (LDCT). We aimed to determine the characteristics of screen-detected subsolid nodules, and to evaluate the probability of lung cancer and the clinical course of subsolid nodules detected at baseline and during follow-up screening. METHODS We evaluated 50 132 asymptomatic adults (22 631 never-smokers and 27 501 ever-smokers) who underwent LDCT screening for lung cancer between May 2003 and June 2019 at a tertiary centre in South Korea. The incidence, characteristics and clinical outcomes of the baseline and new screen-detected subsolid nodules were determined. RESULTS A total of 6725 subsolid nodules (5116 pure ground glass opacity nodules and 1609 part-solid nodules) were detected in 4545 participants (1484 new subsolid nodules detected in 937 (1.9%) participants; the overall incidence of subsolid nodules: 10.7% in never-smokers and 7.7% in ever-smokers, p<0.001). Among 4918 subsolid nodules that underwent follow-up with CT scans (the mean number of CT scans, including the baseline LDCT scan: 4.6), 2116 nodules (30.0% of baseline subsolid nodules and 78.9% of new subsolid nodules) resolved spontaneously. Among 293 biopsied subsolid nodules, 227 (77.5%) nodules were diagnosed as lung cancer, of which 226 (99.6%) were adenocarcinomas. No significant difference was observed in pathological invasiveness or the initial stage between the baseline and new cancerous subsolid nodules. Multivariable analyses revealed that new detection at follow-up screening was significantly associated with a lower probability of lung cancer (OR 0.26, 95% CI 0.14 to 0.49) and overall growth (OR 0.39, 95% CI 0.26 to 0.59), but with a higher probability of resolution (OR 6.30, 95% CI 5.09 to 7.81). CONCLUSIONS LDCT screening led to a considerably high rate of subsolid nodule detection, particularly in never-smokers. Compared with the baseline subsolid nodules, the new subsolid nodules were associated with a lower probability of lung cancer and higher probability of spontaneous resolution, indicating their more inflammatory nature. Less aggressive follow-up may be allowed for new subsolid nodules, particularly in screening programmes for Asian populations.
Collapse
Affiliation(s)
- Yeon Wook Kim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Byoung Soo Kwon
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Sung Yoon Lim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Yeon Joo Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Jong Sun Park
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Young-Jae Cho
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Ho Il Yoon
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Kyung Won Lee
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Jae Ho Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Jin-Haeng Chung
- Department of Pathology and Translational Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Eunjeong Ji
- Medical Research Collaborating Center, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Choon-Taek Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| |
Collapse
|
31
|
Wen Z, Zhang Y, Fu F, Ma Z, Deng C, Ma X, Hu H, Sun Y, Chen H. Clinical, pathological and radiologic features of minute pulmonary meningothelial-like nodules. J Cancer Res Clin Oncol 2021; 148:1473-1479. [PMID: 34287680 DOI: 10.1007/s00432-021-03744-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 07/14/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVES Reports about the radiologic features of minute pulmonary meningothelial-like nodules are sparse. This study aims to investigate the radiologic features of minute pulmonary meningothelial-like nodules. METHOD From January 2016 to April 2019, 7589 patients underwent pulmonary resections at Fudan University Shanghai Cancer Center. Postoperative pathology records were reviewed retrospectively. Fifty-nine patients with minute pulmonary meningothelial-like nodule were included. The identification of minute pulmonary meningothelial-like nodules in pathology specimen included pathologically confirmed in resected nodules, and discovery in the peripheral tissue of other resected nodules incidentally. We went back and checked all the pre-operative scans of patients to analyze surgical decision and observe any change of visible minute pulmonary meningothelial-like nodule over time. Clinic, radiologic and pathological features were collected. RESULT Fifty-nine patients included 10 men and 49 women, with a mean age of 57.7. Five patients had history, while 54 patients were non-smokers. 79 min pulmonary meningothelial-like nodules was found. Of them, 36 nodules were not visible on computed tomography scan. 43 nodules were visible on computed tomography scan, with an average size of 5.3 mm in 29 patients. Computed tomography appearance included pure ground-glass opacity in 36, mixed in 2, and solid nodules in 5. Nearly half of patients had a pre-operative follow-up more than 6 months (13/29, 44.8%). The median pre-operative radiologic follow-up was 4.9 months. Approximately 90% of patients underwent pulmonary surgery because of other malignant nodule on chest computed tomography scan (52/59, 88.1%). CONCLUSION Most minute pulmonary meningothelial-like nodules tend to present as ground-glass opacity, especially pure ground-glass opacity. Continuous computed tomography monitoring revealed no radiologic change over time. Continuous computed tomography monitoring was necessary part of management of minute pulmonary meningothelial-like nodule.
Collapse
Affiliation(s)
- Zhexu Wen
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Yang Zhang
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Fangqiu Fu
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Zelin Ma
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Chaoqiang Deng
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Xiangyi Ma
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Hong Hu
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Yihua Sun
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China
| | - Haiquan Chen
- Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, 270 Dong-An Rd, Shanghai, 200032, China.
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 20032, China.
- State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 20032, China.
| |
Collapse
|
32
|
Yoshida Y, Yanagawa M, Hata A, Sato Y, Tsubamoto M, Doi S, Yamagata K, Miyata T, Kikuchi N, Tomiyama N. Quantitative volumetry of ground-glass nodules on high-spatial-resolution CT with 0.25-mm section thickness and 1024 matrix: Phantom and clinical studies. Eur J Radiol Open 2021; 8:100362. [PMID: 34141831 PMCID: PMC8184508 DOI: 10.1016/j.ejro.2021.100362] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 05/26/2021] [Accepted: 05/29/2021] [Indexed: 11/25/2022] Open
Abstract
High-spatial-resolution CT provided more accurate volume of a −800-HU nodule in a phantom than conventional settings. The maximum CT attenuation values were significantly higher in high-resolution setting than conventional setting. The high-resolution setting might allow earlier detection of solid components in GGNs during follow-up.
