Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features
BackgroundExtracranial internal carotid artery dissection (EICAD) is a prominent factor in ischemic stroke in young patients, and vessel recanalization is correlated with stroke recurrence. We propose to determine the possible association between carotid duplex ultrasound (CDU) features, clinical fa...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2025.1498182/full |
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| author | Xinchun Xu Xinchun Xu Xinchun Xu Yanhong Yan Yanhong Yan Yafeng Qu Lianlian Zhang Lianlian Zhang Pinjing Hui Pinjing Hui |
| author_facet | Xinchun Xu Xinchun Xu Xinchun Xu Yanhong Yan Yanhong Yan Yafeng Qu Lianlian Zhang Lianlian Zhang Pinjing Hui Pinjing Hui |
| author_sort | Xinchun Xu |
| collection | DOAJ |
| description | BackgroundExtracranial internal carotid artery dissection (EICAD) is a prominent factor in ischemic stroke in young patients, and vessel recanalization is correlated with stroke recurrence. We propose to determine the possible association between carotid duplex ultrasound (CDU) features, clinical factors, and vessel recanalization in EICAD patients.MethodsIn the current retrospective study, data from 202 patients diagnosed with EICAD by CDU and confirmed by computed tomography angiography (CTA) or high-resolution magnetic resonance imaging (HRMRI) were encompassed. Patients were randomized 7:3 into training cohort (n = 142) and validation cohort (n = 60). The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis were used to build a nomogram to predict recanalization. At last, we assessed the performance of the nomogram with an area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC).ResultsThe nomogram included CDU features (intramural hematoma, Intraluminal thrombus, and stenosis degree) and age, with AUC values of 0.906 (95% CI: 0.857–0.946) and 0.903 (95% CI: 0.820–0.963) in the training cohort and the validation cohort, respectively. Using a probability cutoff of 0.5 derived from the Youden index, patients were stratified into high-risk (recanalization probability <50%) and low-risk groups (≥50%). DCA showed that the nomogram performed significantly better across various threshold probabilities, and CIC demonstrated that the nomogram offers superior net benefit across a broad range of threshold probabilities, indicating its significant predictive value.ConclusionA nomogram depended on CDU and clinical features could accurately predict recanalization in EICAD patients. The nomogram may facilitate early identification of high-risk patients and personalized therapeutic strategies. |
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| institution | OA Journals |
| issn | 1664-2295 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Neurology |
| spelling | doaj-art-28e6c869c2854e998e5ec6f8dfcadae32025-08-20T02:07:59ZengFrontiers Media S.A.Frontiers in Neurology1664-22952025-04-011610.3389/fneur.2025.14981821498182Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical featuresXinchun Xu0Xinchun Xu1Xinchun Xu2Yanhong Yan3Yanhong Yan4Yafeng Qu5Lianlian Zhang6Lianlian Zhang7Pinjing Hui8Pinjing Hui9Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Stroke Center, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Ultrasound, The Affiliated Zhangjiagang Hospital of Soochow University, Suzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Stroke Center, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Ultrasound, The Affiliated Zhangjiagang Hospital of Soochow University, Suzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Stroke Center, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, ChinaDepartment of Stroke Center, The First Affiliated Hospital of Soochow University, Suzhou, ChinaBackgroundExtracranial internal carotid artery dissection (EICAD) is a prominent factor in ischemic stroke in young patients, and vessel recanalization is correlated with stroke recurrence. We propose to determine the possible association between carotid duplex ultrasound (CDU) features, clinical factors, and vessel recanalization in EICAD patients.MethodsIn the current retrospective study, data from 202 patients diagnosed with EICAD by CDU and confirmed by computed tomography angiography (CTA) or high-resolution magnetic resonance imaging (HRMRI) were encompassed. Patients were randomized 7:3 into training cohort (n = 142) and validation cohort (n = 60). The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis were used to build a nomogram to predict recanalization. At last, we assessed the performance of the nomogram with an area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC).ResultsThe nomogram included CDU features (intramural hematoma, Intraluminal thrombus, and stenosis degree) and age, with AUC values of 0.906 (95% CI: 0.857–0.946) and 0.903 (95% CI: 0.820–0.963) in the training cohort and the validation cohort, respectively. Using a probability cutoff of 0.5 derived from the Youden index, patients were stratified into high-risk (recanalization probability <50%) and low-risk groups (≥50%). DCA showed that the nomogram performed significantly better across various threshold probabilities, and CIC demonstrated that the nomogram offers superior net benefit across a broad range of threshold probabilities, indicating its significant predictive value.ConclusionA nomogram depended on CDU and clinical features could accurately predict recanalization in EICAD patients. The nomogram may facilitate early identification of high-risk patients and personalized therapeutic strategies.https://www.frontiersin.org/articles/10.3389/fneur.2025.1498182/fullextracranial internal carotid artery dissectionvessel recanalizationcarotid duplex ultrasoundpredictive modelnomogram |
| spellingShingle | Xinchun Xu Xinchun Xu Xinchun Xu Yanhong Yan Yanhong Yan Yafeng Qu Lianlian Zhang Lianlian Zhang Pinjing Hui Pinjing Hui Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features Frontiers in Neurology extracranial internal carotid artery dissection vessel recanalization carotid duplex ultrasound predictive model nomogram |
| title | Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features |
| title_full | Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features |
| title_fullStr | Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features |
| title_full_unstemmed | Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features |
| title_short | Predicting vessel recanalization in extracranial internal carotid artery dissection: a nomogram based on ultrasonography and clinical features |
| title_sort | predicting vessel recanalization in extracranial internal carotid artery dissection a nomogram based on ultrasonography and clinical features |
| topic | extracranial internal carotid artery dissection vessel recanalization carotid duplex ultrasound predictive model nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2025.1498182/full |
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