Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis
Abstract Background Osteoporosis is a serious global public health issue. Currently, there are few studies that explore the use of multiparametric MRI radiomics for osteoporosis detection. The purpose of this study was to compare the performance of radiomics features from multiple MRI sequences (T1W...
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| Format: | Article |
| Language: | English |
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BMC
2024-02-01
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| Series: | BMC Musculoskeletal Disorders |
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| Online Access: | https://doi.org/10.1186/s12891-024-07309-0 |
| _version_ | 1797276204025249792 |
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| author | Tao Zhen Jing Fang Dacheng Hu Qijun Shen Mei Ruan |
| author_facet | Tao Zhen Jing Fang Dacheng Hu Qijun Shen Mei Ruan |
| author_sort | Tao Zhen |
| collection | DOAJ |
| description | Abstract Background Osteoporosis is a serious global public health issue. Currently, there are few studies that explore the use of multiparametric MRI radiomics for osteoporosis detection. The purpose of this study was to compare the performance of radiomics features from multiple MRI sequences (T1WI, T2WI and T1WI combined with T2WI) for detecting osteoporosis in patients. Methods A retrospective analysis was performed on 160 patients who had undergone dual-energy X-ray absorptiometry(DXA) and lumbar magnetic resonance imaging (MRI) at our hospital. Among them, 86 patients were diagnosed with abnormal bone mass (osteoporosis or low bone mass), and 74 patients were diagnosed with normal bone mass based on the DXA results. Sagittal T1-and T2-weighted images of all patients were imported into the uAI Research Portal (United Imaging Intelligence) for image delineation and radiomics analysis, where a series of radiomic features were obtained. A radiomic model that included T1WI, T2WI, and T1WI+T2WI was established using features selected by LASSO regression. We used ROC curve analysis to evaluate the predictive efficacy of each model for identifying bone abnormalities and conducted decision curve analysis (DCA) to evaluate the net benefit of each model. Finally, we validated the model in a sample of 35 patients from different health care institution. Results The T1WI + T2WI radiomics model showed better screening performance for patients with abnormal bone mass. In the training group, the sensitivity was 0.758, the specificity was 0.78, and the accuracy was 0.768 (AUC =0.839, 95% CI=0.757-0.901). In the validation group, the sensitivity was 0.792, the specificity was 0.875, and the accuracy was 0.833 (AUC =0.86, 95% CI=0.73-0.943).The DCA also showed that the combined model had better net benefits. In the external validation group, the sensitivity was 0.764, the specificity was 0.833, and the accuracy was 0.8 (AUC =0.824, 95% CI 0.678-0.969). Conclusions Radiomics-based multiparametric MRI can be used for the quantitative analysis of lumbar MRI and for accurately screening patients with abnormal bone mass. |
| first_indexed | 2024-03-07T15:25:00Z |
| format | Article |
| id | doaj.art-9cc54fdeddbf46d4ad9df60aa592e501 |
| institution | Directory Open Access Journal |
| issn | 1471-2474 |
| language | English |
| last_indexed | 2024-03-07T15:25:00Z |
| publishDate | 2024-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Musculoskeletal Disorders |
| spelling | doaj.art-9cc54fdeddbf46d4ad9df60aa592e5012024-03-05T17:24:46ZengBMCBMC Musculoskeletal Disorders1471-24742024-02-0125111010.1186/s12891-024-07309-0Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosisTao Zhen0Jing Fang1Dacheng Hu2Qijun Shen3Mei Ruan4Department of Radiology, Hangzhou First People’s HospitalZhejiang Provincial Hospital of Traditional Chinese medicineDepartment of Radiology, Hangzhou First People’s HospitalDepartment of Radiology, Hangzhou First People’s HospitalDepartment of Radiology, Hangzhou First People’s HospitalAbstract Background Osteoporosis is a serious global public health issue. Currently, there are few studies that explore the use of multiparametric MRI radiomics for osteoporosis detection. The purpose of this study was to compare the performance of radiomics features from multiple MRI sequences (T1WI, T2WI and T1WI combined with T2WI) for detecting osteoporosis in patients. Methods A retrospective analysis was performed on 160 patients who had undergone dual-energy X-ray absorptiometry(DXA) and lumbar magnetic resonance imaging (MRI) at our hospital. Among them, 86 patients were diagnosed with abnormal bone mass (osteoporosis or low bone mass), and 74 patients were diagnosed with normal bone mass based on the DXA results. Sagittal T1-and T2-weighted images of all patients were imported into the uAI Research Portal (United Imaging Intelligence) for image delineation and radiomics analysis, where a series of radiomic features were obtained. A radiomic model that included T1WI, T2WI, and T1WI+T2WI was established using features selected by LASSO regression. We used ROC curve analysis to evaluate the predictive efficacy of each model for identifying bone abnormalities and conducted decision curve analysis (DCA) to evaluate the net benefit of each model. Finally, we validated the model in a sample of 35 patients from different health care institution. Results The T1WI + T2WI radiomics model showed better screening performance for patients with abnormal bone mass. In the training group, the sensitivity was 0.758, the specificity was 0.78, and the accuracy was 0.768 (AUC =0.839, 95% CI=0.757-0.901). In the validation group, the sensitivity was 0.792, the specificity was 0.875, and the accuracy was 0.833 (AUC =0.86, 95% CI=0.73-0.943).The DCA also showed that the combined model had better net benefits. In the external validation group, the sensitivity was 0.764, the specificity was 0.833, and the accuracy was 0.8 (AUC =0.824, 95% CI 0.678-0.969). Conclusions Radiomics-based multiparametric MRI can be used for the quantitative analysis of lumbar MRI and for accurately screening patients with abnormal bone mass.https://doi.org/10.1186/s12891-024-07309-0OsteoporosisRadiomicsMagnetic resonance imagingLumbar spineBone mineral density |
| spellingShingle | Tao Zhen Jing Fang Dacheng Hu Qijun Shen Mei Ruan Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis BMC Musculoskeletal Disorders Osteoporosis Radiomics Magnetic resonance imaging Lumbar spine Bone mineral density |
| title | Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis |
| title_full | Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis |
| title_fullStr | Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis |
| title_full_unstemmed | Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis |
| title_short | Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis |
| title_sort | comparative evaluation of multiparametric lumbar mri radiomic models for detecting osteoporosis |
| topic | Osteoporosis Radiomics Magnetic resonance imaging Lumbar spine Bone mineral density |
| url | https://doi.org/10.1186/s12891-024-07309-0 |
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