Label-free imaging of metabolic parameters in animals and humans

动物和人类代谢参数的无标记成像

• 批准号: 471417917
• 负责人: Professor Dr. Vasilis Ntziachristos
• 金额: --
• 依托单位: Lehrstuhl für Biologische Bildgebung
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/471417917?language=en
• 关键词: Label; free; imaging; metabolic; parameters

Multispectral optoacoustic tomography (MSOT) enables label-free imaging of oxy- and deoxy-hemoglobin as an intrinsic tissue biosensor to resolve oxygen saturation and utilization as a metabolic indicator. Moreover, it images lipid distribution and water. Therefore, it has strong potential to provide dynamic measurements of cardio-metabolic status. However, MSOT is currently not optimized and not validated for metabolism studies.Our goal is to develop a deeper-reaching MSOT and confirm in-vivo MSOT assays for measuring tissue bioenergetics and lipid profiles in-vivo in the context of metabolic diseases. First, a new geometry for MSOT will be designed and combined with an extended wavelength range to improve the penetration depth and accuracy for hemoglobin and lipid imaging in human muscle, brown adipose tissue (BAT) and the vascular system – critical for confirming deep-reaching MSOT for the needs of the other sub-projects. Subsequently, this new MSOT ability will be used to provide metrics of oxidative metabolism, calculated as the time derivative of oxygen saturation and lipid utilization and composition in different tissue compartments. We will validate MSOT to reliably quantify subcutaneous and muscle fat in human volunteers and then explore the identification of BAT presence without the need of activation, by quantifying lipid and hemoglobin distributions in the supraclavicular region of healthy volunteers. Measurements will be contrasted to corresponding measurements by BMI and other clinical metrics. We aim to deliver a validated MSOT feature-set that quantifies local and intra-muscular lipid composition or BAT, enabling more accurate characterization compared to the current clinical standards.To validate MSOT-resolved lipid composition in vasculature, a localized spectroscopy MSOT test will be developed to measure and understand food intake and lipid digestion dynamics, as they relate to projects P1, P2, and P6. The test will be useful for identifying the dynamics of lipid digestion in different groups (e.g. athletes, other healthy volunteers, cardiovascular disease and diabetic patients) with the aim of combining this data with tissue composition and dynamic measurements (exercising muscle, BAT activation) to investigate correlations between obesity, BAT content, and lipid digestion.Finally, lipid/water will be correlated to hemoglobin/oxygenation signals using simulations, phantom and experimental measurements, including human and mouse data gathered in P1, P2 and P6. We will examine the performance of our computational tools and monitor against possible cross-talk between these two measurements at rest and in metabolically active tissues, resulting in a validated assay for studying lipid metabolism and hemodynamics in a label-free fashion in-vivo. The results of this sub-project will pave the way to utilize MSOT in the other sub-projects and more generally in cardiometabolic medicine as a confirmed and validated modality.

多光谱光声断层扫描 (MSOT) 能够将氧合血红蛋白和脱氧血红蛋白作为内在组织生物传感器进行无标记成像，以解析氧饱和度和利用率作为代谢指标。此外，它还能对脂质分布和水进行成像。 因此，它具有提供心脏代谢状态动态测量的巨大潜力。然而，MSOT 目前尚未针对代谢研究进行优化和验证。我们的目标是开发更深入的 MSOT 并确认体内 MSOT 测定，用于测量代谢疾病背景下的体内组织生物能和脂质谱。首先，将设计一种新的 MSOT 几何形状，并将其与扩展的波长范围相结合，以提高人体肌肉、棕色脂肪组织 (BAT) 和血管系统中血红蛋白和脂质成像的穿透深度和准确性，这对于确认深层次的 MSOT 以满足其他子项目的需求至关重要。随后，这种新的 MSOT 能力将用于提供氧化代谢指标，计算为不同组织区室中氧饱和度和脂质利用率和成分的时间导数。我们将验证 MSOT 是否能够可靠地量化人类志愿者的皮下脂肪和肌肉脂肪，然后通过量化健康志愿者锁骨上区域的脂质和血红蛋白分布，探索无需激活即可识别 BAT 存在的方法。测量结果将与 BMI 和其他临床指标的相应测量结果进行对比。我们的目标是提供经过验证的 MSOT 功能集，可量化局部和肌内脂质成分或 BAT，与当前的临床标准相比，能够实现更准确的表征。为了验证脉管系统中 MSOT 解析的脂质成分，将开发局部光谱 MSOT 测试来测量和了解食物摄入和脂质消化动态，因为它们与项目 P1、P2 和 P6 相关。该测试将有助于确定不同群体（例如运动员、其他健康志愿者、心血管疾病和糖尿病患者）的脂质消化动态，目的是将这些数据与组织成分和动态测量（锻炼肌肉、BAT 激活）相结合，以研究肥胖、BAT 含量和脂质消化之间的相关性。最后，脂质/水将与 使用模拟、模型和实验测量的血红蛋白/氧合信号，包括在 P1、P2 和 P6 中收集的人类和小鼠数据。我们将检查我们的计算工具的性能，并监测这两种测量在休息时和代谢活跃的组织中可能存在的串扰，从而形成一种经过验证的测定方法，用于以无标记的方式在体内研究脂质代谢和血流动力学。该子项目的结果将为在其他子项目中以及更广泛地在心脏代谢医学中使用 MSOT 作为一种经过确认和验证的方式铺平道路。