Deep Enhanced Imaging in Stroke and Vascular Neurology

Sponsor

Chinese PLA General Hospital (Other)

Overall Status

Not yet recruiting

CT.gov ID

NCT05614193

Collaborator

(none)

1,000

Enrollment

Location

Anticipated Duration (Months)

16.4

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

To investigate the performance of enhanced computed tomography (CT) or magnetic resonance (MR) imaging by deep learning relative to conventional CT or MR imaging in brain stroke and vascular neurology. We expect that the deep enhanced imaging method can shorten the time stay in the imaging session of stroke patients, optimize the overall imaging quality and improve the patients' care in imaging session.

Condition or Disease	Intervention/Treatment	Phase
Radiology Cerebral Stroke Vascular Diseases	Diagnostic Test: Deep learning imaging enhancement

Detailed Description

Early diagnosis of cerebral infarction, detection of ischemic penumbra, evaluation of collateral circulation and identification of vascular lesions by imaging are critical for treatment decision and outcome improvement in cerebral stroke. Multimodal computed tomography (CT) and magnetic resonance (MR) imaging are most prevalent and accessible approaches in clinical scenarios. These two approaches are downgraded either by radiation exposure or long scanning time which may hinder the rapid treatment for patients. Deep learning has shown substantial achievements in medical imaging enhancement. The added value of deep learning method in stroke and vascular neurology has not been thoroughly validated. In this study, we aimed to investigate the performance of enhanced computed tomography (CT) or magnetic resonance (MR) imaging by deep learning relative to conventional CT or MR imaging in brain stroke and vascular neurology. We expect that the deep enhanced imaging method can shorten the time stay in the imaging session of stroke patients, optimize the overall imaging quality and improve the patients' care in imaging session.

Study Design

Study Type:

Observational

Anticipated Enrollment :

1000 participants

Observational Model:

Case-Only

Time Perspective:

Prospective

Official Title:

Deep Enhanced Imaging in Stroke and Vascular Neurology

Anticipated Study Start Date :

Dec 1, 2022

Anticipated Primary Completion Date :

Dec 31, 2027

Anticipated Study Completion Date :

Dec 31, 2027

Arms and Interventions

Arm	Intervention/Treatment
Imaging group Participants with suspecting brain stroke or vascular lesion conducted conventional CT or MR imaging and deep enhanced imaging.	Diagnostic Test: Deep learning imaging enhancement Conventional imaging or down-sampling imaging from CT or MR are enhanced by approved deep learning method.

Arm

Intervention/Treatment

Imaging group

Participants with suspecting brain stroke or vascular lesion conducted conventional CT or MR imaging and deep enhanced imaging.

Diagnostic Test: Deep learning imaging enhancement

Conventional imaging or down-sampling imaging from CT or MR are enhanced by approved deep learning method.

Outcome Measures

Primary Outcome Measures

The performance of deep enhanced imaging in lesion detection and diagnosis [1 year]
The performance of deep enhanced imaging in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 100 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

suspecting to have experienced stroke or cerebral ischemia and needed to undergo brain imaging and vascular imaging including CT or MRI
no history of kidney failure
a minimum age of 18 years
obtained written informed consent