Precision Cardiac CT: Development of a Computational Platform for Optimizing Imaging

精密心脏 CT：开发优化成像的计算平台

• 批准号: 9240231
• 负责人: Ehsan Samei
• 金额: $ 69.26万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-15 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9240231
• 关键词: 4D Imaging; Address; Affect; Algorithms; Anatomy; Architecture; Benchmarking; Cardiac; Caring; Case Study; Catalogs; Cause of Death; Cellular Phone; Characteristics; Clinic; Clinical; Clinical Data; Clinical Trials; Communities; Computer Simulation; Computers; Coronary; Coronary Arteriosclerosis; Coronary Stenosis; Coronary artery; Custom; Data; Data Analyses; Detection; Development; Diagnosis; Diagnostic; Disease; Dose; Elements; Emerging Technologies; Evaluation; Geometry; Goals; Heart; Heart Diseases; Heart Rate; Heterogeneity; Human; Human body; Image; Image Analysis; Imaging Device; Imaging Techniques; Imaging technology; Industry; Intravenous; Ionizing radiation; Manufacturer Name; Medical Imaging; Methodology; Methods; Modeling; Modernization; Morphologic artifacts; Motion; Noise; Patients; Perfusion; Population; Positioning Attribute; Process; Property; Protocols documentation; Radiation; Research; Research Personnel; Research Subjects; Resolution; Scanning; Series; Stenosis; Structure; System; Technology; Time; Translations; Variant; Work; X-Ray Computed Tomography; base; cardiovascular visualization; clinical decision-making; clinical investigation; computerized tools; design; evidence base; experimental study; heart imaging; heart motion; heart visualization; high risk; human subject; imaging modality; imaging system; improved; individual patient; metrology; new technology; patient population; reconstruction; simulation; simulation software; spatiotemporal; temporal measurement; tool; virtual

Coronary artery disease (CAD) is the leading cause of death in the US. Medical imaging is integral to the diagnosis and management of CAD fueling the development of new technologies and applications. However, imaging of the heart continues to be a challenging task. There is always a degree of temporal blur or motion artifact, the impact and documented limitations of which remain uncertain. Additionally, patient body habitus and technical limitations may contribute to high noise and degrade spatial resolution. For imaging modalities involving ionizing radiation like CT, radiation dose is also an ever-present reality that needs to be minimized without compromising image quality. Clinical trials are the best avenue for the evaluation of imaging technologies, but the ever-expanding number of technologies and parameters make a trial for every application or protocol unfeasible, pragmatically and financially. As a result, medical imaging researchers, industry, and the FDA are increasingly moving toward computerized simulations or `virtual trials'. Virtual trials involve the use of computational tools to perform experiments entirely on the computer. Realistic patient models or phantoms are combined with validated imaging simulations to emulate imaging examinations and patient conditions. These can subsequently be used to ascertain how differing patient attributes and imaging conditions impact dose, image quality, and depiction of pre-defined known conditions. The findings can be used to prescribe specific imaging protocols and optimal scan parameters that are customized to individual patient anatomy to provide a sufficient degree of certainty for effective clinical decision-making. The goal of this project is to develop, validate, and distribute to the research community a computational platform (including a series of anatomically variable phantoms with realistic finite-element cardiac models, accurate models for modern imaging devices, and a suite of image quality metrics) to perform virtual trials in dynamic cardiac imaging. The virtual framework can be extended to any number of cardiac conditions, imaging modalities, and technologies. As a first case study in our long-term strategy, the focus of this project is on CT as it has both a great need for and great potential to provide high spatial and temporal resolution for the optimized evaluation of CAD. If CT image quality is not optimal, the evaluation of CAD, particularly the degree of stenosis and characterization of high-risk plaque features, may be compromised. The tools we develop will provide the first practical platform to characterize the precise impact of the technical aspects of CT on image quality over a wide range of patient anatomies with the view to enable optimal visualization of cardiac conditions at the lowest possible radiation dose for a given patient. The approach has great potential to significantly improve clinical investigations of heart disease, extending beyond CT imaging and CAD, paving the way towards faster translation of new cardiac imaging technologies into the clinic and more precise and personalized patient management.

冠状动脉疾病（CAD）是美国的主要死亡原因。医学成像是 CAD的诊断和管理推动了新技术和应用的发展。然而，在这方面， 心脏成像仍然是一项具有挑战性的任务。总是有一定程度的时间模糊或运动 人工制品，其影响和记录的局限性仍然不确定。此外，患者体型 并且技术限制可能导致高噪声并降低空间分辨率。用于成像设备 涉及电离辐射，如CT，辐射剂量也是一个永远存在的现实，需要尽量减少 而不损害图像质量。临床试验是影像学评价的最佳途径 技术，但不断扩大的技术和参数的数量使每一个应用程序的尝试 或协议不可行，务实和财政。因此，医学成像研究人员、工业界和 FDA正越来越多地转向计算机模拟或“虚拟试验”。 虚拟试验涉及使用计算工具完全在计算机上进行实验。现实 患者模型或体模与经验证的成像模拟相结合 和病人的情况。这些可以随后用于确定如何不同的患者属性， 成像条件影响剂量、图像质量和预定义的已知条件的描述。这些发现 可用于规定特定的成像协议和最佳扫描参数， 个体患者解剖结构，为有效的临床决策提供足够程度的确定性。 该项目的目标是开发、验证并向研究社区分发一个计算的 平台（包括一系列具有真实有限元心脏模型的解剖学可变体模， 现代成像设备的精确模型，以及一套图像质量指标），以执行虚拟试验， 动态心脏成像虚拟框架可以扩展到任何数量的心脏状况、成像 模式和技术。作为我们长期战略中的第一个案例研究，该项目的重点是CT 因为它既有很大的需求，也有很大的潜力，可以提供高的空间和时间分辨率， CAD优化评价如果CT图像质量不是最佳的，CAD的评价，特别是程度 狭窄和高风险斑块特征的表征可能会受到影响。我们开发的工具将 提供了第一个实用的平台来描述CT技术方面对图像的精确影响 广泛的患者解剖结构的质量，以实现心脏的最佳可视化 在给定患者的最低可能辐射剂量下的条件。该方法具有很大的潜力， 显著改善心脏病的临床研究，超越CT成像和CAD， 新的心脏成像技术更快地转化为临床，更精确， 个性化的患者管理