Compressed Sensing with Motion Models for MRI of Late Gadolinium Enhancement

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。可变形运动模型将由数据沿着导航信号驱动，以估计迭代重建内的图像及其速度场。这种方法将与压缩传感方法相结合，以进一步限制解决方案。每一种方法都是对另一种方法的补充，因此它们的结合可能会产生大大改进的图像。该方法将用于心脏中成像晚期钆增强（LGE）的应用，特别是左心房中的成像LGE。这是由于新的研究表明，房颤及其治疗可以通过左心房中纤维化或LGE的数量和位置来表征，以及与成像薄壁移动结构相关的挑战。具体目标是（1）将采用稀疏约束的联合收割机迭代重建与运动模型相结合，并利用现实的计算机模拟和初始测试对象来开发和测试该方法。(2)通过在GPU上实现，使重建时间在临床上实用，并测试用于获得正在接受房颤治疗的人左心房中LGE的高分辨率3D图像的新方法。研究方法：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3D LGE序列的呼吸运动补偿。模拟、测试患者数据和一系列房颤患者将用于开发和测试这些方法。将采用从差异和模糊度量到医生评级的图像质量的各种测试。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速临床治疗的评估。 公共卫生相关性：该提议提供了开发用于MRI的新颖运动补偿方法的方法，并且将它们与稀疏约束重建框架结合联合收割机。这些方法将用于改善心脏纤维化和细胞活力的成像。如果这种测量能够更准确，这将允许更好和更及时地治疗和监测心脏病并改善公共健康。所提出的方法将应用于房颤患者未满足的需求，以改善他们的管理，并提高我们对房颤消融治疗的理解。

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.