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<https://discovery.ucl.ac.uk/id/eprint/10060068> <http://purl.org/dc/terms/title> "A Preclinical Ultrasound Method for the Assessment of Vascular Disease Progression in Murine Models"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10060068> <http://purl.org/ontology/bibo/abstract> "INTRODUCTION: The efficacy of preclinical ultrasound at providing a quantitative assessment of mouse models of vascular disease is relatively unknown. In this study, preclinical ultrasound was used in combination with a semi-automatic image processing method to track arterial distension alterations in mouse models of abdominal aortic aneurysm and atherosclerosis. METHODS: Longitudinal B-mode ultrasound images of the abdominal aorta were acquired using a preclinical ultrasound scanner. Arterial distension was assessed using a semi-automatic image processing algorithm to track vessel wall motion over the cardiac cycle. A standard, manual analysis method was applied for comparison. RESULTS: Mean arterial distension was significantly lower in abdominal aortic aneurysm mice between day 0 and day 7 post-onset of disease (p < 0.01) and between day 0 and day 14 (p < 0.001), while no difference was observed in sham control mice. Manual analysis detected a significant decrease (p < 0.05) between day 0 and day 14 only. Atherosclerotic mice showed alterations in arterial distension relating to genetic modification and diet. Arterial distension was significantly lower (p < 0.05) in Ldlr−/−(++/−−) mice fed high-fat western diet when compared with both wild type (++/++) mice and Ldlr−/−(++/−−) mice fed chow diet. The manual method did not detect a significant difference between these groups. CONCLUSIONS: Arterial distension can be used as an early marker for the detection of arterial disease in murine models. The semi-automatic analysis method provided increased sensitivity to differences between experimental groups when compared to the manual analysis method."^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10060068> <http://purl.org/dc/terms/date> "2019" .
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