Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke
| Autor: | Michael D. Hill, Connor C. McDougall, Brooklyn Mcdougall, Hulin Kuang, Kevin J. Chung, Zarina Assis, Alexis T Wilson, Mohamed Najm, Mayank Goyal, Wu Qiu, Jay Kumar Raghavan Nair, Andrew M. Demchuk, Bijoy K. Menon |
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| Rok vydání: | 2018 |
| Předmět: |
Male
medicine.medical_specialty Support Vector Machine Computed Tomography Angiography Neuroimaging 030218 nuclear medicine & medical imaging Linear discriminative analysis 03 medical and health sciences 0302 clinical medicine Radiomics Image Interpretation Computer-Assisted Humans Medicine Radiology Nuclear Medicine and imaging In patient cardiovascular diseases Thrombus Acute ischemic stroke Proximal occlusion Aged Receiver operating characteristic medicine.diagnostic_test business.industry Adult Brain Middle Aged medicine.disease Stroke Treatment Outcome ROC Curve Case-Control Studies Tissue Plasminogen Activator Angiography cardiovascular system Female Neurology (clinical) Radiology Intracranial Thrombosis Tomography X-Ray Computed business 030217 neurology & neurosurgery |
| Zdroj: | American Journal of Neuroradiology. 40:39-44 |
| ISSN: | 1936-959X 0195-6108 |
| Popis: | BACKGROUND AND PURPOSE: Thrombus characteristics identified on non-contrast CT (NCCT) are potentially associated with recanalization with intravenous (IV) alteplase in patients with acute ischemic stroke (AIS). Our aim was to determine the best radiomics-based features of thrombus on NCCT and CT angiography associated with recanalization with IV alteplase in AIS patients and proximal intracranial thrombi. MATERIALS AND METHODS: With a nested case-control design, 67 patients with ICA/M1 MCA segment thrombus treated with IV alteplase were included in this analysis. Three hundred twenty-six radiomics features were extracted from each thrombus on both NCCT and CTA images. Linear discriminative analysis was applied to select features most strongly associated with early recanalization with IV alteplase. These features were then used to train a linear support vector machine classifier. Ten times 5-fold cross-validation was used to evaluate the accuracy of the trained classifier and the stability of the selected features. RESULTS: Receiver operating characteristic curves showed that thrombus radiomics features are predictive of early recanalization with IV alteplase. The combination of radiomics features from NCCT, CTA, and radiomics changes is best associated with early recanalization with IV alteplase (area under the curve = 0.85) and was significantly better than any single feature such as thrombus length (P < .001), volume (P < .001), and permeability as measured by mean attenuation increase (P < .001), maximum attenuation in CTA (P < .001), maximum attenuation increase (P < .001), and assessment of residual flow grade (P < .001). CONCLUSIONS: Thrombus radiomics features derived from NCCT and CTA are more predictive of recanalization with IV alteplase in patients with acute ischemic stroke with proximal occlusion than previously known thrombus imaging features such as length, volume, and permeability. |
| Databáze: | OpenAIRE |
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