Differentiating Between Brain Hemorrhage and Contrast

Ischemic Stroke Clinical Trial

Official title:

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

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06032819
• Other study ID #: SYSKY-2023-865-01
• Status: Not yet recruiting
• Start date: September 2023
• Est. completion date: December 2024

Study information

• Verified date: September 2023
• Source: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
• Contact: Meiwei Chen
• Phone: +86 18898534109
• Email: chenmw7[@]mail.sysu.edu.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 500
• Est. completion date: December 2024
• Est. primary completion date: July 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 100 Years

Eligibility

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.

Related Conditions & MeSH terms

• Hemorrhage
• Intracranial Hemorrhages
• Ischemic Stroke

Locations

Country	Name	City	State
n/a

Sponsors (12)

Lead Sponsor

Collaborator

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Dongguan People's Hospital, First Affiliated Hospital, Sun Yat-Sen University, Guangdong 999 Brain Hospital, Hong Kong University of Science and Technology, Peking University Shenzhen Hospital, Shantou Central Hospital, Shenshan Medical Center, Memorial Hospital of Sun Yat-sen University, The First People's Hospital of Qinzhou, The Seventh Affiliated Hospital of Sun Yat-sen University, The Third Affiliated Hospital of Guangzhou Medical University, The Third Affiliated Hospital of Southern Medical University

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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