Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation
Abstract Background Local aortic pulse wave velocity (PWV) is a measure for vascular stiffness and has a predictive value for cardiovascular events. Ultra high field CMR scanners allow the quantification of local PWV in mice, however these systems are yet unable to monitor the distribution of local...
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doaj-bc4435aac90446cf8db5f06006c93c6a2020-11-24T21:53:03ZengBMCJournal of Cardiovascular Magnetic Resonance1532-429X2017-10-0119111010.1186/s12968-017-0382-2Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentationVolker Herold0Stefan Herz1Patrick Winter2Fabian Tobias Gutjahr3Kristina Andelovic4Wolfgang Rudolf Bauer5Peter Michael Jakob6Department of Experimental Physics, University of WürzburgComprehensive Heart Failure Center/Deutsches Zentrum für Herzinsuffizienz, University of WürzburgDepartment of Experimental Physics, University of WürzburgDepartment of Experimental Physics, University of WürzburgDepartment of Internal Medicine I, University Hospital WürzburgDepartment of Internal Medicine I, University Hospital WürzburgDepartment of Experimental Physics, University of WürzburgAbstract Background Local aortic pulse wave velocity (PWV) is a measure for vascular stiffness and has a predictive value for cardiovascular events. Ultra high field CMR scanners allow the quantification of local PWV in mice, however these systems are yet unable to monitor the distribution of local elasticities. Methods In the present study we provide a new accelerated method to quantify local aortic PWV in mice with phase-contrast cardiovascular magnetic resonance imaging (PC-CMR) at 17.6 T. Based on a k-t BLAST (Broad-use Linear Acquisition Speed-up Technique) undersampling scheme, total measurement time could be reduced by a factor of 6. The fast data acquisition enables to quantify the local PWV at several locations along the aortic blood vessel based on the evaluation of local temporal changes in blood flow and vessel cross sectional area. To speed up post processing and to eliminate operator bias, we introduce a new semi-automatic segmentation algorithm to quantify cross-sectional areas of the aortic vessel. The new methods were applied in 10 eight-month-old mice (4 C57BL/6J-mice and 6 ApoE (−/−)-mice) at 12 adjacent locations along the abdominal aorta. Results Accelerated data acquisition and semi-automatic post-processing delivered reliable measures for the local PWV, similiar to those obtained with full data sampling and manual segmentation. No statistically significant differences of the mean values could be detected for the different measurement approaches. Mean PWV values were elevated for the ApoE (−/−)-group compared to the C57BL/6J-group (3.5 ± 0.7 m/s vs. 2.2 ± 0.4 m/s, p < 0.01). A more heterogeneous PWV-distribution in the ApoE (−/−)-animals could be observed compared to the C57BL/6J-mice, representing the local character of lesion development in atherosclerosis. Conclusion In the present work, we showed that k-t BLAST PC-MRI enables the measurement of the local PWV distribution in the mouse aorta. The semi-automatic segmentation method based on PC-CMR data allowed rapid determination of local PWV. The findings of this study demonstrate the ability of the proposed methods to non-invasively quantify the spatial variations in local PWV along the aorta of ApoE (−/−)-mice as a relevant model of atherosclerosis.http://link.springer.com/article/10.1186/s12968-017-0382-2Pulse wave velocityMagnetic resonance imagingPhase contrastApoE (−/−) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Volker Herold Stefan Herz Patrick Winter Fabian Tobias Gutjahr Kristina Andelovic Wolfgang Rudolf Bauer Peter Michael Jakob |
spellingShingle |
Volker Herold Stefan Herz Patrick Winter Fabian Tobias Gutjahr Kristina Andelovic Wolfgang Rudolf Bauer Peter Michael Jakob Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation Journal of Cardiovascular Magnetic Resonance Pulse wave velocity Magnetic resonance imaging Phase contrast ApoE (−/−) |
author_facet |
Volker Herold Stefan Herz Patrick Winter Fabian Tobias Gutjahr Kristina Andelovic Wolfgang Rudolf Bauer Peter Michael Jakob |
author_sort |
Volker Herold |
title |
Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation |
title_short |
Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation |
title_full |
Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation |
title_fullStr |
Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation |
title_full_unstemmed |
Assessment of local pulse wave velocity distribution in mice using k-t BLAST PC-CMR with semi-automatic area segmentation |
title_sort |
assessment of local pulse wave velocity distribution in mice using k-t blast pc-cmr with semi-automatic area segmentation |
publisher |
BMC |
series |
Journal of Cardiovascular Magnetic Resonance |
issn |
1532-429X |
publishDate |
2017-10-01 |
description |
Abstract Background Local aortic pulse wave velocity (PWV) is a measure for vascular stiffness and has a predictive value for cardiovascular events. Ultra high field CMR scanners allow the quantification of local PWV in mice, however these systems are yet unable to monitor the distribution of local elasticities. Methods In the present study we provide a new accelerated method to quantify local aortic PWV in mice with phase-contrast cardiovascular magnetic resonance imaging (PC-CMR) at 17.6 T. Based on a k-t BLAST (Broad-use Linear Acquisition Speed-up Technique) undersampling scheme, total measurement time could be reduced by a factor of 6. The fast data acquisition enables to quantify the local PWV at several locations along the aortic blood vessel based on the evaluation of local temporal changes in blood flow and vessel cross sectional area. To speed up post processing and to eliminate operator bias, we introduce a new semi-automatic segmentation algorithm to quantify cross-sectional areas of the aortic vessel. The new methods were applied in 10 eight-month-old mice (4 C57BL/6J-mice and 6 ApoE (−/−)-mice) at 12 adjacent locations along the abdominal aorta. Results Accelerated data acquisition and semi-automatic post-processing delivered reliable measures for the local PWV, similiar to those obtained with full data sampling and manual segmentation. No statistically significant differences of the mean values could be detected for the different measurement approaches. Mean PWV values were elevated for the ApoE (−/−)-group compared to the C57BL/6J-group (3.5 ± 0.7 m/s vs. 2.2 ± 0.4 m/s, p < 0.01). A more heterogeneous PWV-distribution in the ApoE (−/−)-animals could be observed compared to the C57BL/6J-mice, representing the local character of lesion development in atherosclerosis. Conclusion In the present work, we showed that k-t BLAST PC-MRI enables the measurement of the local PWV distribution in the mouse aorta. The semi-automatic segmentation method based on PC-CMR data allowed rapid determination of local PWV. The findings of this study demonstrate the ability of the proposed methods to non-invasively quantify the spatial variations in local PWV along the aorta of ApoE (−/−)-mice as a relevant model of atherosclerosis. |
topic |
Pulse wave velocity Magnetic resonance imaging Phase contrast ApoE (−/−) |
url |
http://link.springer.com/article/10.1186/s12968-017-0382-2 |
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