Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Innovation Center for Smart Medical Technologies & Devices, Binjiang Institute of Zhejiang University, Hangzhou, China.
Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Innovation Center for Smart Medical Technologies & Devices, Binjiang Institute of Zhejiang University, Hangzhou, China.
Neuroimage. 2024 Apr 15;290:120553. doi: 10.1016/j.neuroimage.2024.120553. Epub 2024 Feb 23.
Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.
神经科学的最新进展需要高分辨率的 MRI 来解析大脑的结构和功能细节。开发高性能的梯度系统是该领域的一项持续努力，旨在实现更高的空间和时间编码。在这里，我们提出了一种仅用于头部的梯度系统 NeuroFrontier，用于神经成像，具有超高的梯度强度 650 mT/m 和 600 T/m/s。该系统的特点在于：1）通过使用一种新颖的并联方法运行两个梯度功率放大器，实现了 7MW 的超高功率；2）采用两级机械结构的力/扭矩平衡梯度线圈设计，允许高效灵活地优化外周神经刺激；3）高密度集成的 RF 系统，针对仅头部系统进行了小型化和定制；4）具有 AI 功能的压缩感知技术，可实现高分辨率图像的超快速采集和 q-t 空间的 AI 加速扩散 MRI（dMRI）；5）前瞻性头部运动校正技术，可通过 3D 光学跟踪实时有效地校正运动伪影。我们展示了该系统在成像分辨率、速度和信噪比方面的潜在优势，用于亚毫米层特异性 fMRI 和 dMRI 的神经科学应用中的 3D 结构 MRI（sMRI）、功能 MRI（fMRI）和 dMRI。我们还说明了该系统在基于 dMRI 的微观结构映射方面的独特优势，例如，在短扩散时间或高 b 值下增强病变对比度，以及使用扩散时间相关 dMRI 或使用 q 空间方法进行神经突微观结构的细胞微观结构的估计精度提高。
