RadiologyNCT05614193
Deep Enhanced Imaging in Stroke and Vascular Neurology
An observational study of Radiology and Cerebral Stroke, run by Chinese PLA General Hospital at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- Radiology, Cerebral Stroke, Vascular Diseases
- What is being tested?
- Deep learning imaging enhancement
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Dec 2022to 31 Dec 2027
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients have experienced stroke or cerebral ischemia and undergone brain imaging and vascular imaging.
Who may be able to join
- 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
Who cannot join
- severe movement artifacts
- incidental finding of tumor lesion or craniocerebral surgery history
- poor imaging failed to perform deep learning method
- women who pregnancy
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Chinese PLA General Hospital
Beijing, Beijing Municipality, 100853
Jinhao Lyu, MD, 330322990@qq.com
About this study
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.
Read the 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.
- Conditions
- Radiology, Cerebral Stroke, Vascular Diseases
- Being tested
- Deep learning imaging enhancement
- Keywords
- Deep learning, Medical imaging, Cerebral stroke, Cerebrovascular disease, Vascular imaging
- Medical subject headings
- Stroke, Vascular Diseases, Cerebrovascular Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Deep learning imaging enhancementDiagnostic test
Conventional imaging or down-sampling imaging from CT or MR are enhanced by approved deep learning method.
| Study group | Role | What they receive |
|---|---|---|
| Imaging group | Participants with suspecting brain stroke or vascular lesion conducted conventional CT or MR imaging and deep enhanced imaging. Receives: Diagnostic Test: Deep learning imaging enhancement |
What is being measured
The primary outcome is the main question the study is designed to answer.
The performance of deep enhanced imaging in lesion detection and diagnosis
The performance of deep enhanced imaging in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Nov 2022
- Study start1 Dec 2022
- Primary completion31 Dec 2027 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for RadiologyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chinese PLA General Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xin Lou, Chinese PLA General Hospital
- Investigators
- Lou Xin, Study chair, Chinese PLA General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05614193
- Sponsor's protocol ID
- AI-301
- Status last verified
- Feb 2023
- First submitted
- 5 Nov 2022
- Last updated
- 8 Feb 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No