Sparsity-Based MRI Reconstruction of Physiologic Dimensions

基于稀疏性的生理维度 MRI 重建

• 批准号: 9125827
• 负责人: Leon Axel
• 金额: $ 21.19万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9125827
• 关键词: Abdomen; Angiography; Area; Arrhythmia; Breathing; Cardiac; Cardiovascular Diseases; Cardiovascular system; Chest; Clinical; Data; Diagnostic; Dimensions; Disease; Evaluation; Exercise; Financial compensation; Future; Generations; Goals; Health; Heart; Image; Imaging Phantoms; Lead; Left ventricular structure; Magnetic Resonance Imaging; Measures; Methods; Monitor; Morphologic artifacts; Motion; Musculoskeletal; Normal Range; Patients; Physiological; Positron-Emission Tomography; Property; Radial; Research; Resolution; Respiration; Right ventricular structure; Sampling; Speed; Stress; Variant; Ventricular; attenuation; base; data acquisition; heart function; heart motion; image reconstruction; imaging modality; imaging system; improved; interest; musculoskeletal imaging; novel; novel strategies; pediatric patients; performance tests; practical application; research clinical testing; respiratory; simulation; tool

 DESCRIPTION (provided by applicant): While magnetic resonance imaging (MRI) is clinically very valuable, current imaging methods are subject to blurring and artifacts in the presence of physiologic (e.g., respiratory and cardiac) motion, as well as of arrhythmias, thus limiting the practical application of MRI in many patients. The currently used MRI methods are also limited in their ability to study the effects of free breathing and arrhythmias on the heart. The proposed research will further develop and evaluate a new approach to imaging in the presence of physiologic motion, which parameterizes such motions with a variable that is treated as an additional "dimension" to be reconstructed. This would not be practically feasible with conventional methods, due to the additional associated data acquisition that would be required. However, with the use of sparsity-based image reconstruction methods, the high degree of correlation of the images along these additional dimensions permits good quality image reconstructions, even with heavily undersampled imaging data. We already have made successful initial implementations of this new method for 2D cine imaging and 3D MR angiography. In the proposed research, we will further improve these initial implementations, and we will extend them to include implementations of our methods for other MRI sequences, particularly fully 3D cine data acquisitions. We will evaluate the image quality achievable with these new methods in the presence of free breathing and arrhythmias, as compared with conventional clinical imaging methods, using both numerical phantom simulations and clinical cardiac function analysis in pediatric patients to test the performance. We will also evaluate the potential for extracting new kinds of functional information from these multidimensional image sets, including the effects of free breathing and arrhythmias on the heart, using analysis tools that we will be developing. If this research is successful, these new methods will provide significantly improved MR image quality in the presence of free breathing and arrhythmias, as well as providing potentially valuable new kinds of information on the function of the heart. They may also be able to be used for performing MRI in the presence of exercise, which could be useful for both cardiovascular and musculoskeletal applications, as well as in combination with other kinds of imaging, such as with integrated PET/MRI systems. This research should thus further increase the clinical utility of MR imaging for many patients.

 描述（由申请人提供）：虽然磁共振成像（MRI）在临床上非常有价值，但当前的成像方法在存在生理（例如呼吸和心脏）运动以及心律失常的情况下容易出现模糊和伪影，从而限制了目前使用的 MRI 方法在研究自由呼吸和心律失常对心脏的影响方面也受到限制。这项研究将进一步开发和评估一种新的方法。在存在生理运动的情况下进行成像的方法，该方法用被视为要重建的附加“维度”的变量来参数化这些运动，这对于传统方法来说实际上是不可行的，因为需要额外的相关数据采集。然而，通过使用基于稀疏性的图像重建方法，即使对于严重欠采样的成像数据，图像沿这些附加维度的高度相关性也可以实现高质量的图像重建。方法用于2D 电影成像和 3D MR 血管造影在拟议的研究中，我们将进一步改进这些初始实现，并将其扩展到其他 MRI 序列的方法的实现，特别是完整的 3D 电影数据采集，我们将评估图像质量。与传统的临床成像方法相比，在存在自由呼吸和心律失常的情况下，使用这些新方法可以实现，使用数值模型模拟和临床心脏功能分析来测试儿科患者的性能。还使用我们将开发的分析工具评估从这些多维图像集中提取新型功能信息的潜力，包括自由呼吸和心律失常对心脏的影响，如果这项研究成功，这些新方法将提供显着的帮助。在存在自由呼吸和心律失常的情况下提高 MR 图像质量，并提供有关心脏功能的潜在有价值的新信息。它们还可以用于在运动情况下进行 MRI。对心血管都有用因此，这项研究将进一步提高 MR 成像对许多患者的临床实用性。