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科学家开发出专为7特斯拉超高分辨率人脑成像设计的新一代磁共振成像扫描仪
作者:小柯机器人 发布时间:2023/11/30 21:29:17

美国加州大学伯克利分校David A. Feinberg等研究人员开发出专为7特斯拉超高分辨率人脑成像设计的新一代磁共振成像扫描仪。2023年11月27日,《自然—方法学》杂志在线发表了这项成果。

为了提高人类神经成像科学的颗粒度,研究人员设计并制造了新一代7特斯拉磁共振成像扫描仪,通过实现硬件上的多项进步,达到超高分辨率。为了改进空间编码和提高图像信噪比,研究人员开发了一种头部专用非对称梯度线圈(200 mT m-1,900 T m-1s-1),并增加了第三层绕组。研究人员将128通道接收器系统与64通道和96通道接收器线圈阵列整合在一起,以增强大脑皮层的信号,同时降低g因子噪声,从而实现更高的加速度。

16通道发射系统减少了功率沉积,提高了图像均匀性。该扫描仪能以0.35-0.45毫米的各向同性空间分辨率进行常规功能成像研究,以揭示皮质层的功能活动,在弥散成像中实现了高角度分辨率,并缩短了功能和结构成像的采集时间。

附:英文原文

Title: Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla

Author: Feinberg, David A., Beckett, Alexander J. S., Vu, An T., Stockmann, Jason, Huber, Laurentius, Ma, Samantha, Ahn, Sinyeob, Setsompop, Kawin, Cao, Xiaozhi, Park, Suhyung, Liu, Chunlei, Wald, Lawrence L., Polimeni, Jonathan R., Mareyam, Azma, Gruber, Bernhard, Stirnberg, Rdiger, Liao, Congyu, Yacoub, Essa, Davids, Mathias, Bell, Paul, Rummert, Elmar, Koehler, Michael, Potthast, Andreas, Gonzalez-Insua, Ignacio, Stocker, Stefan, Gunamony, Shajan, Dietz, Peter

Issue&Volume: 2023-11-27

Abstract: To increase granularity in human neuroimaging science, we designed and built a next-generation 7Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200mTm1, 900Tm1s1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35–0.45mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

DOI: 10.1038/s41592-023-02068-7

Source: https://www.nature.com/articles/s41592-023-02068-7

期刊信息

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:47.99
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex