Precise volumetry of human adipose tissue compartments by combining automatic post-processing algorithms and optimized MRI acquisition techniques

通过结合自动后处理算法和优化的 MRI 采集技术，对人体脂肪组织区室进行精确体积测定

• 批准号: 192749169
• 负责人: Professor Dr. Fritz Schick
• 金额: --
• 依托单位: Radiologische Universitätsklinik (Department)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2011
• 资助国家: 德国
• 起止时间: 2010-12-31 至 2015-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/192749169?language=en
• 关键词: Precise; volumetry; human; adipose; tissue; Precise; volumetry; human; adipose; tissue

During the last years multiple large-cohort studies proved a significant correlation between reduced insulin sensitivity and the volumes of some adipose tissue compartments of the human body. The reduced insulin sensitivity can lead to wide-spread diseases such as type 2 diabetes mellitus and the metabolic syndrome which can lead to concomitant diseases such as cardiac arrest, stroke, blindness or renal insufficiency. Therefore, a precise and accurate volumetric assessment of adipose tissue compartments of the body is desirable for risk estimation and for monitoring of lifestyle interventions. Based on our preliminary work on automatic volumetry of major adipose tissue compartments, new reliable procedures for assessment of fatty tissue in the presence of severe signal inhomogeneities (caused by phased-array coils or RF-interferences) are to be developed in the proposed project. In contrast to many other approaches we opt to achieve this by simultaneous optimizing of both, imaging and evaluation techniques. Furthermore, small-volume adipose tissue compartments in the vicinity of blood vessels or the moving epi-/pericardial compartments are to be quantified reliably, since their role in future studies of the metabolism is expected to be highly significant. New methods with high selectivity to fat using adapted phase unwrapping and acceleration of data acquisition by modern 'compressed sensing' techniques are to be developed.

在过去的几年中，多项大型研究证明了胰岛素敏感性降低与人体某些脂肪组织室的体积之间存在显着相关性。降低的胰岛素敏感性会导致广泛的疾病，例如2型糖尿病和代谢综合征，这些疾病可能导致伴随性疾病，例如心脏骤停，中风，失明或肾脏不足。因此，需要对人体的脂肪组织室进行精确，准确的体积评估，以估计风险估计和监测生活方式干预措施。基于我们对主要脂肪组织室自动体积的初步工作，在拟议的项目中将开发出严重信号不均匀性（由相分子阵列线圈或RF互动引起的严重信号不均匀性（由相分子阵列线圈或RF互动引起的），用于评估脂肪组织的新的可靠程序。与许多其他方法相反，我们选择通过同时优化成像和评估技术来实现这一目标。此外，在血管附近或移动的表皮室中的小体积脂肪组织室可靠地量化，因为预计它们在代谢的未来研究中的作用将非常重要。使用改编的相位解开和通过现代“压缩传感”技术对数据采集进行加速的新方法，将开发出来。