Objectives To compare high-resolution (HR) and conventional (C) settings of high-spatial-resolution computed tomography (CT) for software volumetry of ground-glass nodules (GGNs) in phantoms and patients. Methods We placed −800 and −630 HU spherical GGN-mimic nodules in 28 different positions in phantoms and scanned them individually. Additionally, 60 GGNs in 45 patients were assessed retrospectively. Images were reconstructed using the HR-setting (matrix size, 1024; slice thickness, 0.25 mm) and C-setting (matrix size, 512; slice thickness, 0.5 mm). We measured the GGN volume and mass using software. In the phantom study, the absolute percentage error (APE) was calculated as the absolute difference between Vernier caliper measurement-based and software-based volumes. In patients, we measured the density (mean, maximum, and minimum) and classified GGNs into low- and high-attenuation GGNs. Results In images of the −800 HU, but not −630 HU, phantom nodules, the volumes and masses differed significantly between the two settings (both p < 0.01). The APE was significantly lower in the HR-setting than in the C-setting (p < 0.01). In patients, volumes did not differ significantly between settings (p = 0.59). Although the mean attenuation was not significantly different, the maximum and minimum values were significantly increased and decreased, respectively, in the HR-setting (both p < 0.01). The volumes of both low-attenuation and high-attenuation GGNs were not significantly different between settings (p = 0.78 and 0.39, respectively). Conclusion The HR-setting might yield a more accurate volume for phantom GGN of −800 HU and influence the detection of maximum and minimum CT attenuation.
Collapse
Affiliation(s)
- Yuriko Yoshida
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Masahiro Yanagawa
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Akinori Hata
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Yukihisa Sato
- Department of Diagnostic Radiology, Suita Municipal Hospital, 5-7 Kishibeshinmachi Suita, Osaka 564-8567, Japan
| | - Mitsuko Tsubamoto
- Department of Diagnositic Radiology, Nishinomiya Municipal Central Hospital, 8-24 Hayashidacho, Nishinomiya, Hyogo, 663-8014, Japan
| | - Shuhei Doi
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Kazuki Yamagata
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Tomo Miyata
- Department of Future Diagnostic Radiology, Osaka University Graduate School of Medicine 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Noriko Kikuchi
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| | - Noriyuki Tomiyama
- Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka Suita, Osaksa 565-0871, Japan
| |
Collapse
|
33
|
Mak KL, Hsin M. Commentary: Is size everything in the management of ground-glass opacities? J Thorac Cardiovasc Surg 2021; 162:461-462. [PMID: 34088497 DOI: 10.1016/j.jtcvs.2021.05.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 04/30/2021] [Accepted: 05/12/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Ka-Lun Mak
- Department of Cardiothoracic Surgery, Queen Mary Hospital, Hong Kong, China
| | - Michael Hsin
- Department of Cardiothoracic Surgery, Queen Mary Hospital, Hong Kong, China.
| |
Collapse
|
34
|
Chen J, Mehta V, Chowdhary V, Chaya N, Lowry JW. Outcome of PET-Negative Solid Pulmonary Nodules: A Retrospective Study. Acad Radiol 2021; 28:628-633. [PMID: 32303444 DOI: 10.1016/j.acra.2020.03.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/25/2020] [Accepted: 03/08/2020] [Indexed: 12/20/2022]
Abstract
OBJECTIVE It was observed that malignancy had been found on follow-up in patients with PET-negative solid solitary pulmonary nodules (SPN). A retrospective analysis was performed to observe the natural history and malignant potential of these lesions, which, in routine practice, are presumed to be inactive. MATERIALS AND METHODS Patients with an incidentally-discovered solid solitary pulmonary nodule who then had a negative follow-up PET/CT from 2005 to 2015 were identified using a text-based search methodology. These patients' charts were mined to determine the rate of development of subsequent malignancy from these index nodules. RESULTS Of the patients with initially PET-negative solitary pulmonary nodule (n = 62, 43.5% women, mean age 65), 44 had clinical follow-up of the index lesion. 8 (7 pathology-proven) subsequent malignancies were identified with a mean time to diagnosis of 37.6 (±31.3) months. There were no statistically significant predictors of subsequent development of cancer (including age, gender, and smoking status). CONCLUSION Upon follow up, 18.2% of the initially queried solid PET-negative nodules developed subsequent malignancy at an average time of 37.6 months, suggesting the continued need for follow-up of these initially PET-negative nodules beyond the 2 years currently suggested in popular guidelines. Importantly, these findings also remind radiologists that a negative PET/CT is not a surrogate for tissue diagnosis in the case of non-FDG avid SPN.
