Neuroinflammation play an important role in Alzheimer’s disease pathogenesis. Advances in molecular imaging using positron emission tomography have provided insights into the time course of neuroinflammation and its relation with Alzheimer’s disease central pathologies in patients and in animal disease models. Recent single-cell sequencing and transcriptomics indicate dynamic disease-associated microglia and astrocyte profiles in Alzheimer’s disease. Mitochondrial 18-kDa translocator protein is the most widely investigated target for neuroinflammation imaging. New generation of translocator protein tracers with improved performance have been developed and evaluated along with tau and amyloid imaging for assessing the disease progression in Alzheimer’s disease continuum. Given that translocator protein is not exclusively expressed in glia, alternative targets are under rapid development, such as monoamine oxidase B, matrix metalloproteinases, colony-stimulating factor 1 receptor, imidazoline-2 binding sites, cyclooxygenase, cannabinoid-2 receptor, purinergic P2X7 receptor, P2Y12 receptor, the fractalkine receptor, triggering receptor expressed on myeloid cells 2, and receptor for advanced glycation end products. Promising targets should demonstrate a higher specificity for cellular locations with exclusive expression in microglia or astrocyte and activation status (pro- or anti-inflammatory) with highly specific ligand to enable in vivo brain imaging. In this review, we summarised recent advances in the development of neuroinflammation imaging tracers and provided an outlook for promising targets in the future.

Multimodal imaging combining optoacoustic tomography (OAT) with magnetic resonance imaging (MRI) enables spatiotemporal resolution complementarity, improves accurate quantification, and thus yields more insights into physiology and pathophysiology. However, only manual landmark based coregistration of OAT-MRI has been used so far. We developed a toolbox (RegOA), which frames an automated registration pipeline to align OAT with high-field MR images based on mutual information. We assessed the performance of the registration method using images acquired on one phantom with fiducial markers and in vivo/ex vivo data of mouse heads/brain. The accuracy and robustness of the registration are improved using a two-step registration method with preprocessing of OAT and MRI data. The major advantages of our approach are minimal user input and quantitative assessment of the registration error. The registration with MR and standard reference atlas enables regional information extraction, facilitating the accurate, objective, and rapid analysis of large groups of rodent OAT and MR images.

Oxygen metabolism and matrix metalloproteinases (MMPs) play important roles in the pathophysiology of cerebral ischemia. Using multispectral optoacoustic tomography (MSOT) imaging, we visualized changes in cerebral tissue oxygenation during 1 h of transient middle cerebral artery occlusion (tMCAO) and at 48 h after reperfusion together with MMP activity using an MMP-activatable probe. The deoxyhemoglobin, oxyhemoglobin, and MMP signals were coregistered with structural magnetic resonance imaging data. The ipsi-/contralateral ratio of tissue oxygen saturation ([Formula: see text]) was significantly reduced during 1 h of tMCAO and recovered after 48 h of reperfusion in tMCAO compared with sham-operated mice ([Formula: see text] to 10 per group). A higher ipsi-/contralateral MMP signal ratio was detected at 48 h after reperfusion in the lesioned brain regions of tMCAO compared with the sham-operated animal ([Formula: see text] to 6 per group). near-infrared fluorescence imaging of MMP signal in brain slices was used to validate MSOT measurements. In conclusion, noninvasive MSOT imaging can provide visualization of hemodynamic alterations and MMP activity in a mouse model of cerebral ischemia.

Optoacoustic tomography (OAT) and magnetic resonance imaging (MRI) provide highly complementary capabilities for anatomical and functional imaging of living organisms. Herein, we investigate on the feasibility of combining both modalities to render concurrent images. This was achieved by introducing a specifically‐designed copper‐shielded spherical ultrasound array into a preclinical MRI scanner. Phantom experiments revealed that the OAT probe caused minimal distortion in the MRI images, while synchronization of the laser and the MRI pulse sequence enabled defining artifact‐free acquisition windows for OAT. Good dynamic OAT contrast from superparamagnetic iron oxide nanoparticles, a commonly used agent for MRI contrast enhancement, was also observed. The hybrid OAT‐MRI system thus provides an excellent platform for cross‐validating functional readings of both modalities. Overall, this initial study serves to establish the technical feasibility of developing a hybrid OAT‐MRI system for biomedical research.

Fluorescence molecular tomography (FMT) can provide valuable molecular information by mapping the bio-distribution of fluorescent reporter molecules in the intact organism. Various prototype FMT systems have been introduced during the past decade. However, none of them has evolved as a standard tool for routine biomedical research. The goal of this paper is to develop a software package that can automate the complete FMT reconstruction procedure. Methods: We present smart toolkit for fluorescence tomography (STIFT), a comprehensive platform comprising three major protocols: 1) virtual FMT, i.e., forward modeling and reconstruction of simulated data; 2) control of actual FMT data acquisition; and 3) reconstruction of experimental FMT data. Results: Both simulation and phantom experiments have shown robust reconstruction results for homogeneous and heterogeneous tissue-mimicking phantoms containing fluorescent inclusions. Conclusion: STIFT can be used for optimization of FMT experiments, in particular for optimizing illumination patterns. Significance: This paper facilitates FMT experiments by bridging the gaps between simulation, actual experiments, and data reconstruction.

The FMT/dFRI protocol presented is able to accurately map physiological processes and poses an attractive alternative to MRI for characterizing tumor neoangiogenesis.

Fluorescence molecular tomography (FMT) is an emerging powerful tool for biomedical research. There are two factors that influence FMT reconstruction most effectively. The first one is the regularization techniques. Traditional methods such as Tikhonov regularization suffer from low resolution and poor signal to noise ratio. Therefore sparse regularization techniques have been introduced to improve the reconstruction quality. The second factor is the illumination pattern. A better illumination pattern ensures the quantity and quality of the information content of the data set thus leading to better reconstructions. In this work, we take advantage of the discrete formulation of the forward problem to give a rigorous definition of an illumination pattern as well as the admissible set of the patterns. We add restrictions in the admissible set as different types of regularizers to a discrepancy functional, generating another inverse problem with the illumination pattern as unknown. Both inverse problems of reconstructing the fluorescence distribution and finding the optimal illumination pattern are solved by fast efficient iterative algorithms. Numerical experiments have shown that with suitable choice of the regularization parameters the two-step approach converges to an optimal illumination pattern quickly and the reconstruction result is improved significantly, regardless of the initial illumination setting.

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.