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Wang Y, Li C, Wang Z, Wu R, Li H, Meng Y, Liu H, Song Y. Established the prediction model of early-stage non-small cell lung cancer spread through air spaces (STAS) by radiomics and genomics features. Asia Pac J Clin Oncol 2024. [PMID: 38952146 DOI: 10.1111/ajco.14099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 05/17/2024] [Accepted: 06/11/2024] [Indexed: 07/03/2024]
Abstract
BACKGROUND This study was aimed to establish a prediction model for spread through air spaces (STAS) in early-stage non-small cell lung cancer based on imaging and genomic features. METHODS We retrospectively collected 204 patients (47 STAS+ and 157 STAS-) with non-small cell lung cancer who underwent surgical treatment in the Jinling Hospital from January 2021 to December 2021. Their preoperative CT images, genetic testing data (including next-generation sequencing data from other hospitals), and clinical data were collected. Patients were randomly divided into training and testing cohorts (7:3). RESULTS The study included a total of 204 eligible patients. STAS were found in 47 (23.0%) patients, and no STAS were found in 157 (77.0%) patients. The receiver operating characteristic curve showed that radiomics model, clinical genomics model, and mixed model had good predictive performance (area under the curve [AUC] = 0.85; AUC = 0.70; AUC = 0.85). CONCLUSIONS The prediction model based on radiomics and genomics features has a good prediction performance for STAS.
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Affiliation(s)
- Yimin Wang
- Department of Respiratory Medicine, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Chuling Li
- Department of Respiratory Medicine, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Zhaofeng Wang
- Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Ranpu Wu
- Department of Respiratory Medicine, Jinling Hospital, Southeast University School of Medicine, Nanjing, China
| | - Huijuan Li
- Department of Respiratory and Critical Care Medicine, The First School of Clinical Medicine, Jinling Hospital, Southern Medical University (Guangzhou), Nanjing, China
| | - Yunchang Meng
- Department of Respiratory Medicine, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Hongbing Liu
- Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Yong Song
- Department of Respiratory Medicine, Jinling Hospital, Nanjing Medical University, Nanjing, China
- Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
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Chen X, Zhou H, Wu M, Xu M, Li T, Wang J, Sun X, Tsutani Y, Xie M. Prognostic impact of spread through air spaces in patients with ≤2 cm stage IA lung adenocarcinoma. J Thorac Dis 2024; 16:2432-2442. [PMID: 38738220 PMCID: PMC11087609 DOI: 10.21037/jtd-24-444] [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: 03/18/2024] [Accepted: 04/17/2024] [Indexed: 05/14/2024]
Abstract
Background In 2015, the World Health Organization (WHO) included spread through air space (STAS) as a new invasive mode of lung cancer. As a new mode of lung cancer dissemination, STAS has a significant and negative impact on patient prognosis. The surgical approach as well as lymph node dissection (LND) for STAS-positive patients is currently unclear. The aim of this study was to investigate the impact of different surgical approaches to STAS and LND on the prognosis of patients with ≤2 cm stage IA lung adenocarcinoma (LUAD). This study also investigated the possible relationship between STAS and the micropapillary histological subtype and its impact on patient prognosis. Methods A total of 212 patients with LUAD were included in this study from January 2016 to December 2017, and the overall survival (OS) of the patients was compared. The chi-square test and t-test were applied to compare the clinicopathological data of the patients, and the Cox model was used for the multivariate survival analysis. Results Of the 212 patients, 93 (43.9%) were STAS positive. The univariate analysis showed that the surgical approach, LND type, micropapillary pattern (MP), solid pattern, and STAS were risk factors for OS. The multivariate analysis showed that the surgical approach, MP, and STAS were risk factors for OS. The STAS-positive patients who underwent lobectomy had a better prognosis than those who underwent sublobar resection; however, there was no significant difference between the two surgical procedures in the STAS-negative group. Additionally, the STAS-positive patients who underwent systematic lymph node dissection (SLND) had a better prognosis than those who underwent limited lymph node dissection (LLND); however, there was no significant difference between the two LNDs in the STAS-negative group. Conclusions STAS plays an important role in patient prognosis and is an independent risk factor for OS of patients with ≤2 cm stage IA LUAD. When STAS is positive, the choice of lobectomy with SLND may result in a better long-term prognosis for patients.