Collapse
|
35
|
Ye X, Fan W, Wang Z, Wang J, Wang H, Wang J, Wang C, Niu L, Fang Y, Gu S, Tian H, Liu B, Zhong L, Zhuang Y, Chi J, Sun X, Yang N, Wei Z, Li X, Li X, Li Y, Li C, Li Y, Yang X, Yang W, Yang P, Yang Z, Xiao Y, Song X, Zhang K, Chen S, Chen W, Lin Z, Lin D, Meng Z, Zhao X, Hu K, Liu C, Liu C, Gu C, Xu D, Huang Y, Huang G, Peng Z, Dong L, Jiang L, Han Y, Zeng Q, Jin Y, Lei G, Zhai B, Li H, Pan J. [Expert Consensus for Thermal Ablation of Pulmonary Subsolid Nodules (2021 Edition)]. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2021; 24:305-322. [PMID: 33896152 PMCID: PMC8174112 DOI: 10.3779/j.issn.1009-3419.2021.101.14] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
局部热消融技术在肺部结节治疗领域正处在起步与发展阶段,为了肺结节热消融治疗的临床实践和规范发展,由“中国医师协会肿瘤消融治疗技术专家组”“中国医师协会介入医师分会肿瘤消融专业委员会”“中国抗癌协会肿瘤消融治疗专业委员会”“中国临床肿瘤学会消融专家委员会”组织多学科国内有关专家,讨论制定了“热消融治疗肺部亚实性结节专家共识(2021年版)”。主要内容包括:①肺部亚实性结节的临床评估;②热消融治疗肺部亚实性结节技术操作规程、适应证、禁忌证、疗效评价和相关并发症;③存在的问题和未来发展方向。
Collapse
Affiliation(s)
- Xin Ye
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Weijun Fan
- Department of Minimally Invasive Interventional Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510050, China
| | - Zhongmin Wang
- Department of Interventional Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China
| | - Junjie Wang
- Department of Radiation Oncology, Peking University Third Hospital, Beijing 100191, China
| | - Hui Wang
- Interventional Center, Jilin Provincial Cancer Hospital, Changchun 170412, China
| | - Jun Wang
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Chuntang Wang
- Department of Thoracic Surgery, Dezhou Second People's Hospital, Dezhou 253022, China
| | - Lizhi Niu
- Department of Oncology, Affiliated Fuda Cancer Hospital, Jinan University, Guangzhou 510665, China
| | - Yong Fang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China
| | - Shanzhi Gu
- Department of Interventional Radiology, Hunan Cancer Hospital, Changsha 410013, China
| | - Hui Tian
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Baodong Liu
- Department of Thoracic Surgery, Xuan Wu Hospital Affiliated to Capital Medical University, Beijing 100053, China
| | - Lou Zhong
- Thoracic Surgery Department, Affiliated Hospital of Nantong University, Nantong 226001, China
| | - Yiping Zhuang
- Department of Interventional Therapy, Jiangsu Cancer Hospital, Nanjing 210009, China
| | - Jiachang Chi
- Department of Interventional Oncology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
| | - Xichao Sun
- Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Nuo Yang
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Zhigang Wei
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Xiao Li
- Department of Interventional Therapy, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiaoguang Li
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, Beijing 100730, China
| | - Yuliang Li
- Department of Interventional Medicine, The Second Hospital of Shandong University, Jinan 250033, China
| | - Chunhai Li
- Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Yan Li
- Department of Oncology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Lung Cancer Institute, Jinan 250014, China
| | - Xia Yang
- Department of Oncology, Shandong Provincial Hospital Afliated to Shandong First Medical University, Jinan 250101, China
| | - Wuwei Yang
- Department of Oncology, The Fifth Medical Center, Chinese PLA General Hospital, Beijing 100071, China
| | - Po Yang
- Interventionael & Vascular Surgery, The Fourth Hospital of Harbin Medical University, Harbin 150001, China
| | - Zhengqiang Yang
- Department of Interventional Therapy, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yueyong Xiao
- Department of Radiology, Chinese PLA Gneral Hospital, Beijing 100036, China
| | - Xiaoming Song
- Department of Thoracic Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Kaixian Zhang
- Department of Oncology, Tengzhou Central People's Hospital, Tengzhou 277500, China
| | - Shilin Chen
- Department of Thoracic Surgery, Jiangsu Cancer Hospital, Nanjing 210009, China
| | - Weisheng Chen
- Department of Thoracic Surgery, Fujian Medical University Cancer Hospital, Fujian 350011, China
| | - Zhengyu Lin
- Department of Intervention, The First Affiliated Hospital of Fujian Medical University, Fujian 350005, China
| | - Dianjie Lin
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Zhiqiang Meng
- Minimally Invasive Therapy Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Xiaojing Zhao
- Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
| | - Kaiwen Hu
- Department of Oncology, Dongfang Hospital Affiliated to Beijing University of Chinese Medicine, Beijing 100078, China
| | - Chen Liu
- Department of Interventional Therapy, Beijing Cancer Hospital, Beijing 100161, China
| | - Cheng Liu
- Department of Radiology, Shandong Medical Imaging Research Institute, Jinan 250021, China
| | - Chundong Gu
- Department of Thoracic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| | - Dong Xu
- Department of Diagnostic Ultrasound Imaging & Interventional Therapy, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China
| | - Yong Huang
- Department of Imaging, Affiliated Cancer Hospital of Shandong First Medical University, Jinan 250117, China
| | - Guanghui Huang
- Department of Oncology, Shandong Provincial Hospital Afliated to Shandong First Medical University, Jinan 250101, China
| | - Zhongmin Peng
- Department of Thoracic Surgery , Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Liang Dong
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Lei Jiang
- Department of Radiology, The Convalescent Hospital of East China, Wuxi 214063, China
| | - Yue Han
- Department of Interventional Therapy, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Qingshi Zeng
- Department of Medical Imaging, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Yong Jin
- Interventionnal Therapy Department, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China
| | - Guangyan Lei
- Department of Thoracic Surgery, Shanxi Provincial Cancer Hospital, Xi'an 710061, China
| | - Bo Zhai
- Department of Interventional Oncology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
| | - Hailiang Li
- Department of Interventional Radiology, Henan Cancer Hospital, Zhengzhou 450003, China
| | - Jie Pan
- Department of Radiology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | | | | | | | | |
Collapse
|
36
|
Jiang B, Zhang Y, Zhang L, H de Bock G, Vliegenthart R, Xie X. Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks. Eur Radiol 2021; 31:7303-7315. [PMID: 33847813 DOI: 10.1007/s00330-021-07901-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 02/03/2021] [Accepted: 03/16/2021] [Indexed: 12/17/2022]
Abstract
OBJECTIVES The interpretability of convolutional neural networks (CNNs) for classifying subsolid nodules (SSNs) is insufficient for clinicians. Our purpose was to develop CNN models to classify SSNs on CT images and to investigate image features associated with the CNN classification. METHODS CT images containing SSNs with a diameter of ≤ 3 cm were retrospectively collected. We trained and validated CNNs by a 5-fold cross-validation method for classifying SSNs into three categories (benign and preinvasive lesions [PL], minimally invasive adenocarcinoma [MIA], and invasive adenocarcinoma [IA]) that were histologically confirmed or followed up for 6.4 years. The mechanism of CNNs on human-recognizable CT image features was investigated and visualized by gradient-weighted class activation map (Grad-CAM), separated activation channels and areas, and DeepDream algorithm. RESULTS The accuracy was 93% for classifying 586 SSNs from 569 patients into three categories (346 benign and PL, 144 MIA, and 96 IA in 5-fold cross-validation). The Grad-CAM successfully located the entire region of image features that determined the final classification. Activated areas in the benign and PL group were primarily smooth margins (p < 0.001) and ground-glass components (p = 0.033), whereas in the IA group, the activated areas were mainly part-solid (p < 0.001) and solid components (p < 0.001), lobulated shapes (p < 0.001), and air bronchograms (p < 0.001). However, the activated areas for MIA were variable. The DeepDream algorithm showed the image features in a human-recognizable pattern that the CNN learned from a training dataset. CONCLUSION This study provides medical evidence to interpret the mechanism of CNNs that helps support the clinical application of artificial intelligence. KEY POINTS • CNN achieved high accuracy (93%) in classifying subsolid nodules on CT images into three categories: benign and preinvasive lesions, MIA, and IA. • The gradient-weighted class activation map (Grad-CAM) located the entire region of image features that determined the final classification, and the visualization of the separated activated areas was consistent with radiologists' expertise for diagnosing subsolid nodules. • DeepDream showed the image features that CNN learned from a training dataset in a human-recognizable pattern.
