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Liu X, Li H, Wang S, Yang S, Zhang G, Xu Y, Yang H, Shan F. CT radiomics to differentiate neuroendocrine neoplasm from adenocarcinoma in patients with a peripheral solid pulmonary nodule: a multicenter study. Front Oncol 2024; 14:1420213. [PMID: 38952551 PMCID: PMC11215045 DOI: 10.3389/fonc.2024.1420213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 06/03/2024] [Indexed: 07/03/2024] Open
Abstract
Purpose To construct and validate a computed tomography (CT) radiomics model for differentiating lung neuroendocrine neoplasm (LNEN) from lung adenocarcinoma (LADC) manifesting as a peripheral solid nodule (PSN) to aid in early clinical decision-making. Methods A total of 445 patients with pathologically confirmed LNEN and LADC from June 2016 to July 2023 were retrospectively included from five medical centers. Those patients were split into the training set (n = 316; 158 LNEN) and external test set (n = 129; 43 LNEN), the former including the cross-validation (CV) training set and CV test set using ten-fold CV. The support vector machine (SVM) classifier was used to develop the semantic, radiomics and merged models. The diagnostic performances were evaluated by the area under the receiver operating characteristic curve (AUC) and compared by Delong test. Preoperative neuron-specific enolase (NSE) levels were collected as a clinical predictor. Results In the training set, the AUCs of the radiomics model (0.878 [95% CI: 0.836, 0.915]) and merged model (0.884 [95% CI: 0.844, 0.919]) significantly outperformed the semantic model (0.718 [95% CI: 0.663, 0.769], p both<.001). In the external test set, the AUCs of the radiomics model (0.787 [95% CI: 0.696, 0.871]), merged model (0.807 [95%CI: 0.720, 0.889]) and semantic model (0.729 [95% CI: 0.631, 0.811]) did not exhibit statistical differences. The radiomics model outperformed NSE in sensitivity in the training set (85.3% vs 20.0%; p <.001) and external test set (88.9% vs 40.7%; p = .002). Conclusion The CT radiomics model could non-invasively, effectively and sensitively predict LNEN and LADC presenting as a PSN to assist in treatment strategy selection.
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Affiliation(s)
- Xiaoyu Liu
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Hongjian Li
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, North Sichuan Medical College, Nanchong, China
| | - Shengping Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Shan Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guobin Zhang
- Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yonghua Xu
- Department of Imaging and Interventional Radiology, Zhongshan-Xuhui Hospital of Fudan University, Fudan University, Shanghai, China
| | - Hanfeng Yang
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, North Sichuan Medical College, Nanchong, China
| | - Fei Shan
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
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Sasaki T, Kuno H, Hiyama T, Oda S, Masuoka S, Miyasaka Y, Taki T, Nagasaki Y, Ohtani-Kim SJY, Ishii G, Kaku S, Shroff GS, Kobayashi T. 2021 WHO Classification of Lung Cancer: Molecular Biology Research and Radiologic-Pathologic Correlation. Radiographics 2024; 44:e230136. [PMID: 38358935 DOI: 10.1148/rg.230136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
The 2021 World Health Organization (WHO) classification system for thoracic tumors (including lung cancer) contains several updates to the 2015 edition. Revisions for lung cancer include a new grading system for invasive nonmucinous adenocarcinoma that better reflects prognosis, reorganization of squamous cell carcinomas and neuroendocrine neoplasms, and description of some new entities. Moreover, remarkable advancements in our knowledge of genetic mutations and targeted therapies have led to a much greater emphasis on genetic testing than that in 2015. In 2015, guidelines recommended evaluation of only two driver mutations, ie, epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) fusions, in patients with nonsquamous non-small cell lung cancer. The 2021 guidelines recommend testing for numerous additional gene mutations for which targeted therapies are now available including ROS1, RET, NTRK1-3, KRAS, BRAF, and MET. The correlation of imaging features and genetic mutations is being studied. Testing for the immune biomarker programmed death ligand 1 is now recommended before starting first-line therapy in patients with metastatic non-small cell lung cancer. Because 70% of lung cancers are unresectable at patient presentation, diagnosis of lung cancer is usually based on small diagnostic samples (ie, biopsy specimens) rather than surgical resection specimens. The 2021 version emphasizes differences in the histopathologic interpretation of small diagnostic samples and resection specimens. Radiologists play a key role not only in evaluation of tumor and metastatic disease but also in identification of optimal biopsy targets. ©RSNA, 2024 Test Your Knowledge questions in the supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.
