Intelligent Analysis and Clinical Validation of Cerebral Small Vessel Disease on Magnetic Resonance Imaging：A Multi-center Study
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial intelligence.
- Who it may be relevant to
- Registry conditions: Cerebral Small Vessel Disease. Basic parameters: from 40 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
Interventions
- Diagnostic test Artificial intelligence
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）.
Primary outcome measures
- The performance of AI in lesion detection and diagnosis [Time frame: 2 year]
Eligibility criteria
Inclusion criteria
- 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).
Exclusion criteria
- 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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Chinese PLA General Hospital — Beijing
Identifiers
NCT: NCT06667635 · 2024-685