Collapse
Affiliation(s)
- Beibei Jiang
- Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080, China
| | - Yaping Zhang
- Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080, China
| | - Lu Zhang
- Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080, China
| | - Geertruida H de Bock
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Xueqian Xie
- Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080, China.
| |
Collapse
|
37
|
Wu H, Zhang Y, Hu H, Li Y, Shen X, Liu Q, Wang S, Chen H. Ground glass opacity featured lung adenocarcinoma in teenagers. J Cancer Res Clin Oncol 2021; 147:3719-3724. [PMID: 33829316 PMCID: PMC8026089 DOI: 10.1007/s00432-021-03611-9] [Citation(s) in RCA: 4] [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: 01/01/2021] [Accepted: 03/20/2021] [Indexed: 12/19/2022]
Abstract
Introduction Ground glass opacity (GGO) nodules were found incidentally by computed tomography (CT) scan in some teenagers, which turned out to be lung cancer. The purpose of this study is to summarize the characteristics of teenage patients with GGO featured lung adenocarcinoma. Methods Patients aging from 13 to 20 who were incidentally diagnosed with lung cancer were reviewed between February 2015 to December 2020. The clinical, radiological and pathological characteristics were analyzed. Results Totally 12 patients were included. All of them were diagnosed as GGO featured lung cancer through CT scan, with no presenting symptom. The median surveillance before surgery was 5.5 months, and none of these GGO lesions enlarged or altered in the property during the surveillance. The mean tumor diameter was 0.93 ± 0.25 cm. Ten patients underwent wedge resection by video-assisted thoracoscopic surgery (VATS), 9 of which were minimally invasive adenocarcinoma (MIA) and 1 of which were invasive adenocarcinoma (IAC) in the pathological analysis. One patient underwent VATS left-upper sublobectomy, pathologically diagnosed as MIA and 1 patient underwent VATS left-upper lobectomy with systematic mediastinal lymphadenectomy, pathologically diagnosed as IAC. The median postoperative hospital stay was 3 days. All patients survived without recurrence during a median follow-up of 12.5 months. Conclusions GGO nodules could be a sign of early-stage teenage lung adenocarcinoma. We proposed a screening strategy with long intervals based on a baseline CT scan for the teenage population, and a treatment strategy for diagnosed teenage patients.
Collapse
Affiliation(s)
- Haoxuan Wu
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, 270 Dong-An Road, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Yang Zhang
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, 270 Dong-An Road, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Hong Hu
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, 270 Dong-An Road, Shanghai, 200032, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Yuan Li
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
| | - Xuxia Shen
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
| | - Quan Liu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
| | - Shengping Wang
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
| | - Haiquan Chen
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, 270 Dong-An Road, Shanghai, 200032, China.
- Institute of Thoracic Oncology, Fudan University, Shanghai, 200032, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
| |
Collapse
|
38
|
Niu R, Wang Y, Shao X, Jiang Z, Wang J, Shao X. Association Between 18F-FDG PET/CT-Based SUV Index and Malignant Status of Persistent Ground-Glass Nodules. Front Oncol 2021; 11:594693. [PMID: 33842310 PMCID: PMC8024639 DOI: 10.3389/fonc.2021.594693] [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: 08/14/2020] [Accepted: 03/02/2021] [Indexed: 11/14/2022] Open
Abstract
To explore the association between 18F-FDG PET/CT-based SUV index and malignant risk of persistent ground-glass nodules (GGNs). We retrospectively analyzed a total of 166 patients with GGN who underwent PET/CT examination from January 2012 to October 2019. There were 113 women and 53 men, with an average age of 60.8 ± 9.1 years old. A total of 192 GGNs were resected and confirmed by pathology, including 22 in benign group and 170 in adenocarcinoma group. They were divided into three groups according to SUV index tertiles: Tertile 1 (0.14–0.54), Tertile 2 (0.55–1.17), and Tertile 3 (1.19–6.78), with 64 GGNs in each group. The clinical and imaging data of all patients were collected and analyzed. After adjusting for the potential confounding factors, we found that the malignancy risk of GGN significantly decreased as the SUV index increased (OR, 0.245; 95%CI, 0.119–0.504; P <0.001), the average probability of malignant GGN was 89.1% (95% CI, 53.1–98.3%), 80.5% (95% CI, 36.7–96.7%), and 34.3% (95%CI, 9.5–72.2%) for Tertile 1 to Tertile 3. And the increasing trend of SUV index was significantly correlated with the reduction of malignant risk (OR, 0.099; 95%CI, 0.025–0.394; P = 0.001), especially between Tertile 3 versus Tertile 1 (OR, 0.064; 95%CI, 0.012–0.356; P = 0.002). Curve fitting showed that the SUV index was linearly and negatively correlated with the malignant risk of GGN. SUV index is an independent correlation factor for malignancy risk of GGN, the higher the SUV index, the lower the probability of GGN malignancy.
