A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study
Abstract Objectives Stereotactic body radiotherapy (SBRT) is a treatment option for patients with early-stage non-small cell lung cancer (NSCLC) who are unfit for surgery. Some patients may experience distant metastasis. This study aimed to develop and validate a radiomics model for predicting dista...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-01-01
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| Series: | Radiation Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13014-024-02402-z |
| _version_ | 1797276423437680640 |
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| author | Lu Yu Zhen Zhang HeQing Yi Jin Wang Junyi Li Xiaofeng Wang Hui Bai Hong Ge Xiaoli Zheng Jianjiao Ni Haoran Qi Yong Guan Wengui Xu Zhengfei Zhu Ligang Xing Andre Dekker Leonard Wee Alberto Traverso Zhaoxiang Ye Zhiyong Yuan |
| author_facet | Lu Yu Zhen Zhang HeQing Yi Jin Wang Junyi Li Xiaofeng Wang Hui Bai Hong Ge Xiaoli Zheng Jianjiao Ni Haoran Qi Yong Guan Wengui Xu Zhengfei Zhu Ligang Xing Andre Dekker Leonard Wee Alberto Traverso Zhaoxiang Ye Zhiyong Yuan |
| author_sort | Lu Yu |
| collection | DOAJ |
| description | Abstract Objectives Stereotactic body radiotherapy (SBRT) is a treatment option for patients with early-stage non-small cell lung cancer (NSCLC) who are unfit for surgery. Some patients may experience distant metastasis. This study aimed to develop and validate a radiomics model for predicting distant metastasis in patients with early-stage NSCLC treated with SBRT. Methods Patients at five institutions were enrolled in this study. Radiomics features were extracted based on the PET/CT images. After feature selection in the training set (from Tianjin), CT-based and PET-based radiomics signatures were built. Models based on CT and PET signatures were built and validated using external datasets (from Zhejiang, Zhengzhou, Shandong, and Shanghai). An integrated model that included CT and PET radiomic signatures was developed. The performance of the proposed model was evaluated in terms of its discrimination, calibration, and clinical utility. Multivariate logistic regression was used to calculate the probability of distant metastases. The cutoff value was obtained using the receiver operator characteristic curve (ROC), and the patients were divided into high- and low-risk groups. Kaplan-Meier analysis was used to evaluate the distant metastasis-free survival (DMFS) of different risk groups. Results In total, 228 patients were enrolled. The median follow-up time was 31.4 (2.0-111.4) months. The model based on CT radiomics signatures had an area under the curve (AUC) of 0.819 in the training set (n = 139) and 0.786 in the external dataset (n = 89). The PET radiomics model had an AUC of 0.763 for the training set and 0.804 for the external dataset. The model combining CT and PET radiomics had an AUC of 0.835 for the training set and 0.819 for the external dataset. The combined model showed a moderate calibration and a positive net benefit. When the probability of distant metastasis was greater than 0.19, the patient was considered to be at high risk. The DMFS of patients with high- and low-risk was significantly stratified (P < 0.001). Conclusions The proposed PET/CT radiomics model can be used to predict distant metastasis in patients with early-stage NSCLC treated with SBRT and provide a reference for clinical decision-making. Plain language summary In this study, the model was established by combining CT and PET radiomics signatures in a moderate-quantity training cohort of early-stage NSCLC patients treated with SBRT and was successfully validated in independent cohorts. Physicians could use this easy-to-use model to assess the risk of distant metastasis after SBRT. Identifying subgroups of patients with different risk factors for distant metastasis is useful for guiding personalized treatment approaches. |
| first_indexed | 2024-03-07T15:28:03Z |
| format | Article |
| id | doaj.art-b3e696f352594251a7623527ef97baa7 |
| institution | Directory Open Access Journal |
| issn | 1748-717X |
| language | English |
| last_indexed | 2024-03-07T15:28:03Z |
| publishDate | 2024-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Radiation Oncology |
| spelling | doaj.art-b3e696f352594251a7623527ef97baa72024-03-05T16:37:18ZengBMCRadiation Oncology1748-717X2024-01-0119111110.1186/s13014-024-02402-zA PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric studyLu Yu0Zhen Zhang1HeQing Yi2Jin Wang3Junyi Li4Xiaofeng Wang5Hui Bai6Hong Ge7Xiaoli Zheng8Jianjiao Ni9Haoran Qi10Yong Guan11Wengui Xu12Zhengfei Zhu13Ligang Xing14Andre Dekker15Leonard Wee16Alberto Traverso17Zhaoxiang Ye18Zhiyong Yuan19Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerZhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesZhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesZhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of SciencesDepartment of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerDepartment of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerDepartment