CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor
ObjectivesThis study aimed to distinguish preoperatively anterior mediastinal thymic cysts from thymic epithelial tumors via a computed tomography (CT)-based radiomics nomogram.MethodsThis study analyzed 74 samples of thymic cysts and 116 samples of thymic epithelial tumors as confirmed by pathology...
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| Format: | Article |
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Frontiers Media S.A.
2021-12-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.744021/full |
| _version_ | 1818402350660845568 |
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| author | Chengzhou Zhang Qinglin Yang Fan Lin Fan Lin Heng Ma Haicheng Zhang Ran Zhang Ping Wang Ning Mao |
| author_facet | Chengzhou Zhang Qinglin Yang Fan Lin Fan Lin Heng Ma Haicheng Zhang Ran Zhang Ping Wang Ning Mao |
| author_sort | Chengzhou Zhang |
| collection | DOAJ |
| description | ObjectivesThis study aimed to distinguish preoperatively anterior mediastinal thymic cysts from thymic epithelial tumors via a computed tomography (CT)-based radiomics nomogram.MethodsThis study analyzed 74 samples of thymic cysts and 116 samples of thymic epithelial tumors as confirmed by pathology examination that were collected from January 2014 to December 2020. Among the patients, 151 cases (scanned at CT 1) were selected as the training cohort, and 39 cases (scanned at CT 2 and 3) served as the validation cohort. Radiomics features were extracted from pre-contrast CT images. Key features were selected by SelectKBest and least absolute shrinkage and selection operator and then used to build a radiomics signature (Rad-score). The radiomics nomogram developed herein via multivariate logistic regression analysis incorporated clinical factors, conventional CT findings, and Rad-score. Its performance in distinguishing the samples of thymic cysts from those of thymic epithelial tumors was assessed via discrimination, calibration curve, and decision curve analysis (DCA).ResultsThe radiomics nomogram, which incorporated 16 radiomics features and 3 conventional CT findings, including lesion edge, lobulation, and CT value, performed better than Rad-score, conventional CT model, and the clinical judgment by radiologists in distinguishing thymic cysts from thymic epithelial tumors. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.980 [95% confidence interval (CI), 0.963–0.993] in the training cohort and 0.992 (95% CI, 0.969–1.000) in the validation cohort. The calibration curve and the results of DCA indicated that the nomogram has good consistency and valuable clinical utility.ConclusionThe CT-based radiomics nomogram presented herein may serve as an effective and convenient tool for differentiating thymic cysts from thymic epithelial tumors. Thus, it may aid in clinical decision-making. |
| first_indexed | 2024-12-14T08:06:58Z |
| format | Article |
| id | doaj.art-945bdb19d56543039a95bb0d746bc3ef |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-14T08:06:58Z |
| publishDate | 2021-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-945bdb19d56543039a95bb0d746bc3ef2022-12-21T23:10:08ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-12-011110.3389/fonc.2021.744021744021CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial TumorChengzhou Zhang0Qinglin Yang1Fan Lin2Fan Lin3Heng Ma4Haicheng Zhang5Ran Zhang6Ping Wang7Ning Mao8Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaDepartment of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaDepartment of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaSchool of Medical Imaging, Binzhou Medical University, Yantai, ChinaDepartment of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaDepartment of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaCollaboration Department, Huiying Medical Technology, Beijing, ChinaDepartment of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaDepartment of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, ChinaObjectivesThis study aimed to distinguish preoperatively anterior mediastinal thymic cysts from thymic epithelial tumors via a computed tomography (CT)-based radiomics nomogram.MethodsThis study analyzed 74 samples of thymic cysts and 116 samples of thymic epithelial tumors as confirmed by pathology examination that were collected from January 2014 to December 2020. Among the patients, 151 cases (scanned at CT 1) were selected as the training cohort, and 39 cases (scanned at CT 2 and 3) served as the validation cohort. Radiomics features were extracted from pre-contrast CT images. Key features were selected by SelectKBest and least absolute shrinkage and selection operator and then used to build a radiomics signature (Rad-score). The radiomics nomogram developed herein via multivariate logistic regression analysis incorporated clinical factors, conventional CT findings, and Rad-score. Its performance in distinguishing the samples of thymic cysts from those of thymic epithelial tumors was assessed via discrimination, calibration curve, and decision curve analysis (DCA).ResultsThe radiomics nomogram, which incorporated 16 radiomics features and 3 conventional CT findings, including lesion edge, lobulation, and CT value, performed better than Rad-score, conventional CT model, and the clinical judgment by radiologists in distinguishing thymic cysts from thymic epithelial tumors. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.980 [95% confidence interval (CI), 0.963–0.993] in the training cohort and 0.992 (95% CI, 0.969–1.000) in the validation cohort. The calibration curve and the results of DCA indicated that the nomogram has good consistency and valuable clinical utility.ConclusionThe CT-based radiomics nomogram presented herein may serve as an effective and convenient tool for differentiating thymic cysts from thymic epithelial tumors. Thus, it may aid in clinical decision-making.https://www.frontiersin.org/articles/10.3389/fonc.2021.744021/fullradiomicsnomogramcomputed tomographythymic epithelial tumorcyst |
| spellingShingle | Chengzhou Zhang Qinglin Yang Fan Lin Fan Lin Heng Ma Haicheng Zhang Ran Zhang Ping Wang Ning Mao CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor Frontiers in Oncology radiomics nomogram computed tomography thymic epithelial tumor cyst |
| title | CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor |
| title_full | CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor |
| title_fullStr | CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor |
| title_full_unstemmed | CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor |
| title_short | CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor |
| title_sort | ct based radiomics nomogram for differentiation of anterior mediastinal thymic cyst from thymic epithelial tumor |
| topic | radiomics nomogram computed tomography thymic epithelial tumor cyst |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2021.744021/full |
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