Collapse
Affiliation(s)
- Rong Niu
- Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China.,Changzhou Key Laboratory of Molecular Imaging, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Yuetao Wang
- Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China.,Changzhou Key Laboratory of Molecular Imaging, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Xiaoliang Shao
- Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China.,Changzhou Key Laboratory of Molecular Imaging, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Zhenxing Jiang
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Jianfeng Wang
- Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China.,Changzhou Key Laboratory of Molecular Imaging, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Xiaonan Shao
- Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China.,Changzhou Key Laboratory of Molecular Imaging, The Third Affiliated Hospital of Soochow University, Changzhou, China
| |
Collapse
|
39
|
A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules. Sci Rep 2021; 11:66. [PMID: 33462251 PMCID: PMC7814025 DOI: 10.1038/s41598-020-79690-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 12/08/2020] [Indexed: 12/21/2022] Open
Abstract
This study aims to predict the histological invasiveness of pulmonary adenocarcinoma spectrum manifesting with subsolid nodules ≦ 3 cm using the preoperative CT-based radiomic approach. A total of 186 patients with 203 SSNs confirmed with surgically pathologic proof were retrospectively reviewed from February 2016 to March 2020 for training cohort modeling. The validation cohort included 50 subjects with 57 SSNs confirmed with surgically pathologic proof from April 2020 to August 2020. CT-based radiomic features were extracted using an open-source software with 3D nodular volume segmentation manually. The association between CT-based conventional features/selected radiomic features and histological invasiveness of pulmonary adenocarcinoma status were analyzed. Diagnostic models were built using conventional CT features, selected radiomic CT features and experienced radiologists. In addition, we compared diagnostic performance between radiomic CT feature, conventional CT features and experienced radiologists. In the training cohort of 203 SSNs, there were 106 invasive lesions and 97 pre-invasive lesions. Logistic analysis identified that a selected radiomic feature named GLCM_Entropy_log10 was the predictor for histological invasiveness of pulmonary adenocarcinoma spectrum (OR: 38.081, 95% CI 2.735–530.309, p = 0.007). The sensitivity and specificity for predicting histological invasiveness of pulmonary adenocarcinoma spectrum using the cutoff value of CT-based radiomic parameter (GLCM_Entropy_log10) were 84.8% and 79.2% respectively (area under curve, 0.878). The diagnostic model of CT-based radiomic feature was compared to those of conventional CT feature (morphologic and quantitative) and three experienced radiologists. The diagnostic performance of radiomic feature was similar to those of the quantitative CT feature (nodular size and solid component, both lung and mediastinal window) in prediction invasive pulmonary adenocarcinoma (IPA). The AUC value of CT radiomic feature was higher than those of conventional CT morphologic feature and three experienced radiologists. The c-statistic of the training cohort model was 0.878 (95% CI 0.831–0.925) and 0.923 (0.854–0.991) in the validation cohort. Calibration was good in both cohorts. The diagnostic performance of CT-based radiomic feature is not inferior to solid component (lung and mediastinal window) and nodular size for predicting invasiveness. CT-based radiomic feature and nomogram could help to differentiate IPA lesions from preinvasive lesions in the both independent training and validation cohorts. The nomogram may help clinicians with decision making in the management of subsolid nodules.
Collapse
|
40
|
Zhang Y, Ma X, Shen X, Wang S, Li Y, Hu H, Chen H. Surgery for pre- and minimally invasive lung adenocarcinoma. J Thorac Cardiovasc Surg 2020; 163:456-464. [PMID: 33485660 DOI: 10.1016/j.jtcvs.2020.11.151] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/21/2020] [Accepted: 11/27/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are the pre- and minimally invasive forms of lung adenocarcinoma. We aimed to investigate safety results and survival outcomes following different types of surgical resection in a large sample of patients with AIS/MIA. METHODS Medical records of patients with lung AIS/MIA who underwent surgery between 2012 and 2017 were retrospectively reviewed. Clinical characteristics, surgical types and complications, recurrence-free survival, and overall survival were investigated. RESULTS A total of 1644 patients (422 AIS and 1222 MIA) were included. The overall surgical complication rate was significantly lower in patients receiving wedge resection (1.0%), and was comparable between patients undergoing segmentectomy (3.3%) or lobectomy (5.6%). Grade ≥ 3 complications occurred in 0.1% of patients in the wedge resection group, and in a comparable proportion of patients in the segmentectomy group (1.5%) and the lobectomy group (1.5%). There was no lymph node metastasis. The 5-year recurrence-free survival rate was 100%. The 5-year overall survival rate in the entire cohort was 98.8%, and was comparable among the wedge resection group (98.8%), the segmentectomy group (98.2%), and the lobectomy group (99.4%). CONCLUSIONS Sublobar resection, especially wedge resection without lymph node dissection, may be the preferred surgical procedure for patients with AIS/MIA. If there are no risk factors, postoperative follow-up intervals may be extended. These implications should be validated in further studies.
