QUANTITATIVE IMAGE ANALYSIS TECHNIQUES FOR STUDIES OF AGING PHENOTYPES AND AGE-RELATED DISEASES

 描述(申请人提供)：组织鉴定和量化在衰老和老年相关疾病的研究中发挥着重要作用。例如，脂肪在人体内的积累及其随年龄增长的区域分布与2型糖尿病和心血管疾病有关。肌肉成分的变化与肌肉力量下降、衰老导致的活动能力下降或肌肉骨骼疾病密切相关。特别有趣的是对形态描述符的纵向变化的分析，这对于 研究衰老过程，诊断和预防与年龄相关的疾病。医学成像因其非侵入性和产生多维信息而成为估测人体成分的主要工具。如今，MRI和CT采集是临床试验的核心组成部分。收集了丰富的影像数据，但这些丰富的信息并没有得到充分的利用。因此，研究可重复性、可用于大规模临床试验的组织量化图像分析技术具有特别重要的意义。这项工作的技术假设是，定量图像处理可以稳健而准确地分割、配准和融合来自现代MRI和CT成像的身体成分数据。这一建议的中心假设是，临床成像上的定性身体成分表型将区分健康的个体和不健康的个体。我们的工作目的是为腹部和下肢的图像分析提供基础，并研究身体形态变化与年龄相关病理的关系。我们将在医学图像计算的最新进展的基础上，在临床CT和MRI扫描中分割肌肉、区域脂肪组织和骨骼。我们还将开发图像配准程序，以实现对象内和对象间的对应，并有效利用在临床试验中收集的多模式和多时间成像数据提供的信息(目标1)。在这些方法被开发出来后，我们将解决这样的假设，即临床成像的定量使用可以提高年龄相关病理学的预后准确性(AIM2)。

 DESCRIPTION (provided by applicant): Tissue identification and quantification plays a significant role in the study of aging and age-related diseases. For example, the accumulation of fat in the human body and its regional distribution with aging is associated with type 2 diabetes and cardiovascular diseases. Changes in muscle composition are strongly linked to decline of muscle strength, decreased mobility caused by aging, or musculoskeletal disorders. Especially interesting is analysis of longitudinal changes of morphometric descriptors that is significant for studying the aging process and for the diagnosis and prevention of age-related diseases. Medical imaging has emerged as a major tool for estimation of body composition mainly due to being non- invasive and producing multi-dimensional information. Nowadays MRI and CT acquisition is a central component of clinical trials. An abundance of imaging data is collected, but this wealth of information has not been utilized to full extent. Therefore research on image analysis techniques for tissue quantification that are reproducible and can be used on large-scale clinical trials is of particular importance. The technical hypothesis of this work is that quantitative image processing can robustly and accurately segment, register, and fuse body composition data from modern MRI and CT imaging. The central hypothesis of this proposal is that qualitative body composition phenotypes on clinical imaging will differentiate individuals who are healthy versus those who are not. The goal of our work is to provide a foundation for image analysis of the abdomen and lower extremities and to study the relationship between body morphological changes and age-related pathologies. We will build upon recent advances in medical image computing to segment muscle, regional adipose tissue, and bone in clinical CT and MRI scans. We will also develop image registration procedures to achieve intra- and inter-subject correspondence and make efficient use of information provided by multi-modal and multi-temporal imaging data collected in clinical trials (aim 1). After these methods have been developed, we will address the hypothesis that quantitative use of clinical imaging can increase the prognostic accuracy of age-related pathologies (aim2).