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Multiparametric, Longitudinal Optical Coherence Tomography Imaging Reveals Acute Injury and Chronic Recovery in Experimental Ischemic Stroke

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Title
Multiparametric, Longitudinal Optical Coherence Tomography Imaging Reveals Acute Injury and Chronic Recovery in Experimental Ischemic Stroke
Published in
PLOS ONE, August 2013
DOI 10.1371/journal.pone.0071478
Pubmed ID
Authors

Vivek J. Srinivasan, Emiri T. Mandeville, Anil Can, Francesco Blasi, Mihail Climov, Ali Daneshmand, Jeong Hyun Lee, Esther Yu, Harsha Radhakrishnan, Eng H. Lo, Sava Sakadžić, Katharina Eikermann-Haerter, Cenk Ayata

Abstract

Progress in experimental stroke and translational medicine could be accelerated by high-resolution in vivo imaging of disease progression in the mouse cortex. Here, we introduce optical microscopic methods that monitor brain injury progression using intrinsic optical scattering properties of cortical tissue. A multi-parametric Optical Coherence Tomography (OCT) platform for longitudinal imaging of ischemic stroke in mice, through thinned-skull, reinforced cranial window surgical preparations, is described. In the acute stages, the spatiotemporal interplay between hemodynamics and cell viability, a key determinant of pathogenesis, was imaged. In acute stroke, microscopic biomarkers for eventual infarction, including capillary non-perfusion, cerebral blood flow deficiency, altered cellular scattering, and impaired autoregulation of cerebral blood flow, were quantified and correlated with histology. Additionally, longitudinal microscopy revealed remodeling and flow recovery after one week of chronic stroke. Intrinsic scattering properties serve as reporters of acute cellular and vascular injury and recovery in experimental stroke. Multi-parametric OCT represents a robust in vivo imaging platform to comprehensively investigate these properties.

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Geographical breakdown

Country Count As %
United States 3 3%
Unknown 97 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 25%
Student > Ph. D. Student 20 20%
Professor > Associate Professor 7 7%
Student > Doctoral Student 7 7%
Student > Master 5 5%
Other 20 20%
Unknown 16 16%
Readers by discipline Count As %
Engineering 22 22%
Medicine and Dentistry 17 17%
Neuroscience 10 10%
Physics and Astronomy 8 8%
Agricultural and Biological Sciences 8 8%
Other 14 14%
Unknown 21 21%