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首页> 美国卫生研究院文献>Frontiers in Pediatrics >Investigating Cardiac Motion Patterns Using Synthetic High-Resolution 3D Cardiovascular Magnetic Resonance Images and Statistical Shape Analysis
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Investigating Cardiac Motion Patterns Using Synthetic High-Resolution 3D Cardiovascular Magnetic Resonance Images and Statistical Shape Analysis

机译：使用合成的高分辨率3D心血管磁共振图像和统计形状分析研究心脏运动模式

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Diagnosis of ventricular dysfunction in congenital heart disease is more and more based on medical imaging, which allows investigation of abnormal cardiac morphology and correlated abnormal function. Although analysis of 2D images represents the clinical standard, novel tools performing automatic processing of 3D images are becoming available, providing more detailed and comprehensive information than simple 2D morphometry. Among these, statistical shape analysis (SSA) allows a consistent and quantitative description of a population of complex shapes, as a way to detect novel biomarkers, ultimately improving diagnosis and pathology understanding. The aim of this study is to describe the implementation of a SSA method for the investigation of 3D left ventricular shape and motion patterns and to test it on a small sample of 4 congenital repaired aortic stenosis patients and 4 age-matched healthy volunteers to demonstrate its potential. The advantage of this method is the capability of analyzing subject-specific motion patterns separately from the individual morphology, visually and quantitatively, as a way to identify functional abnormalities related to both dynamics and shape. Specifically, we combined 3D, high-resolution whole heart data with 2D, temporal information provided by cine cardiovascular magnetic resonance images, and we used an SSA approach to analyze 3D motion per se. Preliminary results of this pilot study showed that using this method, some differences in end-diastolic and end-systolic ventricular shapes could be captured, but it was not possible to clearly separate the two cohorts based on shape information alone. However, further analyses on ventricular motion allowed to qualitatively identify differences between the two populations. Moreover, by describing shape and motion with a small number of principal components, this method offers a fully automated process to obtain visually intuitive and numerical information on cardiac shape and motion, which could be, once validated on a larger sample size, easily integrated into the clinical workflow. To conclude, in this preliminary work, we have implemented state-of-the-art automatic segmentation and SSA methods, and we have shown how they could improve our understanding of ventricular kinetics by visually and potentially quantitatively highlighting aspects that are usually not picked up by traditional approaches.
机译：先天性心脏病的心室功能不全的诊断越来越多地基于医学影像学，这使得可以研究异常的心脏形态和相关的异常功能。尽管2D图像的分析代表了临床标准，但是执行3D图像自动处理的新颖工具正变得可用，与简单的2D形态计量学相比，它提供了更详细和全面的信息。其中，统计形状分析（SSA）可以对大量复杂形状进行一致且定量的描述，以此作为检测新型生物标记物的方法，从而最终改善诊断和病理学理解。这项研究的目的是描述一种用于研究3D左心室形状和运动模式的SSA方法的实施，并在4名先天性修复的主动脉瓣狭窄患者和4名年龄匹配的健康志愿者的一小样本中对其进行测试，以证明其安全性。潜在。这种方法的优点是能够从视觉上和数量上与个体形态分开地分析特定于对象的运动模式，以识别与动力学和形状相关的功能异常。具体来说，我们将3D高分辨率全心数据与2D，电影心血管磁共振图像提供的时间信息相结合，并且我们使用了SSA方法来分析3D运动本身。这项初步研究的初步结果表明，使用这种方法，可以捕获舒张末期和收缩期末期心室形状的一些差异，但无法仅根据形状信息清楚地区分这两个队列。但是，对心室运动的进一步分析可以定性地确定两个人群之间的差异。此外，通过用少量主要成分描述形状和运动，该方法提供了一个全自动过程，以获得关于心脏形状和运动的视觉直观和数字信息，一旦在更大的样本量上得到验证，就可以轻松地将其整合到临床工作流程。总而言之，在这项初步工作中，我们实施了最先进的自动分割和SSA方法，并且我们展示了它们如何通过视觉和潜在地定量突出通常未发现的方面来改善我们对心室动力学的理解。通过传统方法。

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