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）是美国的首要死因。医学影像是不可或缺的一部分 CAD 的诊断和管理推动了新技术和应用的开发。然而， 心脏成像仍然是一项具有挑战性的任务。总是存在一定程度的时间模糊或运动 工件，其影响和记录的局限性仍然不确定。另外，患者的身体习惯 技术限制可能会导致高噪声并降低空间分辨率。对于成像方式 涉及像CT这样的电离辐射，辐射剂量也是一个始终存在的现实，需要尽量减少 而不影响图像质量。临床试验是影像学评估的最佳途径 技术，但不断增加的技术和参数对每一种应用都进行了尝试 或协议在务实和财务上不可行。因此，医学影像研究人员、行业和 FDA 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。实际的 患者模型或模型与经过验证的成像模拟相结合，以模拟成像检查 和病人的情况。随后可以使用这些来确定患者属性和 成像条件影响剂量、图像质量和预定义已知条件的描述。研究结果 可用于制定特定的成像协议和定制的最佳扫描参数 个体患者的解剖结构，为有效的临床决策提供足够的确定性。 该项目的目标是开发、验证并向研究界分发一个计算 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）来执行虚拟试验 动态心脏成像。虚拟框架可以扩展到任意数量的心脏疾病、成像 方式和技术。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 因为它对于提供高空间和时间分辨率有很大的需求和巨大的潜力 CAD 的优化评估。如果 CT 图像质量不是最佳，则 CAD 的评估，特别是程度 狭窄的评估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 提供第一个实用平台来表征 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 对于特定患者来说，尽可能降低辐射剂量的条件。该方法具有巨大的潜力 显着改善心脏病的临床研究，超越 CT 成像和 CAD，铺平道路 将新的心脏成像技术更快地转化为临床并更精确和更准确的方法 个性化的患者管理。