Cerebral Small Vessel DiseaseNCT06667635
Intelligent Analysis and Clinical Validation of Cerebral Small Vessel Disease on Magnetic Resonance Imaging：A Multi-center Study
An observational study of Cerebral Small Vessel Disease, run by Chinese PLA General Hospital at 1 site in China.
Trial summary
Cerebral small vessel disease (CSVD) accounts for 20% of ischemic strokes and is the most common cause of vascular cognitive impairment. Early identification of CSVD is critical for early intervention and improve clinical outcomes. Read more about this study
- Who is it for?
- Ages 40 years and olderHealthy volunteers can take part
- Conditions the study is for
- Cerebral Small Vessel Disease
- What is being tested?
- Artificial intelligence
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Nov 2024to 1 Sep 2030
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 40 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: This is a multicenter study with a total plan of 1000 patients, 500 from Chinese PLA General Hospital and 500 from other centers.
Who may be able to join
- ① Men and women age 40 years or older;
- At least one vascular risk factor has been identified, including hypertension, diabetes, hyperlipidemia, coronary heart disease, and chronic kidney disease；
- The patient performed two brain MRI Examinations simultaneously at a time interval of more than 6 months (≥6).
Who cannot join
- ① The patient had no vascular risk factors；
- No clinical follow-up images;
- There are significant motion artifacts in the image, which cannot meet the
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
Chinese PLA General Hospital
Beijing, China, 100853
Chaobang Xie, 18798120676, chaobangxie@163.com
About this study
Cerebral small vessel disease (CSVD) accounts for 20% of ischemic strokes and is the most common cause of vascular cognitive impairment. Early identification of CSVD is critical for early intervention and improve clinical outcomes. Magnetic resonance imaging (MRI) may represent as a sensitive and robust tool to detect early changes in brain subtle structures and functions. The study is to investigate the comprehensive evaluation by using AI in early diagnosis and management of CSVD.
Read the detailed description
Cerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment, and other diseases, and its early quantitative evaluation can significantly improve patient prognosis. Magnetic resonance imaging (MRI) is an important method to evaluate the occurrence, development, and severity of CSVD. However, the diagnostic process lacks quantitative evaluation criteria and is limited by experience, which may easily lead to missed diagnoses and misdiagnoses. Based on the current technical challenges, subject development and upgrade of knowledge, to avoid the occurrence of adverse medical accidents, simplify the diagnostic process, artificial intelligence（AI） has become the alternative method of choice, by constructing training deep learning model,which can assist doctors in clinical decision-making to improve diagnosis effectiveness of CSCD detection and diagnosis.
- Conditions
- Cerebral Small Vessel Disease
- Being tested
- Artificial intelligence
- Keywords
- Cerebral small vessel disease, Artificial intelligence, Deep learning, Magnetic resonance imaging
- Medical subject headings
- Cerebral Small Vessel Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligenceDiagnostic test
Artificial intelligence (AI) tools developed through the training of large amounts of image data can assist with the analysis and interpretation of neuroimaging data of cerebral small vascular disease（CSVD）.
What is being measured
The primary outcome is the main question the study is designed to answer.
The performance of AI in lesion detection and diagnosis
The performance of AI in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.
Measured: 2 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Oct 2024
- Study start1 Nov 2024 (estimated)
- Primary completion1 Sep 2030 (estimated)
- Study completion1 Sep 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Cerebral Small Vessel DiseaseStudies of the same condition, open and under way.
- More trials run by Chinese PLA General HospitalThe sponsor's other registered studies.
- 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
- Cohort
- 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
- Xin Lou, MD/PhD, Study chair, Chinese PLA General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06667635
- Sponsor's protocol ID
- 2024-685
- Status last verified
- Sep 2024
- First submitted
- 22 Oct 2024
- Last updated
- 31 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 31 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Intelligent Analysis and Clinical Validation of Cerebral Small Vessel Disease on Magnetic Resonance Imaging：A Multi-center Study
- ClinicalTrials.gov ID
- NCT06667635
- Acronym / sponsor ID
- 2024-685
- Conditions
- Cerebral Small Vessel Disease
- Keywords
- Cerebral small vessel disease, Artificial intelligence, Deep learning, Magnetic resonance imaging
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Chinese PLA General HospitalUniversity, hospital or other
- Study start
- 1 Nov 2024 (estimated)
- Primary completion
- 1 Sep 2030 (estimated)
- Study completion
- 1 Sep 2030 (estimated)
- First posted
- 31 Oct 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Cerebral small vessel disease (CSVD) accounts for 20% of ischemic strokes and is the most common cause of vascular cognitive impairment. Early identification of CSVD is critical for early intervention and improve clinical outcomes. Magnetic resonance imaging (MRI) may represent as a sensitive and robust tool to detect early changes in brain subtle structures and functions. The study is to investigate the comprehensive evaluation by using AI in early diagnosis and management of CSVD.
Detailed description
Cerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment, and other diseases, and its early quantitative evaluation can significantly improve patient prognosis. Magnetic resonance imaging (MRI) is an important method to evaluate the occurrence, development, and severity of CSVD. However, the diagnostic process lacks quantitative evaluation criteria and is limited by experience, which may easily lead to missed diagnoses and misdiagnoses. Based on the current technical challenges, subject development and upgrade of knowledge, to avoid the occurrence of adverse medical accidents, simplify the diagnostic process, artificial intelligence（AI） has become the alternative method of choice, by constructing training deep learning model,which can assist doctors in clinical decision-making to improve diagnosis effectiveness of CSCD detection and diagnosis.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 40 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- This is a multicenter study with a total plan of 1000 patients, 500 from Chinese PLA General Hospital and 500 from other centers.
Key inclusion criteria (3 listed)
- ① Men and women age 40 years or older;
Key exclusion criteria (3 listed)
- ① The patient had no vascular risk factors；
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial intelligenceArtificial intelligence (AI) tools developed through the training of large amounts of image data can assist with the analysis and interpretation of neuroimaging data of cerebral small vascular disease（CSVD）. | Diagnostic test | – |
Primary outcome
The performance of AI in lesion detection and diagnosis
Time frame: 2 year
The performance of AI in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 Oct 2024.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Xin Lou, MD/PhD study chair
Chinese PLA General Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cerebral Small Vessel Disease, run by Chinese PLA General Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 31 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Chaobang Xie (18798120676, chaobangxie@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The performance of AI in lesion detection and diagnosis (time frame: 2 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 Oct 2024.