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.
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).
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
This is a multicenter study with a total plan of 1000 patients, 500 from Chinese PLA General Hospital and 500 from other centers.
Cohort
Prospective
Artificial intelligence
Diagnostic testArtificial 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）.
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.
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