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）.
Study 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. 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.
Eligibility
Sex
ALL
Min age
40 Years
Max age
—
Healthy volunteers
Accepted
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
Primary outcome measure(s)
The performance of AI in lesion detection and diagnosis — 2 year The performance of AI in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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