of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerThe Affiliated Cancer Hospital of Zhengzhou UniversityThe Affiliated Cancer Hospital of Zhengzhou UniversityDepartment of Radiation Oncology, Fudan University Shanghai Cancer CenterDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical ScienceDepartment of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerDepartment of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerDepartment of Radiation Oncology, Fudan University Shanghai Cancer CenterDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical ScienceDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical CentreDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical CentreDepartment of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical CentreDepartment of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerDepartment of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerAbstract Objectives Stereotactic body radiotherapy (SBRT) is a treatment option for patients with early-stage non-small cell lung cancer (NSCLC) who are unfit for surgery. Some patients may experience distant metastasis. This study aimed to develop and validate a radiomics model for predicting distant metastasis in patients with early-stage NSCLC treated with SBRT. Methods Patients at five institutions were enrolled in this study. Radiomics features were extracted based on the PET/CT images. After feature selection in the training set (from Tianjin), CT-based and PET-based radiomics signatures were built. Models based on CT and PET signatures were built and validated using external datasets (from Zhejiang, Zhengzhou, Shandong, and Shanghai). An integrated model that included CT and PET radiomic signatures was developed. The performance of the proposed model was evaluated in terms of its discrimination, calibration, and clinical utility. Multivariate logistic regression was used to calculate the probability of distant metastases. The cutoff value was obtained using the receiver operator characteristic curve (ROC), and the patients were divided into high- and low-risk groups. Kaplan-Meier analysis was used to evaluate the distant metastasis-free survival (DMFS) of different risk groups. Results In total, 228 patients were enrolled. The median follow-up time was 31.4 (2.0-111.4) months. The model based on CT radiomics signatures had an area under the curve (AUC) of 0.819 in the training set (n = 139) and 0.786 in the external dataset (n = 89). The PET radiomics model had an AUC of 0.763 for the training set and 0.804 for the external dataset. The model combining CT and PET radiomics had an AUC of 0.835 for the training set and 0.819 for the external dataset. The combined model showed a moderate calibration and a positive net benefit. When the probability of distant metastasis was greater than 0.19, the patient was considered to be at high risk. The DMFS of patients with high- and low-risk was significantly stratified (P < 0.001). Conclusions The proposed PET/CT radiomics model can be used to predict distant metastasis in patients with early-stage NSCLC treated with SBRT and provide a reference for clinical decision-making. Plain language summary In this study, the model was established by combining CT and PET radiomics signatures in a moderate-quantity training cohort of early-stage NSCLC patients treated with SBRT and was successfully validated in independent cohorts. Physicians could use this easy-to-use model to assess the risk of distant metastasis after SBRT. Identifying subgroups of patients with different risk factors for distant metastasis is useful for guiding personalized treatment approaches.https://doi.org/10.1186/s13014-024-02402-zRadiomicsPET/CTNon-small cell lung cancerStereotactic body radiotherapyDistant metastasis |
| spellingShingle | Lu Yu Zhen Zhang HeQing Yi Jin Wang Junyi Li Xiaofeng Wang Hui Bai Hong Ge Xiaoli Zheng Jianjiao Ni Haoran Qi Yong Guan Wengui Xu Zhengfei Zhu Ligang Xing Andre Dekker Leonard Wee Alberto Traverso Zhaoxiang Ye Zhiyong Yuan A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study Radiation Oncology Radiomics PET/CT Non-small cell lung cancer Stereotactic body radiotherapy Distant metastasis |
| title | A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study |
| title_full | A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study |
| title_fullStr | A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study |
| title_full_unstemmed | A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study |
| title_short | A PET/CT radiomics model for predicting distant metastasis in early-stage non–small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study |
| title_sort | pet ct radiomics model for predicting distant metastasis in early stage non small cell lung cancer patients treated with stereotactic body radiotherapy a multicentric study |
| topic | Radiomics PET/CT Non-small cell lung cancer Stereotactic body radiotherapy Distant metastasis |
| url | https://doi.org/10.1186/s13014-024-02402-z |
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