Differentiating Between Brain Hemorrhage and Contrast

Study Overview
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Brief Summary
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The goal of this observational study is to use artificial intelligence to differentiate cerebral hemorrhage from contrast agent extravasation after mechanical revascularization in ischemic stroke. The main question it aims to answer is: Whether artificial intelligence can help differentiate brain hemorrhage from contrast agent extravasation. Patients with intracranial high-density lesions on CT scans within 24h after mechanical revascularization will be included. Expected to enroll 500 patients. The type of high-density lesion is determined according to dual-energy CT images or follow-up images. Patients will be divided into training group, validation and testing groups by stratified random sampling (6:2:2). After the images and the image labels are obtained, deep learning artificial intelligence will be used to learn the image characteristics and establish a diagnostic model, and the model performance and generalization ability will be evaluated.

Official Title
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Artificial Intelligence for Differentiating Between Brain Hemorrhage and Contrast Extravasation After Mechanical Revascularization in Acute Ischemic Stroke

Conditions
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Ischemic Stroke

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: (1) patients underwent non-enhanced head CT after mechanical vascularization; (2) initial post-operative non-enhanced head CT was performed within 24 h after mechanical vascularization; and (3) intracranial hyper-intensity, which was defined as an objectively higher density than the surrounding grey or white matter in the parenchyma or higher density than cerebrospinal fluid in ventricles and cisterns, could be seen on the initial non-enhanced head CT after mechanical vascularization. Exclusion Criteria: (1) the follow-up time of non-enhanced head CT after mechanical vascularization was less than 24 h; (2) artifacts (e.g. metal artifacts or motion artifacts) affected the hyper-intensity in CT images; and (3) patients underwent craniotomy after mechanical vascularization, which made it difficult to identify the area of hyper-intensity.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 100 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| hemorrhage<br>The result of the Intracranial hyper-density on CT images is determined by dual-energy CT or follow-up images: hyper-density can be seen on the virtual non-contrasted image of dual-energy CT, or high density persist longer than 48 hours. | |
| simple contrast extravasation<br>There is no Intracranial hyper-density on the virtual non-contrast images of dual-energy CT, or the follow-up CT show that the hyper-density is absorbed within 48 hours. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Develop a deep learning model to differentiate brain hemorrhage from contrast agent extravasation, and evaluate the model performance and generalization ability | The accuracy, sensitivity, specificity, precision, and recall of the model will be calculated, and confusion matrix will be display. | 2024-12 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Hemorrhage, Contrast Media Extravasation, Artificial Intelligence, Mechanical Revascularisation