Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment

Background and Purpose�Chronic hypoperfusion in the mouse brain has been suggested to mimic aspects of vascular cognitive impairment, such as white matter damage. Although this model has attracted attention, our group has struggled to generate a reliable cognitive and pathological phenotype. This...

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Main Authors: Boehm-Sturm, Philipp, Füchtemeier, Martina, Foddis, Marco, Mueller, Susanne, Trueman, Rebecca C., Zille, Marietta, Rinnenthal, Jan Leo, Kypraios, Theodore, Shaw, Laurence, Dirnagl, Ulrich, Farr, Tracy D.
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Published: American Heart Association 2017
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Online Access:https://eprints.nottingham.ac.uk/39844/
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author Boehm-Sturm, Philipp
Füchtemeier, Martina
Foddis, Marco
Mueller, Susanne
Trueman, Rebecca C.
Zille, Marietta
Rinnenthal, Jan Leo
Kypraios, Theodore
Shaw, Laurence
Dirnagl, Ulrich
Farr, Tracy D.
author_facet Boehm-Sturm, Philipp
Füchtemeier, Martina
Foddis, Marco
Mueller, Susanne
Trueman, Rebecca C.
Zille, Marietta
Rinnenthal, Jan Leo
Kypraios, Theodore
Shaw, Laurence
Dirnagl, Ulrich
Farr, Tracy D.
author_sort Boehm-Sturm, Philipp
building Nottingham Research Data Repository
collection Online Access
description Background and Purpose�Chronic hypoperfusion in the mouse brain has been suggested to mimic aspects of vascular cognitive impairment, such as white matter damage. Although this model has attracted attention, our group has struggled to generate a reliable cognitive and pathological phenotype. This study aimed to identify neuroimaging biomarkers of brain pathology in aged, more severely hypoperfused mice. Methods�We used magnetic resonance imaging to characterize brain degeneration in mice hypoperfused by refining the surgical procedure to use the smallest reported diameter microcoils (160 ?m). Results�Acute cerebral blood flow decreases were observed in the hypoperfused group that recovered over 1 month and coincided with arterial remodeling. Increasing hypoperfusion resulted in a reduction in spatial learning abilities in the water maze that has not been previously reported. We were unable to observe severe white matter damage with histology, but a novel approach to analyze diffusion tensor imaging data, graph theory, revealed substantial reorganization of the hypoperfused brain network. A logistic regression model from the data revealed that 3 network parameters were particularly efficient at predicting group membership (global and local efficiency and degrees), and clustering coefficient was correlated with performance in the water maze. Conclusions�Overall, these findings suggest that, despite the autoregulatory abilities of the mouse brain to compensate for a sudden decrease in blood flow, there is evidence of change in the brain networks that can be used as neuroimaging biomarkers to predict outcome.
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spelling nottingham-398442020-05-04T18:31:14Z https://eprints.nottingham.ac.uk/39844/ Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment Boehm-Sturm, Philipp Füchtemeier, Martina Foddis, Marco Mueller, Susanne Trueman, Rebecca C. Zille, Marietta Rinnenthal, Jan Leo Kypraios, Theodore Shaw, Laurence Dirnagl, Ulrich Farr, Tracy D. Background and Purpose�Chronic hypoperfusion in the mouse brain has been suggested to mimic aspects of vascular cognitive impairment, such as white matter damage. Although this model has attracted attention, our group has struggled to generate a reliable cognitive and pathological phenotype. This study aimed to identify neuroimaging biomarkers of brain pathology in aged, more severely hypoperfused mice. Methods�We used magnetic resonance imaging to characterize brain degeneration in mice hypoperfused by refining the surgical procedure to use the smallest reported diameter microcoils (160 ?m). Results�Acute cerebral blood flow decreases were observed in the hypoperfused group that recovered over 1 month and coincided with arterial remodeling. Increasing hypoperfusion resulted in a reduction in spatial learning abilities in the water maze that has not been previously reported. We were unable to observe severe white matter damage with histology, but a novel approach to analyze diffusion tensor imaging data, graph theory, revealed substantial reorganization of the hypoperfused brain network. A logistic regression model from the data revealed that 3 network parameters were particularly efficient at predicting group membership (global and local efficiency and degrees), and clustering coefficient was correlated with performance in the water maze. Conclusions�Overall, these findings suggest that, despite the autoregulatory abilities of the mouse brain to compensate for a sudden decrease in blood flow, there is evidence of change in the brain networks that can be used as neuroimaging biomarkers to predict outcome. American Heart Association 2017-01-09 Article PeerReviewed Boehm-Sturm, Philipp, Füchtemeier, Martina, Foddis, Marco, Mueller, Susanne, Trueman, Rebecca C., Zille, Marietta, Rinnenthal, Jan Leo, Kypraios, Theodore, Shaw, Laurence, Dirnagl, Ulrich and Farr, Tracy D. (2017) Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment. Stroke, 48 (1). pp. 1-9. ISSN 1524-4628 biomarkers diffusion tensor imaging hypoperfusion magnetic resonance imaging mouse neuroimaging vascular cognitive impairment http://stroke.ahajournals.org/content/early/2017/01/09/STROKEAHA.116.014394 doi:10.1161/STROKEAHA.116.014394 doi:10.1161/STROKEAHA.116.014394
spellingShingle biomarkers
diffusion tensor imaging
hypoperfusion
magnetic resonance imaging
mouse
neuroimaging
vascular cognitive impairment
Boehm-Sturm, Philipp
Füchtemeier, Martina
Foddis, Marco
Mueller, Susanne
Trueman, Rebecca C.
Zille, Marietta
Rinnenthal, Jan Leo
Kypraios, Theodore
Shaw, Laurence
Dirnagl, Ulrich
Farr, Tracy D.
Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
title Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
title_full Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
title_fullStr Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
title_full_unstemmed Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
title_short Neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
title_sort neuroimaging biomarkers predict brain structural connectivity change in a mouse model of vascular cognitive impairment
topic biomarkers
diffusion tensor imaging
hypoperfusion
magnetic resonance imaging
mouse
neuroimaging
vascular cognitive impairment
url https://eprints.nottingham.ac.uk/39844/
https://eprints.nottingham.ac.uk/39844/
https://eprints.nottingham.ac.uk/39844/