Next generation in-vivo diffusion imaging at submillimeter resolution

摘要 扩散MRI（dMRI）允许脑的神经结构的体内研究，其可以用于 研究正常的大脑发育以及大脑疾病的潜在病理学。的空间分辨率 dMRI数据集约为1.5mm各向同性体素，这对于研究大、中型白色物质是很好的 纤维束，但不足以分析小纤维路径。此外，对微观结构的敏感性 小的皮质和皮质下灰质结构的异常由于显著的部分体积而丢失 存在于不同组织类型之间的边界处的效应（例如，灰白色、灰色CSF等）。因此， 许多神经精神疾病不能在低空间分辨率下精确探测。 因此，我们提出了几种新的采集和重建技术的dMRI，将工作 协同地实现dMRI空间分辨率的数量级改进，达到600微米 各向同性体素大小。这将提供一个非常详细的大脑体内地图，这将使新的 在白色物质连通性方面的发现以及对小尺度组织异常的灵敏度的极大提高。 在3T临床扫描仪上，将在临床可行的扫描时间内实现分辨率的10倍提高 高信号质量。dMRI采集开发将涵盖i）SNR高效采集， 并行成像和专门的RF板编码，ii）无导航的多次激发EPI， 失真和模糊，以及iii）运动鲁棒的RF编码技术，其允许超高分辨率dMRI， 运动敏感度曝光时间为2秒或更短。这些技术将与 协同约束重建使用相位建模以及结构保持空间 空间平滑度约束，以在提高SNR的同时实现大的加速度。为了确保科学严谨，我们 将在离体人脑上与几名健康志愿者一起全面验证我们的技术沿着 使用不同的量化指标。这种空间分辨率的飞跃与在临床上完成的采集 可行的扫描时间将在神经科学的许多领域产生重大而持久的影响， 神经外科这是第一次，它将允许对重要的短皮质进行准确和详细的体内研究。 在表面白色物质区域以及功能关键的皮质和皮质下的联合纤维 灰质区这种技术也应该改变游戏规则，以新兴的大规模大脑研究 其中dMRI起着至关重要的作用，例如在人类连接组项目中，青少年大脑认知 发展项目，以及英国。生物银行项目。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观结构异常，并能够准确描绘 用于在脑深部刺激和图像引导手术中定位电极的神经电路。因此，在本发明中， 我们相信这项技术将为研究人脑提供一个范式转变。

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.