Practical Nonlinear Gradient Encoding for Enhanced Accelerated Imaging

项目总结/摘要 该项目将通过引入一种新技术来减少MRI扫描时间，从而有益于公众健康。法兰沙 将动态波形中适度幅度的非线性梯度添加到标准笛卡尔MRI协议。 对标准笛卡尔MRI扫描的这种小扰动允许更大的数据欠采样，并且 更快的收购时间。这个建议是创新的，因为它结合了笛卡尔的可靠性， 使用少量非线性梯度编码成像，以大大增强并行成像 加速度该提案意义重大，因为它将表明，一个单一的特征良好的 非线性梯度波形可以改善用于广泛临床应用的欠采样成像 序列和扫描处方，潜在地使忙碌的临床站点的总体扫描吞吐量加倍。 这些目标将证明，对于许多扫描处方，甚至在常见的 实验缺陷或其他并行成像策略，FRONSAC进一步增加加速度， 额外的2 - 4x。 1)层序开发和优化。 a）开发具有3个NLG通道的FRONSAC波形，以获得最大化的GRE序列 临床上可接受的加速度。 B）使用该FRONSAC波形，开发一组广泛使用的临床序列， FRONSAC加速：3D MP-FLAIR、bSSFP、TSE和T2w-FLAIR。 2)演示体内FRONSAC成像。 a）获取人脑图像并与传统编码进行对比。 B）比较FRONSAC和笛卡尔编码之间的欠采样性能。 3)显示使用针对单个优化的FRONSAC梯度采集的欠采样图像 几何显示了对人类大脑成像的笛卡尔编码的持续改进（对于 不同的几何形状和各种常见的实验缺陷下），并保留 与其他加速方法兼容。 a）当改变FOV、分辨率和切片方向时，测试欠采样伪影。 B）具有已知（引入）缺陷的测试序列：梯度定时误差、不完善的匀场，或 非共振自旋 c）证明与kz欠采样和多层CAIPIRINHA的兼容性。

Project Summary/Abstract This project will benefit public health by ushering in a new technology to reduce MRI scan times. FRONSAC adds nonlinear gradients of modest amplitude in dynamic waveforms to standard Cartesian MRI protocols. This small perturbation to the standard Cartesian MRI scan allows for greater undersampling of data, and faster acquisition times. This proposal is innovative because it marries the reliability of Cartesian imaging with a small amount of nonlinear gradient encoding to greatly enhance parallel imaging acceleration. The proposal is significant because it will demonstrate that a single well-characterized nonlinear gradient waveform can improve undersampled imaging for a broad range of clinical sequences and scan prescriptions, potentially doubling overall scan throughput for busy clinical sites. The aims will demonstrate that, for many scan prescriptions, and even in the presence of common experimental imperfections or other parallel imaging strategies, FRONSAC further multiplies acceleration by an additional 2-4x. 1) Sequence development and optimization. a) Develop a FRONSAC waveform, with 3 NLG channels, for a GRE sequence that maximizes clinically acceptable acceleration. b) Using this FRONSAC waveform, develop a set of widely used clinical sequences implementing FRONSAC acceleration: 3D MP-RAGE, bSSFP, TSE and T2w-FLAIR. 2) Demonstrate FRONSAC imaging in vivo. a) Acquire human brain images and compare contrast with conventional encoding. b) Compare undersampling performance between FRONSAC and Cartesian encoding. 3) Show that undersampled images acquired using a FRONSAC gradient optimized for a single geometry shows persistent improvements over Cartesian encoding for human brain imaging (for different geometries and under various common experimental imperfections), and retains compatibility with other acceleration approaches. a) Test for undersampling artifacts when changing FOV, resolution, and slice orientation. b) Test sequences with known (introduced) imperfections: gradient timing errors, imperfect shim, or off-resonance spins. c) Demonstrate compatibility with both kz undersampling and multislice CAIPIRINHA.