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CT texture-based nomogram in ischaemic stroke to differentiate intracerebral hemorrhage from contrast extravasation after thrombectomy.
Cerebrovascular Diseases 2024 Februrary 11
INTRODUCTION: Post-thrombectomy intraparenchymal hyperdense (PTIH) in patients with acute ischaemic stroke (AIS) is a common CT sign, making it difficult for physicians to distinguish intracerebral hemorrhage in the early post-thrombectomy period. The aim of this study is to develop an effective model to differentiate intracerebral hemorrhage from contrast extravasation in patients with PTIH.
METHODS: We retrospectively collected information on patients who underwent endovascular thrombectomy (EVT) at two stroke centers between August 2017 and January 2023. A total of 222 patients were included in the study, including 118 patients in the development cohort, 52 patients in the internal validation cohort and 52 patients in the external validation cohort. The nomogram was constructed using R software based on independent predictors derived from the multivariate logistic regression analysis, including clinical factors and CT texture features extracted from hyperdense areas on CT images. The performance and accuracy of the derived nomogram was assessed by the area under the receiver operating characteristic curve (AUC-ROC) and calibration curves. Additionally, decision curve analysis was conducted to appraise the clinical utility of the nomogram.
RESULTS: Our nomogram was derived from two clinical factors (ASPECT score and onset to reperfusion time) and two CT texture features ( variance and uniformity), with AUC-ROC of 0.943, 0.930 and 0.937 in the development, internal validation and external validation cohorts, respectively. Furthermore, the calibration plot exhibited a strong agreement between the predicted outcome and the actual outcome. In addition, the decision curve analysis revealed the clinical utility of the nomogram in accurately predicting hemorrhage in patients with PTIH.
CONCLUSION: The developed nomogram, based on clinical factors and CT texture features, proves to be effective in distinguishing intracerebral hemorrhage from contrast extravasation in patients with PTIH.
METHODS: We retrospectively collected information on patients who underwent endovascular thrombectomy (EVT) at two stroke centers between August 2017 and January 2023. A total of 222 patients were included in the study, including 118 patients in the development cohort, 52 patients in the internal validation cohort and 52 patients in the external validation cohort. The nomogram was constructed using R software based on independent predictors derived from the multivariate logistic regression analysis, including clinical factors and CT texture features extracted from hyperdense areas on CT images. The performance and accuracy of the derived nomogram was assessed by the area under the receiver operating characteristic curve (AUC-ROC) and calibration curves. Additionally, decision curve analysis was conducted to appraise the clinical utility of the nomogram.
RESULTS: Our nomogram was derived from two clinical factors (ASPECT score and onset to reperfusion time) and two CT texture features ( variance and uniformity), with AUC-ROC of 0.943, 0.930 and 0.937 in the development, internal validation and external validation cohorts, respectively. Furthermore, the calibration plot exhibited a strong agreement between the predicted outcome and the actual outcome. In addition, the decision curve analysis revealed the clinical utility of the nomogram in accurately predicting hemorrhage in patients with PTIH.
CONCLUSION: The developed nomogram, based on clinical factors and CT texture features, proves to be effective in distinguishing intracerebral hemorrhage from contrast extravasation in patients with PTIH.
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