Intelligent Analysis and Clinical Validation of Cerebral Small Vessel Disease on Magnetic Resonance Imaging：A Multi-center Study

N/ANot Yet RecruitingNCT06667635

Chinese PLA General Hospital1,000 enrolled

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.

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 Type

OBSERVATIONAL

Enrollment

1,000

Conditions

Cerebral Small Vessel Disease

Interventions

Eligibility

Sex: ALLMin age: 40 YearsHealthy volunteers:

Medical Language ↔ Plain English

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

Outcomes

Primary Outcomes

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.

Time frame: 2 year