Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage
Abstract Backgrounds Delayed cerebral ischemia (DCI) is a significant complication following aneurysmal subarachnoid hemorrhage (aSAH), leading to poor prognosis and high mortality. This study developed a non-contrast CT (NCCT)-based radiomics nomogram for early DCI prediction in aSAH patients. Meth...
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2025-05-01
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| Online Access: | https://doi.org/10.1186/s12880-025-01722-0 |
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| author | Lingxu Chen Xiaochen Wang Sihui Wang Xuening Zhao Ying Yan Mengyuan Yuan Shengjun Sun |
| author_facet | Lingxu Chen Xiaochen Wang Sihui Wang Xuening Zhao Ying Yan Mengyuan Yuan Shengjun Sun |
| author_sort | Lingxu Chen |
| collection | DOAJ |
| description | Abstract Backgrounds Delayed cerebral ischemia (DCI) is a significant complication following aneurysmal subarachnoid hemorrhage (aSAH), leading to poor prognosis and high mortality. This study developed a non-contrast CT (NCCT)-based radiomics nomogram for early DCI prediction in aSAH patients. Methods Three hundred seventy-seven aSAH patients were included in this retrospective study. Radiomic features from the baseline CTs were extracted using PyRadiomics. Feature selection was conducted using t-tests, Pearson correlation, and Lasso regression to identify those features most closely associated with DCI. Multivariable logistic regression was used to identify independent clinical and demographic risk factors. Eight machine learning algorithms were applied to construct radiomics-only and radiomics-clinical fusion nomogram models. Results The nomogram integrated the radscore and three clinically significant parameters (aneurysm and aneurysm treatment and admission Hunt-Hess score), with the Support Vector Machine model yielding the highest performance in the validation set. The radiomics model and nomogram produced AUCs of 0.696 (95% CI: 0.578–0.815) and 0.831 (95% CI: 0.739–0.923), respectively. The nomogram achieved an accuracy of 0.775, a sensitivity of 0.750, a specificity of 0.795, and an F1 score of 0.750. Conclusion The NCCT-based radiomics nomogram demonstrated high predictive performance for DCI in aSAH patients, providing a valuable tool for early DCI identification and formulating appropriate treatment strategies. Clinical trial number Not applicable. |
| format | Article |
| id | doaj-art-36ce16ff51c949be8f350c722544ece3 |
| institution | Kabale University |
| issn | 1471-2342 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | BMC Medical Imaging |
| spelling | doaj-art-36ce16ff51c949be8f350c722544ece32025-08-20T03:54:11ZengBMCBMC Medical Imaging1471-23422025-05-0125111210.1186/s12880-025-01722-0Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhageLingxu Chen0Xiaochen Wang1Sihui Wang2Xuening Zhao3Ying Yan4Mengyuan Yuan5Shengjun Sun6Department of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical UniversityAbstract Backgrounds Delayed cerebral ischemia (DCI) is a significant complication following aneurysmal subarachnoid hemorrhage (aSAH), leading to poor prognosis and high mortality. This study developed a non-contrast CT (NCCT)-based radiomics nomogram for early DCI prediction in aSAH patients. Methods Three hundred seventy-seven aSAH patients were included in this retrospective study. Radiomic features from the baseline CTs were extracted using PyRadiomics. Feature selection was conducted using t-tests, Pearson correlation, and Lasso regression to identify those features most closely associated with DCI. Multivariable logistic regression was used to identify independent clinical and demographic risk factors. Eight machine learning algorithms were applied to construct radiomics-only and radiomics-clinical fusion nomogram models. Results The nomogram integrated the radscore and three clinically significant parameters (aneurysm and aneurysm treatment and admission Hunt-Hess score), with the Support Vector Machine model yielding the highest performance in the validation set. The radiomics model and nomogram produced AUCs of 0.696 (95% CI: 0.578–0.815) and 0.831 (95% CI: 0.739–0.923), respectively. The nomogram achieved an accuracy of 0.775, a sensitivity of 0.750, a specificity of 0.795, and an F1 score of 0.750. Conclusion The NCCT-based radiomics nomogram demonstrated high predictive performance for DCI in aSAH patients, providing a valuable tool for early DCI identification and formulating appropriate treatment strategies. Clinical trial number Not applicable.https://doi.org/10.1186/s12880-025-01722-0Aneurysmal subarachnoid hemorrhageDelayed cerebral ischemiaRadiomicsNomogramComputed tomography |
| spellingShingle | Lingxu Chen Xiaochen Wang Sihui Wang Xuening Zhao Ying Yan Mengyuan Yuan Shengjun Sun Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage BMC Medical Imaging Aneurysmal subarachnoid hemorrhage Delayed cerebral ischemia Radiomics Nomogram Computed tomography |
| title | Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage |
| title_full | Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage |
| title_fullStr | Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage |
| title_full_unstemmed | Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage |
| title_short | Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage |
| title_sort | development of a non contrast ct based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage |
| topic | Aneurysmal subarachnoid hemorrhage Delayed cerebral ischemia Radiomics Nomogram Computed tomography |
| url | https://doi.org/10.1186/s12880-025-01722-0 |
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