Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases
PurposeThe purpose of this study was to explore the application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) image radiomics in the identification of spine multiple myeloma (MM) and bone metastasis (BM), and whether this method could improve the classif...
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| Format: | Article |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2022.874847/full |
| _version_ | 1828405926438109184 |
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| author | Zhicheng Jin Yongqing Wang Yizhen Wang Yangting Mao Fang Zhang Jing Yu |
| author_facet | Zhicheng Jin Yongqing Wang Yizhen Wang Yangting Mao Fang Zhang Jing Yu |
| author_sort | Zhicheng Jin |
| collection | DOAJ |
| description | PurposeThe purpose of this study was to explore the application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) image radiomics in the identification of spine multiple myeloma (MM) and bone metastasis (BM), and whether this method could improve the classification diagnosis performance compared with traditional methods.MethodsThis retrospective study collected a total of 184 lesions from 131 patients between January 2017 and January 2021. All images were visually evaluated independently by two physicians with 20 years of experience through the double-blind method, while the maximum standardized uptake value (SUVmax) of each lesion was recorded. A total of 279 radiomics features were extracted from the region of interest (ROI) of CT and PET images of each lesion separately by manual method. After the reliability test, the least absolute shrinkage and selection operator (LASSO) regression and 10-fold cross-validation were used to perform dimensionality reduction and screening of features. Two classification models of CT and PET were derived from CT images and PET images, respectively and constructed using the multivariate logistic regression algorithm. In addition, the ComModel was constructed by combining the PET model and the conventional parameter SUVmax. The performance of the three classification diagnostic models, as well as the human experts and SUVmax, were evaluated and compared, respectively.ResultsA total of 8 and 10 features were selected from CT and PET images for the construction of radiomics models, respectively. Satisfactory performance of the three radiomics models was achieved in both the training and the validation groups (Training: AUC: CT: 0.909, PET: 0.949, ComModel: 0.973; Validation: AUC: CT: 0.897, PET: 0.929, ComModel: 0.948). Moreover, the PET model and ComModel showed significant improvement in diagnostic performance between the two groups compared to the human expert (Training: P = 0.01 and P = 0.001; Validation: P = 0.018 and P = 0.033), and no statistical difference was observed between the CT model and human experts (P = 0.187 and P = 0.229, respectively).ConclusionThe radiomics model constructed based on 18F-FDG PET/CT images achieved satisfactory diagnostic performance for the classification of MM and bone metastases. In addition, the radiomics model showed significant improvement in diagnostic performance compared to human experts and PET conventional parameter SUVmax. |
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| id | doaj.art-4ced090ae1df48578a83f192b7b2ea69 |
| institution | Directory Open Access Journal |
| issn | 2296-858X |
| language | English |
| last_indexed | 2024-12-10T11:02:15Z |
| publishDate | 2022-04-01 |
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| series | Frontiers in Medicine |
| spelling | doaj.art-4ced090ae1df48578a83f192b7b2ea692022-12-22T01:51:38ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2022-04-01910.3389/fmed.2022.874847874847Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone MetastasesZhicheng Jin0Yongqing Wang1Yizhen Wang2Yangting Mao3Fang Zhang4Jing Yu5Department of Nuclear Medicine, Second Affiliated Hospital, Dalian Medical University, Dalian, ChinaSchool of Geophysics and Information Technology, China University of Geosciences, Beijing, ChinaDepartment of Nuclear Medicine, Second Affiliated Hospital, Dalian Medical University, Dalian, ChinaDepartment of Nuclear Medicine, Second Affiliated Hospital, Dalian Medical University, Dalian, ChinaDepartment of Nuclear Medicine, Second Affiliated Hospital, Dalian Medical University, Dalian, ChinaDepartment of Nuclear Medicine, Second Affiliated Hospital, Dalian Medical University, Dalian, ChinaPurposeThe purpose of this study was to explore the application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) image radiomics in the identification of spine multiple myeloma (MM) and bone metastasis (BM), and whether this method could improve the classification diagnosis performance compared with traditional methods.MethodsThis retrospective study collected a total of 184 lesions from 131 patients between January 2017 and January 2021. All images were visually evaluated independently by two physicians with 20 years of experience through the double-blind method, while the maximum standardized uptake value (SUVmax) of each lesion was recorded. A total of 279 radiomics features were extracted from the region of interest (ROI) of CT and PET images of each lesion separately by manual method. After the reliability test, the least absolute shrinkage and selection operator (LASSO) regression and 10-fold cross-validation were used to perform dimensionality reduction and screening of features. Two classification models of CT and PET were derived from CT images and PET images, respectively and constructed using the multivariate logistic regression algorithm. In addition, the ComModel was constructed by combining the PET model and the conventional parameter SUVmax. The performance of the three classification diagnostic models, as well as the human experts and SUVmax, were evaluated and compared, respectively.ResultsA total of 8 and 10 features were selected from CT and PET images for the construction of radiomics models, respectively. Satisfactory performance of the three radiomics models was achieved in both the training and the validation groups (Training: AUC: CT: 0.909, PET: 0.949, ComModel: 0.973; Validation: AUC: CT: 0.897, PET: 0.929, ComModel: 0.948). Moreover, the PET model and ComModel showed significant improvement in diagnostic performance between the two groups compared to the human expert (Training: P = 0.01 and P = 0.001; Validation: P = 0.018 and P = 0.033), and no statistical difference was observed between the CT model and human experts (P = 0.187 and P = 0.229, respectively).ConclusionThe radiomics model constructed based on 18F-FDG PET/CT images achieved satisfactory diagnostic performance for the classification of MM and bone metastases. In addition, the radiomics model showed significant improvement in diagnostic performance compared to human experts and PET conventional parameter SUVmax.https://www.frontiersin.org/articles/10.3389/fmed.2022.874847/fullradiomicsmultiple myelomabone metastases18F-FDG PET-CTSUVmax |
| spellingShingle | Zhicheng Jin Yongqing Wang Yizhen Wang Yangting Mao Fang Zhang Jing Yu Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases Frontiers in Medicine radiomics multiple myeloma bone metastases 18F-FDG PET-CT SUVmax |
| title | Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases |
| title_full | Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases |
| title_fullStr | Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases |
| title_full_unstemmed | Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases |
| title_short | Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases |
| title_sort | application of 18f fdg pet ct images based radiomics in identifying vertebral multiple myeloma and bone metastases |
| topic | radiomics multiple myeloma bone metastases 18F-FDG PET-CT SUVmax |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2022.874847/full |
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