Collapse
Affiliation(s)
- Yang Zhang
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China; Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xiangyi Ma
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China; Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xuxia Shen
- Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Shengping Wang
- Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yuan Li
- Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Hong Hu
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China; Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Haiquan Chen
- Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, China; Institute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
| |
Collapse
|
41
|
Qi LL, Wang JW, Yang L, Huang Y, Zhao SJ, Tang W, Jin YJ, Zhang ZW, Zhou Z, Yu YZ, Wang YZ, Wu N. Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation. Eur Radiol 2020; 31:3884-3897. [PMID: 33219848 DOI: 10.1007/s00330-020-07450-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 09/29/2020] [Accepted: 10/30/2020] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To explore the natural history of pulmonary subsolid nodules (SSNs) with different pathological types by deep learning-assisted nodule segmentation. METHODS Between June 2012 and June 2019, 95 resected SSNs with preoperative long-term follow-up were enrolled in this retrospective study. SSN detection and segmentation were performed on preoperative follow-up CTs using the deep learning-based Dr. Wise system. SSNs were categorized into invasive adenocarcinoma (IAC, n = 47) and non-IAC (n = 48) groups; according to the interval change during the preoperative follow-up, SSNs were divided into growth (n = 68), nongrowth (n = 22), and new emergence (n = 5) groups. We analyzed the cumulative percentages and pattern of SSN growth and identified significant factors for IAC diagnosis and SSN growth. RESULTS The mean preoperative follow-up was 42.1 ± 17.0 months. More SSNs showed growth or new emergence in the IAC than in the non-IAC group (89.4% vs. 64.6%, p = 0.009). Volume doubling time was non-significantly shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days, p = 0.077). Median mass doubling time was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). Lobulated sign (p = 0.002) and SSN mass (p = 0.004) were significant factors for differentiating IACs. IACs showed significantly higher cumulative growth percentages than non-IACs in the first 70 months of follow-up. The growth pattern of SSNs may conform to the exponential model. The initial volume (p = 0.042) was a predictor for SSN growth. CONCLUSIONS IACs appearing as SSNs showed an indolent course. The mean growth rate was larger for IACs than for non-IACs. SSNs with larger initial volume are more likely to grow. KEY POINTS • Invasive adenocarcinomas (IACs) appearing as subsolid nodules (SSNs), with a mean volume doubling time (VDT) of 1436.0 ± 1188.2 days and median mass doubling time (MDT) of 821.7 days, showed an indolent course. • The VDT was shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days), but the difference was not significant (p = 0.077). The median MDT was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). • SSNs with lobulated sign and larger mass (> 390.5 mg) may very likely be IACs. SSNs with larger initial volume are more likely to grow.
Collapse
Affiliation(s)
- Lin-Lin 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, Chaoyang District, Beijing, 100021, China
| | - Jian-Wei 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, Chaoyang District, Beijing, 100021, China
| | - Lin Yang
- Department of Diagnostic Pathology, 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, Chaoyang District, Beijing, 100021, China
| | - Yao Huang
- 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, Chaoyang District, Beijing, 100021, China
| | - Shi-Jun Zhao
- 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, Chaoyang District, Beijing, 100021, China
| | - Wei Tang
- 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, Chaoyang District, Beijing, 100021, China
| | - Yu-Jing Jin
- PET-CT Center, 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, Chaoyang District, Beijing, 100021, China
| | - Ze-Wei Zhang
- PET-CT Center, 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, Chaoyang District, Beijing, 100021, China
| | - Zhen Zhou
- School of Electronic Engineering and Computer Science, Peking University, No. 5 Yiheyuan Rd., Haidian District, Beijing, 100871, China
| | - Yi-Zhou Yu
- Deepwise AI Lab, Deepwise Inc., No. 8 Haidian avenue, Sinosteel International Plaza, Beijing, 100080, China
| | - Yi-Zhou Wang
- Center on Frontiers of Computing Studies, Department of Computer Science, Peking University, No. 5 Yiheyuan Rd., Haidian District, Beijing, 100871, China
| | - Ning Wu
- 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, Chaoyang District, Beijing, 100021, China. .,PET-CT Center, 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, Chaoyang District, Beijing, 100021, China.
| |
Collapse
|
42
|
Infante MV, Cardillo G. Lung cancer screening in never-smokers: facts and remaining issues. Eur Respir J 2020; 56:56/5/2002949. [DOI: 10.1183/13993003.02949-2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 08/07/2020] [Indexed: 12/12/2022]
|
43
|
Abstract
Most focal persistent ground glass nodules (GGNs) do not progress over 10 years. Research suggests that GGNs that do not progress, those that do, and solid lung cancers are fundamentally different diseases, although histologically they seem similar. Surveillance of GGNs to identify those that gradually progress is safe and does not risk losing a window. GGNs with 5 mm solid component or less than 10 mm consolidation (mediastinal and lung windows, respectively, on thin slice CT) are highly curable with resection. The optimal type of resection is unclear; sublobar resection is reasonable but an adequate margin is critically important.
Collapse
Affiliation(s)
- Vincent J Mase
- Department of Surgery, Division of Thoracic Surgery, Yale University School of Medicine, PO Box 208062, New Haven, CT 06520-8062, USA
| | - Frank C Detterbeck
- Department of Surgery, Division of Thoracic Surgery, Yale University School of Medicine, PO Box 208062, New Haven, CT 06520-8062, USA.
