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Enabling accurate identification and quantification of brown adipose tissue mass by xenon enhanced computed tomography

Enabling accurate identification and quantification of brown adipose tissue mass by xenon enhanced computed tomography
通过氙增强计算机断层扫描能够准确识别和量化棕色脂肪组织块
批准号:
10052750
负责人:
Rosa Tamara Branca
金额:
$49.32万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-01 至 2022-08-31
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中文摘要
翻译
项目总结/摘要 在美国,超过36%的人口肥胖,9.4%的人患有糖尿病,其中大多数是2型糖尿病 由肥胖相关的胰岛素抵抗驱动。目前的抗肥胖策略已被证明主要是 我们迫切需要新的靶向疗法来阻止这一流行病。在基波 在这个层面上,肥胖是由于能量摄入和能量消耗之间的不平衡造成的。后者可以 由棕色脂肪组织(BAT)的活动调节,该组织不仅在能量方面发挥调节作用, 平衡,但也在葡萄糖稳态。因此,现在正在设计新的治疗方法, 将BAT作为治疗肥胖和糖尿病的目标。然而,这种发展的主要障碍是, 最重要的是能够准确地检测和量化BAT质量。目前的技术也 不敏感或缺乏区分该组织与白色脂肪组织的必要特异性。这是 尤其是在超重/肥胖受试者中-靶向BAT的介入治疗的目标人群。 拟议研究项目的目标是开发一种基于低剂量氙的新成像方法, 增强CT(XECT)可以检测BAT并准确测量其质量, 活动这一建议建立在我们的初步结果,其中我们已经表明,惰性和亲脂性 氙气可用作CT造影剂以检测和量化BAT质量。不管这些组织 产热能力、水合状态和葡萄糖摄取能力,在刺激产热活性时, 氙以足够高的浓度积累到BAT中,从而显著改变BAT的放射性密度。 组织,使BAT在CT图像中可见。 我们在这一应用中的目标是:a)表征BAT中氙摄取动力学作为组织的函数 在瘦的和肥胖的非人灵长类动物模型中的水合和产热效能; B)表征 并优化低剂量XECT方案,用于人体纵向研究;以及c)建立低剂量XECT方案, 剂量XECT可以正确识别BAT,其灵敏度和特异性高于18F-FDG-PET/CT, 广泛使用的BAT体积测量技术,使用活检作为基础事实。 XECT将能够准确定量一般成年人群中的BAT质量,同时提供 新的见解,发生在这个组织的形态变化,在肥胖症的发病。这个项目是 预期具有很高的影响力;这种新方法可以在标准PET/CT平台上轻松实现 并结合BAT的其他功能措施,通过减少部分体积来提高其准确性 方面的影响.对最佳可得技术的质量和活动进行准确的量化,预计将有助于更好地了解 由各种刺激和条件引起的这种组织的生长、进化和重塑。
英文摘要
PROJECT SUMMARY / ABSTRACT In the US, more than 36% of the population is obese and 9.4% has diabetes, most of which is type-2 diabetes driven by obesity-associated insulin resistance. Current anti-obesity strategies have been proven to be largely inadequate, and new-targeted therapies are desperately needed to stop this epidemic. At the fundamental level, obesity results from the imbalance between energy intake and energy expenditure. The latter can be regulated by the activity of brown adipose tissue (BAT), a tissue that plays a regulatory role not only in energy balance, but also in glucose homeostasis. As a result, new therapeutic approaches are now being devised to target BAT for the treatment of obesity and diabetes. However, a major roadblock to the development of such therapies is the ability to detect and quantify BAT mass accurately. Current techniques are either too insensitive, or lack the necessary specificity to differentiate this tissue from white adipose tissue. This is especially true in overweight/obese subjects - the target population for interventional therapies targeting BAT. The goal of the proposed research project is to develop a new imaging approach based on low-dose, xenon- enhanced CT (XECT) that can detect BAT and yield accurate measurements of its mass, independently of its activity. This proposal builds upon our preliminary results, in which we had shown that the inert and lipophilic gas xenon can be used as a CT contrast agent to detect and quantify BAT mass. Regardless of the tissue's thermogenic capacity, hydration status, and glucose uptake capacity, upon stimulation of thermogenic activity, xenon accumulates into BAT at a concentration high enough to significantly change the radiodensity of this tissue, making BAT visible in CT images. Our objectives in this application are: a) to characterize xenon uptake dynamics in BAT as a function of tissue hydration and thermogenic potency in lean and obese non human primates animal models; b) to characterize and optimize low-dose XECT protocols for use in longitudinal studies in humans; and c) to establish that low- dose XECT can correctly identify BAT with greater sensitivity and specificity than 18F-FDG-PET/CT, the most widely used technique for measurement of BAT volume, using biopsy as ground truth. XECT will enable accurate quantification of BAT mass in the general adult human population, while providing new insights into the morphological changes that occur in this tissue during the onset of obesity. This project is expected to have a high impact; this novel approach can be easily implemented on standard PET/CT platforms and combined with other functional measures of BAT to increase their accuracy by reducing partial volume effects. Accurate quantification of BAT mass and activity is expected to lead to a better understanding of the growth, evolution, and remodeling of this tissue resulting from various stimuli and conditions.
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Enabling accurate identification and quantification of brown adipose tissue mass by xenon enhanced computed tomography
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