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Affiliation(s)
- Tomoaki Sasaki
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Hirofumi Kuno
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Takashi Hiyama
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Shioto Oda
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Sota Masuoka
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Yusuke Miyasaka
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Tetsuro Taki
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Yusuke Nagasaki
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Seiyu Jeong-Yoo Ohtani-Kim
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Genichiro Ishii
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Sawako Kaku
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Girish S Shroff
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
| | - Tatsushi Kobayashi
- From the Departments of Diagnostic Radiology (T.S., H.K., T.H., S.O., S.M., Y.M., T.K.), Pathology and Clinical Laboratories (T.T., G.I.), and Thoracic Surgery (Y.N., S.J.Y.O.K.), National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba 277-8577, Japan; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan (S.K.); Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan (Y.N.); and Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Tex (G.S.S.)
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Jiang X, Liu MW, Zhang X, Dong JY, Miao L, Sun ZH, Dong SS, Zhang L, Yang L, Li M. Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging. Diagnostics (Basel) 2023; 13:2560. [PMID: 37568923 PMCID: PMC10417025 DOI: 10.3390/diagnostics13152560] [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: 06/26/2023] [Revised: 07/18/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. METHODS A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT. RESULTS Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura. CONCLUSIONS Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.
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Affiliation(s)
- Xu Jiang
- 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, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Meng-Wen Liu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Xue Zhang
- 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, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Ji-Yan Dong
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Lei Miao
- 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, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Zi-Han Sun
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Shu-Shan Dong
- Clinical Science, Philips Healthcare, Beijing 100600, China;
| | - Li Zhang
- 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, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Lin Yang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Meng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
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Wang J, Zhong F, Xiao F, Dong X, Long Y, Gan T, Li T, Liao M. CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma. Front Oncol 2023; 13:1157891. [PMID: 37020864 PMCID: PMC10069670 DOI: 10.3389/fonc.2023.1157891] [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: 02/03/2023] [Accepted: 03/06/2023] [Indexed: 04/07/2023] Open
Abstract
Purpose Exploring a non-invasive method to accurately differentiate peripheral small cell lung cancer (PSCLC) and peripheral lung adenocarcinoma (PADC) could improve clinical decision-making and prognosis. Methods This retrospective study reviewed the clinicopathological and imaging data of lung cancer patients between October 2017 and March 2022. A total of 240 patients were enrolled in this study, including 80 cases diagnosed with PSCLC and 160 with PADC. All patients were randomized in a seven-to-three ratio into the training and validation datasets (170 vs. 70, respectively). The least absolute shrinkage and selection operator regression was employed to generate radiomics features and univariate analysis, followed by multivariate logistic regression to select significant clinical and radiographic factors to generate four models: clinical, radiomics, clinical-radiographic, and clinical-radiographic-radiomics (comprehensive). The Delong test was to compare areas under the receiver operating characteristic curves (AUCs) in the models. Results Five clinical-radiographic features and twenty-three selected radiomics features differed significantly in the identification of PSCLC and PADC. The clinical, radiomics, clinical-radiographic and comprehensive models demonstrated AUCs of 0.8960, 0.8356, 0.9396, and 0.9671 in the validation set, with the comprehensive model having better discernment than the clinical model (P=0.036), the radiomics model (P=0.006) and the clinical-radiographic model (P=0.049). Conclusions The proposed model combining clinical data, radiographic characteristics and radiomics features could accurately distinguish PSCLC from PADC, thus providing a potential non-invasive method to help clinicians improve treatment decisions.
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Affiliation(s)
- Jingting Wang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Feiyang Zhong
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Feng Xiao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinyang Dong
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yun Long
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Tian Gan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ting Li
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Meiyan Liao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Meiyan Liao,
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