| |
Collapse
|
44
|
Lam S, Bryant H, Donahoe L, Domingo A, Earle C, Finley C, Gonzalez AV, Hergott C, Hung RJ, Ireland AM, Lovas M, Manos D, Mayo J, Maziak DE, McInnis M, Myers R, Nicholson E, Politis C, Schmidt H, Sekhon HS, Soprovich M, Stewart A, Tammemagi M, Taylor JL, Tsao MS, Warkentin MT, Yasufuku K. Management of screen-detected lung nodules: A Canadian partnership against cancer guidance document. CANADIAN JOURNAL OF RESPIRATORY CRITICAL CARE AND SLEEP MEDICINE 2020. [DOI: 10.1080/24745332.2020.1819175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Stephen Lam
- British Columbia Cancer Agency & the University of British Columbia, Vancouver, British Columbia, Canada
| | - Heather Bryant
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Laura Donahoe
- Division of Thoracic Surgery, Department of Surgery, University Health Network, Toronto, Ontario, Canada
| | - Ashleigh Domingo
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Craig Earle
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Christian Finley
- Department of Thoracic Surgery, St. Joseph's Healthcare, McMaster University, Hamilton, Ontario, Canada
| | - Anne V. Gonzalez
- Division of Respiratory Medicine, McGill University, Montreal, Quebec, Canada
| | - Christopher Hergott
- Division of Respiratory Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Rayjean J. Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Ontario, Canada
| | - Anne Marie Ireland
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Michael Lovas
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Daria Manos
- Department of Diagnostic Radiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - John Mayo
- Department of Radiology, Vancouver Coastal Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Donna E. Maziak
- Surgical Oncology Division of Thoracic Surgery, Ottawa Hospital, Ottawa, Ontario, Canada
| | - Micheal McInnis
- Joint Department of Medical Imaging, University Health Network, Toronto, Ontario, Canada
| | - Renelle Myers
- British Columbia Cancer Agency & the University of British Columbia, Vancouver, British Columbia, Canada
| | - Erika Nicholson
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Christopher Politis
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Heidi Schmidt
- University Health Network and Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Harman S. Sekhon
- Department of Pathology and Laboratory Medicine, University of Ottawa, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Marie Soprovich
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Archie Stewart
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Martin Tammemagi
- Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada
| | - Jana L. Taylor
- Department of Radiology, McGill University, Montreal, Quebec, Canada
| | - Ming-Sound Tsao
- Department of Laboratory Medicine and Pathobiology, University Health Network and Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Matthew T. Warkentin
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Ontario, Canada
| | - Kazuhiro Yasufuku
- Division of Thoracic Surgery, Department of Surgery and Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
| |
Collapse
|
45
|
Lu T, Yang X, Shi Y, Zhao M, Bi G, Liang J, Chen Z, Huang Y, Jiang W, Lin Z, Xi J, Wang S, Yang Y, Zhan C, Wang Q, Tan L. Single-cell transcriptome atlas of lung adenocarcinoma featured with ground glass nodules. Cell Discov 2020; 6:69. [PMID: 33083004 PMCID: PMC7536439 DOI: 10.1038/s41421-020-00200-x] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 07/30/2020] [Indexed: 12/13/2022] Open
Abstract
As an early type of lung adenocarcinoma, ground glass nodule (GGN) has been detected increasingly and now accounts for most lung cancer outpatients. GGN has a satisfactory prognosis and its characteristics are quite different from solid adenocarcinoma (SADC). We compared the GGN adenocarcinoma (GGN-ADC) with SADC using the single-cell RNA sequencing (scRNA-seq) to fully understand GGNs. The tumor samples of five patients with lung GGN-ADCs and five with SADCs underwent surgery were digested to a single-cell suspension and analyzed using 10× Genomic scRNA-seq techniques. We obtained 60,459 cells and then classified them as eight cell types, including cancer cells, endothelial cells, fibroblasts, T cells, B cells, Nature killer cells, mast cells, and myeloid cells. We provided a comprehensive description of the cancer cells and stromal cells. We found that the signaling pathways related to cell proliferation were downregulated in GGN-ADC cancer cells, and stromal cells had different effects in GGN-ADC and SADC based on the analyses of scRNA-seq results. In GGN-ADC, the signaling pathways of angiogenesis were downregulated, fibroblasts expressed low levels of some collagens, and immune cells were more activated. Furthermore, we used flow cytometry to isolate the cancer cells and T cells in 12 GGN-ADC samples and in an equal number of SADC samples, including CD4+ T and CD8+ T cells, and validated the expression of key molecules by quantitative real-time polymerase chain reaction analyses. Through comprehensive analyses of cell phenotypes in GGNs, we provide deep insights into lung carcinogenesis that will be beneficial in lung cancer prevention and therapy.
Collapse
Affiliation(s)
- Tao Lu
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Xiaodong Yang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Yu Shi
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Mengnan Zhao
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Guoshu Bi
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Jiaqi Liang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Zhencong Chen
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Yiwei Huang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Wei Jiang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Zongwu Lin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Junjie Xi
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Shuai Wang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Yong Yang
- Department of Cardio-Thoracic Surgery, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006 China
- Department of Thoracic Surgery, Suzhou Hospital affiliated to Nanjing Medical University, Suzhou, Jiangsu 215001 China
| | - Cheng Zhan
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Qun Wang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Lijie Tan
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| |
Collapse
|
46
|
Tsai PC, Hsu PK, Yeh YC, Chen CK, Chang YY, Huang CS, Hsu HS. Active surveillance or early resection for ground-glass nodules that need preoperative localization. J Surg Oncol 2020; 123:322-331. [PMID: 32989763 DOI: 10.1002/jso.26241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 09/11/2020] [Accepted: 09/17/2020] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Few studies have investigated the impact of active surveillance on pathological outcome ground-glass nodules (GGNs). We focused on GGNs that needed preoperative localization before resection and compared the pathological results between GGNs that underwent early resection or active surveillance. METHODS We retrospectively reviewed data of resected GGNs between January 2017 and December 2018. GGNs were classified by early resection (Group A) and active surveillance (Group B). Group B was subclassified as no (Group B1) and with (Group B2) growth, and intergroup comparison of pathological results was undertaken. RESULTS In total, 509 GGNs (124, 275, and 110 in Groups A, B1, and B2, respectively) were included. Malignancy (primary lung cancer) ratios were 68% and 72% in Groups A and B (p = .312) and 65% and 92% in Groups B1 and B2, respectively (p < .001). The ratios of invasive carcinoma were 21.4%, 9.6%, and 35.6% in Groups A, B1, and B2, respectively. Predictors for invasive carcinoma included history of lung cancer, GGN size ≥ 10 mm, solid size ≥ 6 mm, and GGN growth. CONCLUSIONS The pathological findings were similar for GGNs in the early resection and active surveillance groups. However, rates of malignancy and invasive carcinoma increased in the group that manifested growth during active surveillance.
