Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor
BackgroundHigh expression levels of programmed death receptor 1 (PD-1) and its ligand 1 (PD-L1) have been observed in thymic epithelial tumors (TET), suggesting their potential as prognostic indicators for disease progression and the effectiveness of immunotherapy in TET. The conventional method obt...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1555530/full |
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| author | Jie Shen Lantian Zhang Shuke Li Xiaofei Mu Tongfu Yu Wei Zhang Yue Yu Jing He Wen Gao |
| author_facet | Jie Shen Lantian Zhang Shuke Li Xiaofei Mu Tongfu Yu Wei Zhang Yue Yu Jing He Wen Gao |
| author_sort | Jie Shen |
| collection | DOAJ |
| description | BackgroundHigh expression levels of programmed death receptor 1 (PD-1) and its ligand 1 (PD-L1) have been observed in thymic epithelial tumors (TET), suggesting their potential as prognostic indicators for disease progression and the effectiveness of immunotherapy in TET. The conventional method obtaining PD-L1 was challenging due to invasive sampling and tumor heterogeneityMethodsA total of 124 patients with pathologically confirmed TET (57 PD-L1 positive, 67 PD-L1 negative) were retrospectively enrolled and allocated into training and validation cohorts in a ratio of 7:3. Radiomics features were extracted from T1-weighted, T2-weighted fat suppression, and apparent diffusion coefficient (ADC) map images to establish a radiomics signature in the training cohort. Multivariate logistic regression analysis was conducted to develop a combined radiomics nomogram that incorporated clinical, conventional MR features, or ADC model for evaluation purposes. The performance of each model was compared using receiver operating characteristics analysis, while discrimination, calibration, and clinical efficiency of the combined radiomics nomogram were assessed.ResultsThe radiomics signature, consisting of four features, demonstrated a favorable ability to predict and differentiate between PD-L1 positive and negative TET patients. The combined radiomics nomogram, which incorporates the peri-cardial invasion sign, ADC value, WHO classification, and radiomics signature, showed excellent performance (training cohort: area under the curve [AUC] = 0.903; validation cohorts: AUC = 0.894). The calibration curve and decision curve analysis further confirmed the clinical usefulness of this combined model. The decision curve analysis demonstrated the clinical utility of the integrated radiomics nomogram.ConclusionsThe radiomics signature serves as a valuable tool for predicting the PD-L1 status of TET patients. Furthermore, the integration of radiomics nomogram enhances the personalized prediction capability. |
| format | Article |
| id | doaj-art-cfcca8fa8a4c42488a72cc763fb4e5e4 |
| institution | OA Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-cfcca8fa8a4c42488a72cc763fb4e5e42025-08-20T02:09:35ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-04-011610.3389/fimmu.2025.15555301555530Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumorJie Shen0Lantian Zhang1Shuke Li2Xiaofei Mu3Tongfu Yu4Wei Zhang5Yue Yu6Jing He7Wen Gao8Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Oncology, The Friendship Hospital of Ili Kazakh Autonomous Prefecture, Yining, ChinaDepartment of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaBackgroundHigh expression levels of programmed death receptor 1 (PD-1) and its ligand 1 (PD-L1) have been observed in thymic epithelial tumors (TET), suggesting their potential as prognostic indicators for disease progression and the effectiveness of immunotherapy in TET. The conventional method obtaining PD-L1 was challenging due to invasive sampling and tumor heterogeneityMethodsA total of 124 patients with pathologically confirmed TET (57 PD-L1 positive, 67 PD-L1 negative) were retrospectively enrolled and allocated into training and validation cohorts in a ratio of 7:3. Radiomics features were extracted from T1-weighted, T2-weighted fat suppression, and apparent diffusion coefficient (ADC) map images to establish a radiomics signature in the training cohort. Multivariate logistic regression analysis was conducted to develop a combined radiomics nomogram that incorporated clinical, conventional MR features, or ADC model for evaluation purposes. The performance of each model was compared using receiver operating characteristics analysis, while discrimination, calibration, and clinical efficiency of the combined radiomics nomogram were assessed.ResultsThe radiomics signature, consisting of four features, demonstrated a favorable ability to predict and differentiate between PD-L1 positive and negative TET patients. The combined radiomics nomogram, which incorporates the peri-cardial invasion sign, ADC value, WHO classification, and radiomics signature, showed excellent performance (training cohort: area under the curve [AUC] = 0.903; validation cohorts: AUC = 0.894). The calibration curve and decision curve analysis further confirmed the clinical usefulness of this combined model. The decision curve analysis demonstrated the clinical utility of the integrated radiomics nomogram.ConclusionsThe radiomics signature serves as a valuable tool for predicting the PD-L1 status of TET patients. Furthermore, the integration of radiomics nomogram enhances the personalized prediction capability.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1555530/fullMRIthymic epitelial tumorsradiomicsPD-L1immunotharapy |
| spellingShingle | Jie Shen Lantian Zhang Shuke Li Xiaofei Mu Tongfu Yu Wei Zhang Yue Yu Jing He Wen Gao Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor Frontiers in Immunology MRI thymic epitelial tumors radiomics PD-L1 immunotharapy |
| title | Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor |
| title_full | Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor |
| title_fullStr | Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor |
| title_full_unstemmed | Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor |
| title_short | Multi-sequence MRI based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor |
| title_sort | multi sequence mri based radiomics nomogram for prediction expression of programmed death ligand 1 in thymic epithelial tumor |
| topic | MRI thymic epitelial tumors radiomics PD-L1 immunotharapy |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1555530/full |
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