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新的自由呼吸高分辨率MRI扫描方法。可变形运动模型将由数据和导航信号驱动，以在迭代重建中估计图像及其速度场。这种方法将与压缩传感方法相结合，以进一步约束解决方案。每一种方法都是相辅相成的，因此它们的结合可能会产生极大的改善图像。该方法将用于心脏晚期增强成像(LGE)，特别是左心房的LGE成像。这是因为新的研究表明，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)将使用稀疏约束的迭代重建与运动模型相结合，并利用真实的计算机模拟和初始测试对象来开发和测试这些方法。(2)通过在GPU上的实现，使重建时间在临床上得以实现，并测试在接受心房颤动治疗的人类左心房LGE获得高分辨率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3DLGE序列的呼吸运动补偿。将使用模拟、测试患者数据和一系列房颤患者来开发和测试这些方法。将使用从差异和模糊度量到医生对图像质量进行排名的各种测试。准确的高分辨率自由呼吸LGE成像的开发和使用将改善对心肌疾病的评估，并加快临床治疗的评估。 公共卫生相关性：该提案提供了为MRI开发新的运动补偿方法的方法，并将其与稀疏性约束的重建框架相结合。这些方法将被应用于改善心脏纤维化的成像和细胞活性。如果能够更准确地进行这种测量，这将有助于更好、更及时地治疗和监测心脏病，并改善公众健康。建议的方法将应用于房颤患者未得到满足的需求，以改善他们的管理，并提高我们对消融治疗房颤的理解。