Abstract
Monitoring hemodynamic responses in the rodent stroke model is important in the study of ischemic stroke. However, it is hard for a single imaging modality to comprehensively explore these changes. In this study, we implemented laser speckle imaging (LSI) and visible-light optical coherence tomography (Vis-OCT) to detect cerebral blood flow (CBF), angiography and oxygen saturation (sO2) in the mouse model of distal middle cerebral artery occlusion (dMCAO). LSI provides full-field, real-time cerebral blood flow (CBF) map to guide the Vis-OCT imaging. Vis-OCT offers angiography and sO2 measurements. The results showed the detailed CBF and vasculature changes before and after dMCAO. After dMCAO, sO2 changed little in arteries and arterioles, while sO2 decreased in veins and venules. We also showed that larger veins had a higher decrease in sO2 value in consecutive vein branches after dMCAO. It is suggested that the combination of LSI/Vis-OCT provides a promising tool for the rodent stroke model study.
Original language | English (US) |
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Title of host publication | 8th International IEEE EMBS Conference on Neural Engineering, NER 2017 |
Publisher | IEEE Computer Society |
Pages | 62-65 |
Number of pages | 4 |
ISBN (Electronic) | 9781538619162 |
DOIs | |
State | Published - Aug 10 2017 |
Event | 8th International IEEE EMBS Conference on Neural Engineering, NER 2017 - Shanghai, China Duration: May 25 2017 → May 28 2017 |
Publication series
Name | International IEEE/EMBS Conference on Neural Engineering, NER |
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ISSN (Print) | 1948-3546 |
ISSN (Electronic) | 1948-3554 |
Other
Other | 8th International IEEE EMBS Conference on Neural Engineering, NER 2017 |
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Country/Territory | China |
City | Shanghai |
Period | 5/25/17 → 5/28/17 |
Funding
*Resrach supported by the NIH grants R24EY022883, DP3DK108248, R01EY026078; NSF grants CBET-1055379, DBI-1353952; Chinese program of introducing talents to Universities (111 Project, No. B08020); Q. L. is also supported by the China Scholarship Council (201406230188); S. T. is also supported by the NSFC grant (No. 61371018).
ASJC Scopus subject areas
- Artificial Intelligence
- Mechanical Engineering