Model-based assessment of cardiac adipose tissue volume and distribution

项目摘要： 肥胖仍然是我们这个时代最重要的健康问题之一，是一个重大的风险 心血管疾病的因素。一层称为心外膜脂肪组织（EAT）的脂肪层形成于 心肌和心包脏层。此外，心包脂肪组织（PAT）形成之间的 脏层和壁层心包。这种结合的脂肪存款，心脏脂肪组织（CAT），直接 影响冠状动脉疾病的发展。因此，测量的体积和分布 CAT可作为冠心病的标志物，并已成为心血管风险的重要任务 考核 心脏磁共振成像（MRI）可以提供CAT的三维（3D）评估， 但是它昂贵、耗时，并且仅在大型机构中可用。超声心动图是安全的， 实时、廉价，并且还可用于量化心脏结构和功能。这个目标 项目是使用实时超声心动图和射频（RF）的先进处理， 心脏MRI将用于构建表面图， 脂肪的3D模型将作为超声心动图融合的基础。脂肪在 然后超声心动图将用于扭曲模型以匹配超声中存在的脂肪 图像，如通过处理RF信号所识别的。充分利用 磁共振成像和超声心动图有可能产生一个广泛使用和更便宜的测量 CAT体积是冠状动脉疾病和心血管风险的潜在标志物。 我们将在心脏MRI中手动分割左心室、右心室和CAT层 扫描。分割的脂肪将用于创建CAT的平均表面图和3D模型， 被纳入一个开源的“平均”心脏模型。图中确定的心室轮廓 心脏MRI将用于对准超声图像平面并将其与模型融合。该步骤 将通过将超声心动图图像中识别的左心室轮廓与 核磁共振的结果接下来，短轴2D超声心动图图像序列中的CAT将被 使用原始射频信号的频谱分析进行定位。它将用于引导变形 的3D模型，以匹配在超声心动图中识别的脂肪，从而产生的体积和分布， 每个个体的CAT。该项目的成果将是一套工具，仅基于超声波， 它可用于测量CAT体积，并可能提供冠状动脉疾病的标志物 和心血管风险。

Project Summary: Obesity continues to be one of the most important health issues of our time and is a significant risk factor for cardiovascular disease. A layer of fat called epicardial adipose tissue (EAT) forms between the myocardium and visceral pericardium. In addition, pericardial adipose tissue (PAT) forms between the visceral and parietal pericardium. This combined fat deposit, the cardiac adipose tissue (CAT), directly influences the development of coronary artery disease. Therefore, measuring the volume and distribution of CAT can be a marker for coronary artery disease and has become an important task for cardiovascular risk assessment. Cardiac magnetic resonance imaging (MRI) can provide three-dimensional (3D) assessment of CAT, but it is expensive, time-consuming, and is only available at large institutions. Echocardiography is safe, real-time, inexpensive, and can also be used to quantify cardiac structure and function. The goal of this project is to use real-time echocardiography and advanced processing of the radiofrequency (RF) ultrasound signals for volumetric assessment of CAT. Cardiac MRI will be used to build a surface map and 3D model of the fat that will serve as the foundation for fusion of the echocardiography. The fat identified in the echocardiography will then be used to warp the model to match the fat present in the ultrasound images, as identified through processing of the RF signals. Leveraging the specific individual strengths of MRI and echocardiography has the potential to yield a widely available and less expensive measurement system for CAT volume, a potential marker for coronary artery disease and cardiovascular risk. We will manually segment the left ventricle, right ventricle, and the layer of CAT in the cardiac MRI scans. The segmented fat will be used to create an average surface map and 3D model of the CAT that will be incorporated into an open-source, “average” heart model. The contours from the ventricles identified in the cardiac MRI will be used to align the ultrasound image planes and fuse them with the model. This step will be performed by registering the left-ventricular contours identified in the echocardiography images with those from the MRI. Next, the CAT in a sequence of short-axis 2D echocardiographic images will be localized using spectral analysis of the raw radiofrequency signals. It will be used to guide the deformation of the 3D model to match the fat identified in the echocardiography, resulting in a volume and distribution of CAT in each individual subject. The outcome of the project will be a set of tools, based on ultrasound alone, which can be used to measure CAT volume and potentially provide a marker for coronary artery disease and cardiovascular risk.