In vivo assessment of liver function, perfusion and fat distribution in the animal model by using MRI
In vivo assessment of liver function, perfusion and fat distribution in the animal model by using MRI
批准号:
447245555
负责人:
Professor Dr. Jürgen R. Reichenbach
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Research Units
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:
中文摘要
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英文摘要
Within the overarching goal of the research unit QuaLiPerF to gain a data-integrated, multi-scale understanding of the interplay between hepatic perfusion and function and its recovery after extended hepatectomy (ePHx), this project is devoted to experimental MRI investigations in rats. It aims to establish a comprehensive MR imaging toolbox for small animal imaging at 9.4T and to provide spatially resolved, multi-parametric quantitative in vivo information on liver size, function, and perfusion under various experimental conditions. The toolbox will be applied to scan rats before and after portal vein ligation (PVL) and partial hepatectomy. Animals are monitored longitudinally during regeneration. In addition, the effects of a fat diet on the different MRI parameters, used to characterize the liver status, will also be investigated longitudinally. The acquired MRI data serve to monitor and analyze the physiological adaptations induced by the diet, after PVL and during regeneration of the remnant liver after ePHx. Together with complementary experimental and clinical data contributed by the other projects within the research unit, they form an important source of information for comparison with the temporal changes predicted by the mathematical models, which are also developed in the corresponding projects of the research unit. The data collected in this project will be passed on to be integrated into models on different scales based on statistical approaches. Upon completion of the first funding period of the research unit, a substantial body of experimental in vivo data will be available, which together with the iterative computational modeling and data integration will allow a better prediction of the recovery of liver function.
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