Collapse
Affiliation(s)
- Ping-Chung Tsai
- Department of Surgery, Division of Thoracic Surgery, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Po-Kuei Hsu
- Department of Surgery, Division of Thoracic Surgery, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Yi-Chen Yeh
- Department of Pathology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chun-Ku Chen
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ying-Yueh Chang
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chien-Sheng Huang
- Department of Surgery, Division of Thoracic Surgery, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Han-Shui Hsu
- Department of Surgery, Division of Thoracic Surgery, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| |
Collapse
|
47
|
Hammer MM, Hatabu H. Subsolid pulmonary nodules: Controversy and perspective. Eur J Radiol Open 2020; 7:100267. [PMID: 32944597 PMCID: PMC7481135 DOI: 10.1016/j.ejro.2020.100267] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 08/24/2020] [Indexed: 12/27/2022] Open
Abstract
Ground glass and part-solid nodules, collectively referred to as subsolid nodules, present a challenge in management, with a high risk of malignancy but, when malignant, demonstrating indolent behavior. Emerging data suggest longer follow-up intervals and shorter duration of follow-up is likely appropriate in these nodules. Additionally, definitive therapy is shifting to less aggressive approaches such as sub-lobar resection. Patients may benefit from individualized approaches, incorporating both patient and imaging features to determine whether treatment is necessary.
Collapse
Affiliation(s)
- Mark M Hammer
- Departments of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | - Hiroto Hatabu
- Departments of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| |
Collapse
|
48
|
Affiliation(s)
- David P. Naidich
- From the Center for Biomedical Imaging, NYU Langone Medical Center, 660 1st Ave, New York, NY 10016
| | - Lea Azour
- From the Center for Biomedical Imaging, NYU Langone Medical Center, 660 1st Ave, New York, NY 10016
| |
Collapse
|
49
|
Huang CY, Huang CC, Huang WM, Liang CH, Wu FZ. Letter to the Editor Regarding "Long-Term Follow-Up of Ground-Glass Nodules After 5 Years of Stability." by Lee et al., J Thorac Oncol 2019;14:1370-7. Heart Lung Circ 2020; 29:e254-e257. [PMID: 32224087 DOI: 10.1016/j.hlc.2020.02.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 02/25/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Chung-Yao Huang
- Department of Radiology, MacKay Memorial Hospital, Taipei, Taiwan; Department of Medicine, MacKay Medical College, Taipei, Taiwan; Mackay Junior College of Medicine, Nursing, and Management, Taipei, Taiwan
| | - Chun-Chao Huang
- Department of Radiology, MacKay Memorial Hospital, Taipei, Taiwan; Department of Medicine, MacKay Medical College, Taipei, Taiwan; Mackay Junior College of Medicine, Nursing, and Management, Taipei, Taiwan
| | - Wei-Ming Huang
- Department of Radiology, MacKay Memorial Hospital, Taipei, Taiwan; Department of Medicine, MacKay Medical College, Taipei, Taiwan; Mackay Junior College of Medicine, Nursing, and Management, Taipei, Taiwan
| | - Chia-Hao Liang
- Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Fu-Zong Wu
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Medical Imaging and Radiology, Shu-Zen Junior College of Medicine and Management Kaohsiung, Kaohsiung, Taiwan.
| |
Collapse
|
50
|
Lee JH, Lim WH, Hong JH, Nam JG, Hwang EJ, Kim H, Goo JM, Park CM. Growth and Clinical Impact of 6-mm or Larger Subsolid Nodules after 5 Years of Stability at Chest CT. Radiology 2020; 295:448-455. [PMID: 32181731 DOI: 10.1148/radiol.2020191921] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background It remains unclear whether 5 years of stability is sufficient to establish the benign behavior of subsolid nodules (SSNs) of the lung. There are no guidelines for the length of follow-up needed for these SSNs. Purpose To investigate the incidence of interval growth of pulmonary SSNs 6 mm or greater in diameter after 5 years of stability and their clinical outcome. Materials and Methods This retrospective study assessed SSNs 6 mm or greater that were stable for 5 years after detection (January 2002 to December 2018). The incidence of interval growth after 5 years of stability and the clinical and radiologic features of these SSNs were investigated. Clinical stage shifts of growing SSNs, presence of metastasis, and overall survival were assessed during the follow-up period. Subgroup analysis was performed in patients with nonenhanced thin-section (section thickness ≤1.5 mm) CT for interval growth after 5 years of stability. Results A total of 235 SSNs in 235 patients (mean age, 64 years ± 10 [standard deviation]; 132 women) were evaluated. There were 212 pure ground-glass nodules and 24 part-solid nodules. During follow-up (median, 112 months; range, 84-208 months), five of the 235 SSNs (2%; three primary ground-glass nodules and two part-solid nodules) showed interval growth. Three of these five growing SSNs were 10 mm or greater. Three of the five SSNs with interval growth had clinical stage shifts after growth (from Tis [in situ] to T1mi [minimally invasive] in one lesion; from T1mi to T1a in two lesions). There were no deaths or metastases from lung cancer during follow-up. Of 160 SSNs imaged with section thickness of 1.5 mm or less, two (1%) grew; both lesions were 10 mm or greater. Conclusion Only 2% of subsolid pulmonary nodules greater than or equal to 6 mm that had been stable for 5 years showed subsequent growth. At median follow-up of 9 years (after the initial 5-year period of stability), growth of those lung nodules had no clinical effect. © RSNA, 2020 See also the editorial by Naidich and Azour in this issue.
Collapse
Affiliation(s)
- Jong Hyuk Lee
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Woo Hyeon Lim
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Jung Hee Hong
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Ju Gang Nam
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Eui Jin Hwang
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Hyungjin Kim
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Jin Mo Goo
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| | - Chang Min Park
- From the Department of Radiology and Institute of Radiation Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea (J.H.L., W.H.L., J.H.H., J.G.N., E.J.H., H.K., J.M.G., C.M.P.); and Armed Forces Seoul District Hospital, Seoul, Korea (J.H.L.)
| |
Collapse
|