Novel Computed Tomography (CT) Imaging Biomarkers in Older Adults for Predicting Adverse Geriatric Health Outcomes

基于血液的生物标记物已被广泛用于研究导致衰老的各种代谢途径， 包括能量代谢、慢性炎症、细胞衰老和内皮功能。就像血一样- 衍生生物标记物，基于成像的生物标记物可以被评估为潜在的预测衰老结果的指标。 对于非神经衰老的研究，来自计算机断层扫描(CT)的生物标记物提供了巨大的希望。 扫描仪技术和图像处理的最新进展意味着大多数CT检查可以 在不到一分钟的时间内获得，降低了参与者的负担。此外，辐射剂量已经降低。 扫描仪内和扫描仪间的可变性也有所改善。同时，机器学习工具允许 自动图像处理和分割，提高了图像分析的效率，减少了偏差。 由于这些原因，CT越来越多地被用于研究骨骼肌和脂肪组织。 在CT上，肌肉数量通常是通过横截面积(CSA)来测量的。肌肉质量是传统上的 以骨骼肌密度(SMD)和肌间脂肪组织(IMAT)横截面积量化。在……里面 除了是肌肉质量的衡量标准外，IMAT还可以被认为是脂肪量的衡量标准。我们 最近开发并验证了一种自动机器学习工具，以确定传统的CT测量 肌肉和脂肪组织的数量和质量。为了更好地表征组织质量，我们还应用了 CT图像上肌肉组织的“放射状”纹理分析。质地分析指的是对 图像体素之间的相互关系，并提供组织异质性的测量。据我们所知，这 这项技术从未被应用于社区流行病学研究的CT图像。我们建议 为了将这些基于CT的肌肉和脂肪组织评估与重要的老年结果联系起来，重点是 髋部和其他骨折以及摔倒、体能和力量。我们将完成这些工作 MROS中存档CT图像的分析(一项关于老年男性健康老龄化的前瞻性队列研究 特别关注骨质疏松症)和健康ABC(非残疾黑人和白人的前瞻性队列研究 老年人)。腹部CT图像是在美国MRO男性基线检查时收集的 (2000-2年度为3700人)、香港MRO男性(2001-3年度为400人)和Health ABC(1997-8年度为3000人)。健康状况 美国广播公司还收集了大腿中部的CT图像。在Health ABC中，大腿中部和腹部的CT图像 五年后在一个子集中重复(2000-3年为N~600)。我们将增加三个目标：1)检验假设 腹部和大腿中部较大的肌肉和脂肪组织异质性特征与 增加髋部和其他骨折的风险，2)检验肌肉和脂肪组织异质性更大的假说 腹部和大腿中部的特征与力量较弱和身体表现不佳有关 (步行速度和椅子站立)；它们随着时间的推移而下降；以及摔倒的风险，以及3)表征 大腿中部肌肉和脂肪组织的异质性特征超过6年。

Blood-based biomarkers have been widely used in studying various metabolic pathways contributing to aging, including energy metabolism, chronic inflammation, cellular senescence, and endothelial function. Like blood- derived biomarkers, imaging-based biomarkers can be evaluated as potential predictors of aging outcomes. For study of non-neurologic aging, biomarkers derived from computed tomography (CT) offer great promise. Recent advances in scanner technology and image processing mean that most CT examinations can be obtained in less than one minute, lowering participant burden. In addition, radiation doses have been lowered and the intra- and inter-scanner variability has improved. In parallel, machine learning tools allow for automated image processing and segmentation, increasing efficiency of image analysis, and reducing bias. For these reasons, CT is increasingly being used to study skeletal muscle and adipose tissue. On CT, muscle quantity is typically measured by cross-sectional area (CSA). Muscle quality is traditionally quantified by skeletal muscle density (SMD) and intermuscular adipose tissue (IMAT) cross-sectional area. In addition to being a measure of muscle quality, IMAT may be considered as a measure of fat quantity. We recently developed and validated an automated machine learning tool to determine traditional CT measures of muscle and adipose tissue quantity and quality. To better characterize tissue quality, we have also applied "radiomic" texture analysis to muscle tissue on CT images. Texture analysis refers to the quantification of image voxel inter-relationships and provides a measure of tissue heterogeneity. To our knowledge, this technique has never been applied to CT images from community-based epidemiological studies. We propose to relate these CT-based assessments of muscle and adipose tissues to important geriatric outcomes, focusing on hip and other fractures as well as falls, physical performance, and strength. We will complete these analyses on archived CT images in MrOS (a prospective cohort study of healthy aging in older men, with a particular focus on osteoporosis) and Health ABC (a prospective cohort study of non-disabled Black and White older adults). Abdominal CT images were collected at the baseline exam for MrOS men in the United States (N~3700 in 2000-2), MrOS men in Hong Kong (N~400 in 2001-3), and Health ABC (N~3000 in 1997-8). Health ABC also collected CT images at the mid-thigh. In Health ABC, mid-thigh and abdominal CT images were repeated in a subset five years later (N~600 in 2000-3). We will add three aims: 1) test the hypothesis that that greater muscle and fat tissue heterogeneity features at the abdomen and mid-thigh are associated with increased risk of hip and other fractures, 2) test the hypothesis greater muscle and fat tissue heterogeneity features at the abdomen and mid-thigh are associated with lower strength and poor physical performance (walking speed and chair stands); their decline over time; and risk of falls, and 3) characterize changes in muscle and fat tissue heterogeneity features at the mid-thigh over 6 years.