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Updated: Nov 6, 2025

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
Published on: June 16, 2020
BPV associated with imaging features of SSI on MRI
Yong Peng Yu1,2, Ya Li Zheng1, Lan Tan3
1Department of Neurology, Weihai Central Hospital Affiliated to Qingdao University, Weihai, China.
Blood pressure variability (BPV) is higher in patients with single small infarction (SSI). Increased day-to-day and visit-to-visit BPV are linked to small, deep brain lesions in SSI patients.
Area of Science:
- Neurology
- Cardiology
- Radiology
Background:
- Single small infarction (SSI) is a common finding on magnetic resonance imaging (MRI).
- Blood pressure variability (BPV) has been implicated in various cerebrovascular diseases.
- The relationship between BPV and imaging features of SSI requires further investigation.
Purpose of the Study:
- To investigate the association between blood pressure variability (BPV) and imaging characteristics of single small infarction (SSI) using MRI.
- To compare BPV in patients with SSI versus healthy controls.
- To explore how different SSI features (size, shape, location) correlate with BPV.
Main Methods:
- A retrospective study involving 205 patients with SSI and 120 healthy controls.
- Blood pressure was monitored daily during hospitalization (7-10 days).
- Day-to-day, visit-to-visit, and 24-hour BPV parameters were analyzed and compared between groups and subgroups based on lesion characteristics.
Main Results:
- Patients with SSI exhibited significantly higher 24-hour, day-to-day, and visit-to-visit BPV compared to controls.
- Small lacunar infarcts showed higher BPV than giant lacunar infarcts.
- Non-round and deep small lesions were associated with significantly higher BPV parameters.
Conclusions:
- Elevated BPV, particularly day-to-day and visit-to-visit measures, is associated with single small infarction (SSI).
- Specific imaging features of SSI, such as small size and deep location, correlate with increased BPV.
- BPV may serve as a potential biomarker for identifying patients at risk for SSI with specific characteristics.
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