Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study
Background: Although determining angioarchitecture provide qualitative insights into headache-susceptible brain arteriovenous malformation (BAVM), the potential of quantitative radiomics to detect headache in unruptured BAVM remains unclear. We developed classification models that integrate radiomic...
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Elsevier
2025-06-01
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| Series: | Neuroscience Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772528625000159 |
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| author | Chia-Yu Liu Chia-Feng Lu Jr-Wei Wu Yong-Sin Hu Jih-Yuan Lin Huai-Che Yang Jing-Kai Loo Feng-Chi Chang Kang-Du Liu Chung-Jung Lin |
| author_facet | Chia-Yu Liu Chia-Feng Lu Jr-Wei Wu Yong-Sin Hu Jih-Yuan Lin Huai-Che Yang Jing-Kai Loo Feng-Chi Chang Kang-Du Liu Chung-Jung Lin |
| author_sort | Chia-Yu Liu |
| collection | DOAJ |
| description | Background: Although determining angioarchitecture provide qualitative insights into headache-susceptible brain arteriovenous malformation (BAVM), the potential of quantitative radiomics to detect headache in unruptured BAVM remains unclear. We developed classification models that integrate radiomic features and angioarchitecture to assist unruptured BAVM headache treatment decision-making. Methods: We considered patients with unruptured BAVM who underwent magnetic resonance imaging between 2010 and 2023. 146 radiomic features were assessed. Radiomic features were delineated, and angioarchitecture was analyzed. Statistical analyses, including least absolute shrinkage and selection operator regression and logistic regression, were used to select features and develop models. Receiver operating characteristic and decision curve analyses were performed to evaluate performance. Results: The clinical model based on age, sex, and parieto-occipital lesion location achieved an area under the curve (AUC) of 0.741. Adding two significant radiomic features and one angioarchitecture feature enhanced the models. The radiomic and angioarchitecture models achieved an AUC of 0.763. The combined model, with an AUC of 0.799, significantly outperformed the clinical model (P=0.046). Decision curve analysis indicated that the combined model performed best at threshold probabilities between 15% and 40%. Conclusion: Integrating radiomic features and angioarchitecture enhances the identification of unruptured BAVM headache. |
| format | Article |
| id | doaj-art-62e4e24dc9974b2fb9d4114b451ad8a3 |
| institution | OA Journals |
| issn | 2772-5286 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neuroscience Informatics |
| spelling | doaj-art-62e4e24dc9974b2fb9d4114b451ad8a32025-08-20T01:52:42ZengElsevierNeuroscience Informatics2772-52862025-06-015210020010.1016/j.neuri.2025.100200Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional studyChia-Yu Liu0Chia-Feng Lu1Jr-Wei Wu2Yong-Sin Hu3Jih-Yuan Lin4Huai-Che Yang5Jing-Kai Loo6Feng-Chi Chang7Kang-Du Liu8Chung-Jung Lin9Department of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, No. 155, Sec. 2, Linong St., Beitou District, Taipei City, 112, TaiwanDepartment of Neurology, Neurological Institute, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, Taiwan; Department of Radiology, Taipei Hospital, Ministry of Health and Welfare, No. 127, Su-Yuan Rd., Hsin-Chuang Dist., New Taipei City, 24213, TaiwanDepartment of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Neurology, Neurological Institute, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, TaiwanDepartment of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, 11217, Taipei City, Taiwan; Corresponding author.Background: Although determining angioarchitecture provide qualitative insights into headache-susceptible brain arteriovenous malformation (BAVM), the potential of quantitative radiomics to detect headache in unruptured BAVM remains unclear. We developed classification models that integrate radiomic features and angioarchitecture to assist unruptured BAVM headache treatment decision-making. Methods: We considered patients with unruptured BAVM who underwent magnetic resonance imaging between 2010 and 2023. 146 radiomic features were assessed. Radiomic features were delineated, and angioarchitecture was analyzed. Statistical analyses, including least absolute shrinkage and selection operator regression and logistic regression, were used to select features and develop models. Receiver operating characteristic and decision curve analyses were performed to evaluate performance. Results: The clinical model based on age, sex, and parieto-occipital lesion location achieved an area under the curve (AUC) of 0.741. Adding two significant radiomic features and one angioarchitecture feature enhanced the models. The radiomic and angioarchitecture models achieved an AUC of 0.763. The combined model, with an AUC of 0.799, significantly outperformed the clinical model (P=0.046). Decision curve analysis indicated that the combined model performed best at threshold probabilities between 15% and 40%. Conclusion: Integrating radiomic features and angioarchitecture enhances the identification of unruptured BAVM headache.http://www.sciencedirect.com/science/article/pii/S2772528625000159AngioarchitectureBrain arteriovenous malformationDecision curve analysisHeadacheRadiomics |
| spellingShingle | Chia-Yu Liu Chia-Feng Lu Jr-Wei Wu Yong-Sin Hu Jih-Yuan Lin Huai-Che Yang Jing-Kai Loo Feng-Chi Chang Kang-Du Liu Chung-Jung Lin Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study Neuroscience Informatics Angioarchitecture Brain arteriovenous malformation Decision curve analysis Headache Radiomics |
| title | Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study |
| title_full | Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study |
| title_fullStr | Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study |
| title_full_unstemmed | Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study |
| title_short | Enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features: A cross-sectional study |
| title_sort | enhanced detection of headache presentation in unruptured brain arteriovenous malformation through combined radiologic features a cross sectional study |
| topic | Angioarchitecture Brain arteriovenous malformation Decision curve analysis Headache Radiomics |
| url | http://www.sciencedirect.com/science/article/pii/S2772528625000159 |
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