Compressed Sensing with Motion Models for MRI of Late Gadolinium Enhancement

用于后期钆增强 MRI 的运动模型压缩感知

• 批准号: 8179726
• 负责人: EDWARD VR DIBELLA
• 金额: $ 18.69万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2013-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8179726
• 关键词: Ablation; Area; Arrhythmia; Atrial Fibrillation; Breathing; Cardiac; Cardiomyopathies; Cell Survival; Chest; Clinical; Complement; Computer Simulation; Data; Development; Fibrosis; Financial compensation; Future; Gadolinium; Heart; Heart Atrium; Heart Diseases; Human; Hybrids; Image; Image Enhancement; Injury; Lead; Left atrial structure; Left ventricular structure; Location; MRI Scans; Magnetic Resonance Imaging; Measurement; Methods; Metric; Modeling; Monitor; Motion; Patients; Pharmacotherapy; Physicians; Population; Process; Public Health; Publishing; Radial; Reporting; Resolution; Right atrial structure; Scanning; Series; Signal Transduction; Sinus; Site; Solutions; Speed; Structure; Techniques; Technology; Testing; Three-Dimensional Image; Time; Work; base; gadolinium oxide; heart motion; image registration; improved; novel; novel strategies; reconstruction; research clinical testing; respiratory; simulation; success; tool

DESCRIPTION (provided by applicant): This work proposes a new approach to free-breathing high resolution MRI scans. Deformable motion models will be driven by the data along with a navigator signal to estimate the image and its velocity fields within an iterative reconstruction. This approach will be combined with compressed sensing methods, in order to further constrain the solution. Each of the approaches complements the other so that their combination is likely to yield greatly improved images. The approach will be used in the application of imaging late gadolinium enhancement (LGE) in the heart, and in particular imaging LGE in the left atrium. This is motivated by new studies showing that atrial fibrillation and its treatment can be characterized by the amount and location of fibrosis or LGE in the left atrium, and the challenges associated with imaging a thin-walled moving structure. Specific aims are (1) To combine iterative reconstructions employing sparsity constraints with motion models and develop and test the methods with realistic computer simulations and initial test subjects. (2) To make the reconstruction times clinically practical with implementations on GPUs and to test the new methods for obtaining high resolution 3D images of LGE in the left atrium in humans being treated for atrial fibrillation. Methods: Our multi-disciplinary team will develop advanced combined reconstruction methods that include compensation for respiratory motion for Cartesian and hybrid radial 3D LGE sequences. Simulations, test patient data, and a series of patients with atrial fibrillation will be used to develop and test the methods. A variety of tests from difference and blur metrics to image quality ranked by physicians will be employed. The development and use of accurate high resolution free-breathing LGE imaging will improve the assessment of myocardial disease and accelerate evaluation of clinical therapies. PUBLIC HEALTH RELEVANCE: This proposal offers methods to develop novel motion compensation methods for MRI, and to combine them with a sparsity-constrained reconstruction framework. The methods will be applied to improve imaging of fibrosis and cell viability in the heart. If such measurements can be made more accurate this will allow for better and more timely treatments and monitoring of heart disease and improved public health. The proposed methods will be applied to unmet needs in patients with atrial fibrillation to improve their management and to improve our understanding of ablation treatment for atrial fibrillation.

描述（由申请人提供）：这项工作提出了一种自由呼吸高分辨率MRI扫描的新方法。可变形的运动模型将由数据和导航信号驱动，在迭代重建中估计图像及其速度场。该方法将与压缩感知方法相结合，以进一步约束解。每一种方法都是相互补充的，因此它们的组合很可能产生大大改善的图像。该方法将用于心脏晚期钆增强成像（LGE）的应用，特别是左心房的LGE成像。这是由于新的研究表明心房颤动及其治疗可以通过左心房纤维化或LGE的数量和位置以及与薄壁运动结构成像相关的挑战来表征。具体目标是：(1)将采用稀疏性约束的迭代重建与运动模型相结合，并通过真实的计算机模拟和初始测试对象开发和测试方法。(2)通过在gpu上的实现，使重建次数在临床上可行，并测试获得房颤治疗患者左心房LGE高分辨率3D图像的新方法。方法：我们的多学科团队将开发先进的组合重建方法，包括笛卡尔和混合径向三维LGE序列的呼吸运动补偿。模拟，测试患者数据，以及一系列心房颤动患者将用于开发和测试方法。将采用各种测试，从差异和模糊指标到由医生排名的图像质量。准确的高分辨率自由呼吸LGE成像技术的发展和应用将改善心肌疾病的评估，加快临床治疗的评估。