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Affiliation(s)
- Xiao Chen
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Hangcheng Zhou
- Department of Pathology, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China
| | - Mingsheng Wu
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Meiqing Xu
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Tian Li
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Jun Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Xiaohui Sun
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yasuhiro Tsutani
- Division of Thoracic Surgery, Department of Surgery, Kindai University Faculty of Medicine, Osaka-Sayama, Japan
| | - Mingran Xie
- Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
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Gong J, Yin R, Sun L, Gao N, Wang X, Zhang L, Zhang Z. CT-based radiomics model to predict spread through air space in resectable lung cancer. Cancer Med 2023; 12:18755-18766. [PMID: 37676092 PMCID: PMC10557899 DOI: 10.1002/cam4.6496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS. METHOD There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient to calculate the correlation and redundancy of elements, and redundant features less than 0.80 were removed. In order to reduce the level of overfitting and avoid statistical biases, a dimension reduction process of the dataset was conducted to decrease the number of features. Finally, a radiomics model included 44 features was established to predict STAS. To evaluate the performance of the model, the receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated, and the accuracy of the model was verified by 10-fold cross-validation. RESULTS The incidence of STAS was 38.2% (205/537). The tumor type, maximum tumor diameters, and consolidation tumor ratio were significantly different between STAS group and non-STAS group. The training group included 430 patients, while the test group was consisted with 107. The training group achieved an AUC of 0.825 (sensitivity, 0.875; specificity, 0.621; and accuracy, 0.749) and the test group had an AUC of 0.802 (sensitivity, 0.797; specificity,0.688; and accuracy, 0.748). The 10-fold cross-validation had an AUC of 0.834. CONCLUSION CT-based radiomic model can predict STAS effectively, which is of great importance to guide the selection of operation types before surgery.
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Affiliation(s)
- Jialin Gong
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Rui Yin
- School of Biomedical Engineering & TechnologyTianjin Medical UniversityTianjinChina
| | - Leina Sun
- Department of Pathology, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Na Gao
- Department of Pathology, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Xiaofei Wang
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Lianmin Zhang
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Zhenfa Zhang
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
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Ding Y, Zhao S, Liu X, Ren J, Li J, Zhang W, Xu M, Sun D. The value of frozen section diagnosis of tumor spread through air spaces in small-sized (≤ 2 cm) non-small cell lung cancer. World J Surg Oncol 2023; 21:195. [PMID: 37394469 DOI: 10.1186/s12957-023-03092-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 06/29/2023] [Indexed: 07/04/2023] Open
Abstract
BACKGROUND The current accuracy of frozen section diagnosis of tumor spread through air spaces (STAS) in non-small cell lung cancer (NSCLC) is poor. However, the accuracy and prognostic value of STAS assessment on frozen sections in small-sized NSCLC (diameter ≤ 2 cm) is unknown. METHODS Three hundred fifty-two patients with clinical stage I NSCLC (≤ 2 cm) were included, of which the paraffin sections and frozen sections were reviewed. The accuracy of STAS diagnosis in frozen sections was assessed using paraffin sections as the gold standard. The relationship between STAS on frozen sections and prognosis was assessed by the Kaplan-Meier method and log-rank tests. RESULTS STAS on frozen sections in 58 of 352 patients could not be evaluated. In the other 294 patients, 36.39% (107/294) was STAS-positive on paraffin sections and 29.59% (87/294) on frozen sections. The accuracy of frozen section diagnosis of STAS was 74.14% (218/294), sensitivity was 55.14% (59/107), specificity was 85.02% (159/187) and agreement was moderate (K = 0.418). In subgroup analysis, the Kappa values for frozen section diagnosis of STAS in the consolidation-to-tumor ratio (CTR) ≤ 0.5 group and CTR > 0.5 group were 0.368, 0.415, respectively. In survival analysis, STAS-positive frozen sections were associated with worse recurrence-free survival in the CTR > 0.5 group (P < 0.05). CONCLUSIONS The moderate accuracy and prognostic significance of frozen section diagnosis of STAS in clinical stage I NSCLC (≤ 2 cm in diameter; CTR > 0.5) suggests that frozen section assessment of STAS can be applied to the treatment strategy of small-sized NSCLC with CTR > 0.5.
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Affiliation(s)
- Yun Ding
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Shutong Zhao
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
- Department of Pathology, Tianjin Chest Hospital (Affiliated Hospital of Tianjin University), No. 261, Taierzhuang South Road, Jinnan District, Tianjin, 300222, China
| | - Xin Liu
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Jie Ren
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
- Department of Thoracic Surgery, Tianjin Jinnan Hospital, Tianjin, China
| | - Jiuzhen Li
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Weiran Zhang
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
- Department of Thoracic Surgery, Tianjin Chest Hospital (Affiliated Hospital of Tianjin University), No. 261, Taierzhuang South Road, Jinnan District, Tianjin, 300222, China
| | - Meilin Xu
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China.
- Department of Pathology, Tianjin Chest Hospital (Affiliated Hospital of Tianjin University), No. 261, Taierzhuang South Road, Jinnan District, Tianjin, 300222, China.
| | - Daqiang Sun
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China.
- Department of Thoracic Surgery, Tianjin Chest Hospital (Affiliated Hospital of Tianjin University), No. 261, Taierzhuang South Road, Jinnan District, Tianjin, 300222, China.
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Igai H, Matsuura N, Kamiyoshihara M. Invited commentary on: The usefulness of the nomogram to predict tumor spread through air spaces (STAS) in patients with clinical stage I non-small cell lung cancer preoperatively. Eur J Cardiothorac Surg 2022; 62:6585338. [PMID: 35553658 DOI: 10.1093/ejcts/ezac309] [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: 04/29/2022] [Revised: 05/05/2022] [Accepted: 05/09/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Hitoshi Igai
- Department of General Thoracic Surgery,, Japanese Red Cross Maebashi Hospital
| | - Natsumi Matsuura
- Department of General Thoracic Surgery,, Japanese Red Cross Maebashi Hospital
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