Pushing the limits of in vivo diffusion MRI for the Human Connectome Project.
Pushing the limits of in vivo diffusion MRI for the Human Connectome Project.
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DOI：
10.1016/j.neuroimage.2013.05.078
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发表时间：
2013-10-15
期刊：
影响因子：
5.7
通讯作者：
Wald LL
中科院分区：
文献类型：
--
作者：
Setsompop K;Kimmlingen R;Eberlein E;Witzel T;Cohen-Adad J;McNab JA;Keil B;Tisdall MD;Hoecht P;Dietz P;Cauley SF;Tountcheva V;Matschl V;Lenz VH;Heberlein K;Potthast A;Thein H;Van Horn J;Toga A;Schmitt F;Lehne D;Rosen BR;Wedeen V;Wald LL
也许比任何其他“组学”的努力，从绘制活人大脑的主要连接途径的扩散MRI获得的准确性和细节水平取决于所使用的成像技术的能力。当前的工具非常出色；在大脑中每50万体素的复杂交叉纤维区域，形成水扩散概率分布的“图像”。然而，我们绘制连接路径的能力受到图像灵敏度和分辨率的限制，也受到扩散概率分布编码的对比度和分辨率的限制。我们的人类连接组项目（HCP）的目标是通过从头开始重新设计扫描仪来解决这些限制因素，以优化高b值、高角度分辨率的扩散成像，这是对大脑结构连接进行敏感和准确映射所必需的。我们的工作是根据每个扫描仪组件的相对贡献来指导的。梯度分段是一个主要的焦点，因为梯度振幅是决定扩散对比度、T2信号损失的量和扩散时间过程中水PDF的模糊程度的核心。通过实现一种新颖的4端口驱动几何结构，并优化大脑的尺寸和线性度，我们展示了一种全身大小的扫描仪，每个轴上的Gmax = 300mT/m，能够实现扩散成像所需的持续占空比。该系统能够根据EPI图像编码的需要以200 T/m/s的速率旋转梯度。为了提高扩散序列的效率，我们实现了同时多片（SMS） EPI的视场移位方法，该方法能够在适度的g因子惩罚下消除同时激发的3个切片的混淆，从而使我们能够以低TR和TE对整个脑体积进行扩散编码。最后，我们将多切片方法与压缩采样重建相结合，以充分欠采样q空间，在不到5分钟的时间内实现DSI扫描。为了增强这种加速成像方法，我们开发了一种64通道紧密贴合的脑阵列线圈，并在这些加速采集的大脑所有位置与商用32通道线圈相比，展示了其性能优势。讨论了开发整个系统的技术挑战，以及信噪比比较、ODF指标和光纤跟踪比较的结果。超高梯度通过降低TE、改善信号检测、提高DSI或HARDI采集效率、扩散束影成像的精度和分辨率（通过识别已知结构和光纤交叉来定义），在灵敏度方面产生了巨大而直接的收益。
Perhaps more than any other “-omics” endeavor, the accuracy and level of detail obtained from mapping the major connection pathways in the living human brain with diffusion MRI depends on the capabilities of the imaging technology used. The current tools are remarkable; allowing the formation of an “image” of the water diffusion probability distribution in regions of complex crossing fibers at each of half a million voxels in the brain. Nonetheless our ability to map the connection pathways is limited by the image sensitivity and resolution, and also the contrast and resolution in encoding of the diffusion probability distribution. The goal of our Human Connectome Project (HCP) is to address these limiting factors by re-engineering the scanner from the ground up to optimize the high b-value, high angular resolution diffusion imaging needed for sensitive and accurate mapping of the brain’s structural connections. Our efforts were directed based on the relative contributions of each scanner component. The gradient subsection was a major focus since gradient amplitude is central to determining the diffusion contrast, the amount of T2 signal loss, and the blurring of the water PDF over the course of the diffusion time. By implementing a novel 4-port drive geometry and optimizing size and linearity for the brain, we demonstrate a whole-body sized scanner with Gmax = 300mT/m on each axis capable of the sustained duty cycle needed for diffusion imaging. The system is capable of slewing the gradient at a rate of 200 T/m/s as needed for the EPI image encoding. In order to enhance the efficiency of the diffusion sequence we implemented a FOV shifting approach to Simultaneous MultiSlice (SMS) EPI capable of unaliasing 3 slices excited simultaneously with a modest g-factor penalty allowing us to diffusion encode whole brain volumes with low TR and TE. Finally we combine the multi-slice approach with a compressive sampling reconstruction to sufficiently undersample q-space to achieve a DSI scan in less than 5 minutes. To augment this accelerated imaging approach we developed a 64-channel, tight-fitting brain array coil and show its performance benefit compared to a commercial 32-channel coils at all locations in the brain for these accelerated acquisitions. The technical challenges of developing the over-all system are discussed as well as results from SNR comparisons, ODF metrics and fiber tracking comparisons. The ultra-high gradients yielded substantial and immediate gains in the sensitivity through reduction of TE and improved signal detection and increased efficiency of the DSI or HARDI acquisition, accuracy and resolution of diffusion tractography, as defined by identification of known structure and fiber crossing.
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影响因子：
3.3
作者：
Keil, Boris;Blau, James N.;Biber, Stephan;Hoecht, Philipp;Tountcheva, Veneta;Setsompop, Kawin;Triantafyllou, Christina;Wald, Lawrence L.
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