Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics

Abstract

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.

Automatic image registration of optoacoustic tomography and magnetic resonance imaging based on deep learning

“…These easy changes of network parameters can largely reduce the time cost of algorithm development when we encounter a more specific multimodal imaging task. Furthermore, the registration algorithm can also incorporate a standardized brain atlas [13] with finer segmented anatomical regions. Through this way, MSOT images can be correctly aligned and it can also guide researchers to better localize the optoacoustic signal changes.…”

Monitoring mouse brain perfusion with hybrid magnetic resonance optoacoustic tomography

“…Exogenous contrast agents can further enhance the MRI capabilities [23, 30]. Therefore, the combination between OAT and MRI is expected to bring synergistic advantages and complementarity in terms of spatiotemporal resolution, penetration depth, contrast, as well as multiplex anatomical, functional and molecular readouts [9].…”

“…As shown in Fig.4, the time courses of both contrast agents were in a good agreement, thus further validating the functionality of the MROT system. Although integration between optical imaging methods, such as fluorescence imaging and diffuse optical tomography, and MRI has previously been reported [9, 25, 30, 31], MROT is a unprecedented multimodal combination that achieves sub-second speed, sub-millimeter spatial resolution and a large three-dimensional FOV covering the entire mouse brain with both modalities.…”

“…For example, positron emission tomography (PET) and X-ray computed tomography (CT) are commonly combined to maximize their clinical value in oncology and other medical fields [6, 7]. Likewise, diffuse optical imaging methods can render valuable functional and molecular information in deep tissues [8], but lack the anatomical contrast and spatial resolution required for rendering quantitative information, which can be ameliorated via a multi-modal approach [9]. Multi-modal imaging is also often employed to validate the readings provided by newly developed imaging methods.…”

PET imaging in animal models of Parkinson’s disease

“…Current PD imaging-assisted diagnoses rely on imaging of dopaminergic and metabolic levels in the brain and postganglionic sympathetic cardiac innervation. Small animal imaging has allowed the noninvasive mapping of molecular changes in the brains of animal models with high clinical relevance [28], including αSyn accumulation, neurotransmitter receptor deficits (dopaminergic and serotonergic systems, vesicular monoamine transporter 2), synaptic deficits, cerebral glucose metabolism (CMRglc), neuroinflammation and mitochondrial dysfunction, LRRK2, and the gut-brain axis (targets summarized in Fig. 1, and Table 1).…”