Next generation in-vivo diffusion imaging at submillimeter resolution

摘要 弥散磁共振成像(DMRI)可以在体内研究大脑的神经结构，这是可以使用的 研究正常的大脑发育以及脑部疾病的潜在病理。的空间分辨率 DMRI数据集约为1.5 mm各向同性体素，这对于研究大中型脑白质是很好的 纤维束，但严重不足以分析细小的纤维路径。此外，对微观结构的敏感性 由于显著的部分体积，皮质和皮质下小灰质结构的异常消失 存在于不同组织类型(例如，灰白色、灰色-脑脊液等)之间边界的效果。因此，一个大的 在低空间分辨率下，不能准确探测神经精神障碍的数量。 因此，我们提出了几种适用于dmri的新型采集和重建技术。 协同实现dMRI空间分辨率的数量级提高，达到600微米 各向同性体素大小。这将提供一张极其详细的大脑体内图谱，这将使新的 在白质连通性方面的发现以及对小规模组织异常的敏感度大大提高。 在3T临床扫描仪上，分辨率将在临床可行的扫描时间内实现10倍的提高 具有高信号质量。DMRI采集开发将跨越i)SNR高效采集和高级 并行成像和专门的RF平板编码，ii)最大限度减少几何形状的免导航多激发EPI 失真和模糊，以及iii)运动稳健的RF编码技术，允许超高分辨率的dMRI 运动感光度曝光时间范围为2秒或更短。这些技术将与 协同式约束重建，将相位建模与保结构空间和Q-重建相结合。 空间平滑度限制，以在提高信噪比的同时实现大幅加速。为确保科学严谨，我们 将与几名健康志愿者一起在体外人脑上全面验证我们的技术 使用不同的量化指标。这一空间分辨率的飞跃是在临床上完成的 可行的扫描时间将在神经科学的许多领域产生重大和持久的影响 神经外科。它将第一次允许对重要的短皮质进行准确和详细的体内研究 浅层白质区域以及功能临界皮质和皮质下的联合纤维 灰质区域。对于新兴的大规模大脑研究来说，这种技术也应该改变游戏规则 在dMRI发挥关键作用的地方，例如在人类连接组项目中，青少年大脑认知 开发项目和英国生物库项目。超高分辨率的dmri也将增强我们的能力 了解神经发育障碍的微结构异常，并能够准确地描绘 在脑深部刺激和图像引导手术中用于定位电极的神经电路。因此， 我们相信，提出的技术将为研究人脑提供一种范式转换。

Abstract Diffusion MRI (dMRI) allows the in-vivo investigation of the neural architecture of the brain, which can be used to study normal brain development as well as potential pathologies in brain disorders. The spatial resolution of dMRI data sets is around 1.5mm isotropic voxels, which is good to study large and medium size white matter fiber bundles, but grossly insufficient to analyze small fiber pathways. Further, sensitivity to microstructural abnormalities in small cortical and subcortical gray matter structures is lost due to significant partial volume effects that exist at the boundary between different tissue types (e.g., gray-white, gray-CSF, etc.). Thus, a large number of neuropsychiatric disorders cannot be accurately probed at low spatial resolutions. Consequently, we propose several novel acquisition and reconstruction technologies for dMRI that will work synergistically to achieve an order-of-magnitude improvement in dMRI’s spatial resolution, to 600 micron isotropic voxel size. This will provide an extremely detailed in-vivo map of the brain, which will enable new discoveries in white matter connectivity as well as vastly improved sensitivity to small scale tissue abnormalities. This 10-fold improvement in resolution will be achieved in a clinically feasible scan time, on a 3T clinical scanner with high signal quality. The dMRI acquisition development will span i) SNR-efficient acquisition with advanced parallel imaging and specialized RF slab-encoding, ii) navigation-free multi-shot EPI that minimizes geometric distortions and blurring, and iii) motion-robust RF-encoding technique that allow ultra-high resolution dMRI with motion sensitivity exposure time-frame of 2s or less. These technologies will be developed in parallel with a synergistic constrained reconstruction that use phase modeling together with structure-preserving spatial and q- space smoothness constraints, to enable large accelerations while boosting SNR. To ensure scientific rigor, we will comprehensively validate our technology on an ex-vivo human brain along with several healthy volunteers using different quantification metrics. This leap in spatial resolution with acquisition done in a clinically feasible scan time will have a significant and lasting impact in many areas of neuroscience and neurosurgery. For the first time, it will allow accurate and detailed in-vivo investigation of important short cortical association fibers in the superficial white matter regions, as well as functionally critical cortical and sub-cortical gray matter areas. Such technology should also be game-changing to emerging large-scale studies of the brain where dMRI plays a crucial role, such as in the Human Connectome Project, the Adolescent Brain Cognitive Development project, and the U.K. bio-bank project. The ultra-high resolution dMRI will also enhance our ability to understand microstructural abnormalities in neurodevelopmental disorders, and enable accurate delineation of the neural circuitry for positioning the electrode in deep brain stimulation and in image-guided surgery. Thus, we believe that the propose technology will provide a paradigm shift for studying the human brain.