Ren Wuwei, Ji Bin, Guan Yihui, Cao Lei, Ni Ruiqing
School of Information Science and Technology, ShanghaiTech University, Shanghai, China.
Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, Shanghai, China.
Front Med (Lausanne). 2022 Mar 24;9:771982. doi: 10.3389/fmed.2022.771982. eCollection 2022.
Small animal models play a fundamental role in brain research by deepening the understanding of the physiological functions and mechanisms underlying brain disorders and are thus essential in the development of therapeutic and diagnostic imaging tracers targeting the central nervous system. Advances in structural, functional, and molecular imaging using MRI, PET, fluorescence imaging, and optoacoustic imaging have enabled the interrogation of the rodent brain across a large temporal and spatial resolution scale in a non-invasively manner. However, there are still several major gaps in translating from preclinical brain imaging to the clinical setting. The hindering factors include the following: (1) intrinsic differences between biological species regarding brain size, cell type, protein expression level, and metabolism level and (2) imaging technical barriers regarding the interpretation of image contrast and limited spatiotemporal resolution. To mitigate these factors, single-cell transcriptomics and measures to identify the cellular source of PET tracers have been developed. Meanwhile, hybrid imaging techniques that provide highly complementary anatomical and molecular information are emerging. Furthermore, deep learning-based image analysis has been developed to enhance the quantification and optimization of the imaging protocol. In this mini-review, we summarize the recent developments in small animal neuroimaging toward improved translational power, with a focus on technical improvement including hybrid imaging, data processing, transcriptomics, awake animal imaging, and on-chip pharmacokinetics. We also discuss outstanding challenges in standardization and considerations toward increasing translational power and propose future outlooks.
小动物模型通过加深对脑部疾病潜在生理功能和机制的理解，在脑研究中发挥着基础性作用，因此对于开发针对中枢神经系统的治疗和诊断成像示踪剂至关重要。使用MRI、PET、荧光成像和光声成像的结构、功能和分子成像技术的进步，使得以非侵入性方式在大的时间和空间分辨率尺度上对啮齿动物大脑进行研究成为可能。然而，从临床前脑成像向临床应用转化仍存在几个主要差距。阻碍因素包括：（1）生物物种之间在脑大小、细胞类型、蛋白质表达水平和代谢水平方面的内在差异，以及（2）图像对比度解释和时空分辨率有限方面的成像技术障碍。为了减轻这些因素的影响，已经开发了单细胞转录组学和识别PET示踪剂细胞来源的方法。与此同时，能够提供高度互补的解剖和分子信息的混合成像技术正在兴起。此外，基于深度学习的图像分析也已得到发展，以加强成像方案的量化和优化。在这篇小型综述中，我们总结了小动物神经成像在提高转化能力方面的最新进展，重点关注包括混合成像、数据处理、转录组学、清醒动物成像和芯片上药物动力学等技术改进。我们还讨论了标准化方面的突出挑战以及提高转化能力的考虑因素，并提出了未来展望。
