Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06610578
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-09-18
Brief Title:
ICAS Screen and Stroke Risk Prediction Based on FIF
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Intracranial Atherosclerosis Screen and Stroke Risk Prediction Based on Fundus Imaging Features
Status:
RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
ICASFIF
Brief Summary:
Intracranial atherosclerosis stenosis ICAS is a leading cause of ischemic stroke worldwide and increase the global burden of stroke especially in the Asian population Compared with the other stroke subtypes patients with ICAS had more severe stroke stayed longer in the hospital and higher risk of recurrent ischemic events Thus early screening and effective intervention for intracranial atherosclerotic stenosis can improve the level of early warning and prevention of stroke decrease the incidence and mortality of stroke which is of vital significance Although digital subtraction angiography DSA computed tomography angiography CTA and magnetic resonance angiography MRA have a high diagnostic value for ICAS it is invasive and not available for mass population screening due to expertise expensive cost and poor economic performance Potential screening tools such as transcranial doppler sonography TCD are promising but limited by temporal bone window quality and highly depends on operators experience Therefore it is imperative to explore a novel non-invasive economic and complementary screening method for identifying the subjects with ICAS in mass populations such as primary health-care institutions and physical examination centers
The retina develops from the diencephalon shares the same embryological origin anatomic features and physiological properties with brain including blood supply via the internal carotid artery A prospective cohort study has confirmed that retinal vascular signs enhanced arteriolar light reflex are related to intracranial large artery disease8 Rhee et al study have also showed that retinal diameter variation is associated with ICAS9 Hence these findings hint retinal vascular signs may be a biomarker for ICAS Besides the traditional vascular risk factors such as older age hypertension diabetes dyslipidemia smoking and others are also tightly associated with ICAS However few studies have reported the discrimination performance of retinal vascular signs itself or combining with the traditional vascular risk factors in identifying ICAS Fundus photography has great advantages including non-invasive easy to popularize inexpensive and possess good economic benefits particularly in the age of artificial intelligence Artificial intelligence AI especially deep learning algorithm has widely applied to accurate varieties of retinal diseases detection and classification such as diabetic retinopathy and glaucoma Besides deep learning algorithm was also used to automatic segmentation of retinal arteries or veins which provides a basis for the subsequent automatic calculation of retinal vascular parameters In this study we aim to study on screening for intracranial atherosclerosis and predicting stroke risk based on fundus imaging features
The retina develops from the diencephalon shares the same embryological origin anatomic features and physiological properties with brain including blood supply via the internal carotid artery A prospective cohort study has confirmed that retinal vascular signs enhanced arteriolar light reflex are related to intracranial large artery disease8 Rhee et al study have also showed that retinal diameter variation is associated with ICAS9 Hence these findings hint retinal vascular signs may be a biomarker for ICAS Besides the traditional vascular risk factors such as older age hypertension diabetes dyslipidemia smoking and others are also tightly associated with ICAS However few studies have reported the discrimination performance of retinal vascular signs itself or combining with the traditional vascular risk factors in identifying ICAS Fundus photography has great advantages including non-invasive easy to popularize inexpensive and possess good economic benefits particularly in the age of artificial intelligence Artificial intelligence AI especially deep learning algorithm has widely applied to accurate varieties of retinal diseases detection and classification such as diabetic retinopathy and glaucoma Besides deep learning algorithm was also used to automatic segmentation of retinal arteries or veins which provides a basis for the subsequent automatic calculation of retinal vascular parameters In this study we aim to study on screening for intracranial atherosclerosis and predicting stroke risk based on fundus imaging features
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None