Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging.

OBJECTIVE: We introduce a robust image reconstruction algorithm named Residual-guided Golub-Kahan Iterative Reconstruction Technique (RGIRT) designed for sparse-view computed tomography (CT), which aims at iterative reconstruction for a limited number of projection views. Approach: RGIRT utilizes an inner-outer dual iteration framework, with a flexible least square QR (FLSQR) algorithm implemented in the inner iteration and a restarted iterative scheme applied in the outer iteration. The inner FLSQR employs a flexible Golub-Kahan bidiagonalization method to reduce the size of the inverse problem, and a weighted generalized cross-validation method to adaptively estimate the regularization hyper-parameter. The inner iteration efficiently yields the intermediate reconstruction result, while the outer iteration minimizes the residual and refines the solution by using the result obtained from the inner iteration. Main results: The reconstruction performance of RGIRT is evaluated and compared to other reference methods (FBPConvNet, SART-TV, and FLSQR) using projection data from both numerical phantoms and real experimental Micro-CT data. The experimental findings, from testing various numbers of projection views and different noise levels, underscore the robustness of RGIRT. Meanwhile, theoretical outcomes confirm the convergence of our approach. Significance: We propose a robust iterative reconstruction algorithm for X-ray CT scans with sparse projection views, thereby shortening scanning time and mitigating excessive ionizing radiation exposure to small animals. .

Lanthanide luminescence nanothermometer with working wavelength beyond 1500 nm for cerebrovascular temperature imaging in vivo.

Nanothermometers enable the detection of temperature changes at the microscopic scale, which is crucial for elucidating biological mechanisms and guiding treatment strategies. However, temperature monitoring of micron-scale structures in vivo using luminescent nanothermometers remains challenging, primarily due to the severe scattering effect of biological tissue that compromises the imaging resolution. Herein, a lanthanide luminescence nanothermometer with a working wavelength beyond 1500 nm is developed to achieve high-resolution temperature imaging in vivo. The energy transfer between lanthanide ions (Er3+ and Yb3+) and H2O molecules, called the environment quenching assisted downshifting process, is utilized to establish temperature-sensitive emissions at 1550 and 980 nm. Using an optimized thin active shell doped with Yb3+ ions, the nanothermometer's thermal sensitivity and the 1550 nm emission intensity are enhanced by modulating the environment quenching assisted downshifting process. Consequently, minimally invasive temperature imaging of the cerebrovascular system in mice with an imaging resolution of nearly 200 µm is achieved using the nanothermometer. This work points to a method for high-resolution temperature imaging of micron-level structures in vivo, potentially giving insights into research in temperature sensing, disease diagnosis, and treatment development.

Noninvasive Visualization of Amyloid-Beta Deposits in Alzheimer's Amyloidosis Mice via Fluorescence Molecular Tomography Using Contrast Agent.

Alzheimer's disease is pathologically featured by the accumulation of amyloid-beta (Aß) plaque and neurofibrillary tangles. Compared to small animal positron emission tomography, optical imaging features nonionizing radiation, low cost, and logistic convenience. Optical detection of Aß deposits is typically implemented by 2D macroscopic imaging and various microscopic techniques assisted with Aß-targeted contrast agents. Here, we introduce fluorescence molecular tomography (FMT), a macroscopic 3D fluorescence imaging technique, convenient for in vivo longitudinal monitoring of the animal brain without the involvement of cranial window opening operation. This chapter aims to provide the protocols for FMT in vivo imaging of Aß deposits in the brain of rodent model of Alzheimer's disease. The materials, stepwise method, notes, limitations of FMT, and emerging opportunities for FMT techniques are presented.

Single-pixel p-graded-n junction spectrometers.

Ultra-compact spectrometers are becoming increasingly popular for their promising applications in biomedical analysis, environmental monitoring, and food safety. In this work, we report a single-pixel-photodetector spectrometer with a spectral range from 480 nm to 820 nm, based on the AlGaAs/GaAs p-graded-n junction with a voltage-tunable optical response. To reconstruct the optical spectrum, we propose a tailored method called Neural Spectral Fields (NSF) that leverages the unique wavelength and bias-dependent responsivity matrix. Our spectrometer achieves a high spectral wavelength accuracy of up to 0.30 nm and a spectral resolution of up to 10 nm. Additionally, we demonstrate the high spectral imaging performance of the device. The compatibility of our demonstration with the standard III-V process greatly accelerates the commercialization of miniaturized spectrometers.

MiniMounter: A low-cost miniaturized microscopy development toolkit for image quality control and enhancement.

Head-mounted miniaturized fluorescence microscopy (Miniscope) has emerged as a significant tool in neuroscience, particularly for behavioral studies in awake rodents. However, the challenges of image quality control and standardization persist for both Miniscope users and developers. In this study, we propose a cost-effective and comprehensive toolkit named MiniMounter. This toolkit comprises a hardware platform that offers customized grippers and four-degree-of-freedom adjustment for Miniscope, along with software that integrates displacement control, image quality evaluation, and enhancement of 3D visualization. Our toolkit makes it feasible to accurately characterize Miniscope. Furthermore, MiniMounter enables auto-focusing and 3D imaging for Miniscope prototypes that possess solely a 2D imaging function, as demonstrated in phantom and animal experiments. Overall, the implementation of MiniMounter effectively enhances image quality, reduces the time required for experimental operations and image evaluation, and consequently accelerates the development and research cycle for both users and developers within the Miniscope community.

Multifunctional Optical Tomography System With High-Fidelity Surface Extraction Based on a Single Programmable Scanner and Unified Pinhole Modeling.

OBJECTIVE: Macroscopic optical tomography is a non-invasive method that can visualize the 3D distribution of intrinsic optical properties or exogenous fluorophores, making it highly attractive for small animal imaging. However, reconstructing the images requires prior knowledge of surface information. To address this, existing systems often use additional hardware components or integrate multimodal information, which is expensive and introduces new issues such as image registration. Our goal is to develop a multifunctional optical tomography system that can extract surface information using a concise hardware design. METHODS: Our proposed system uses a single programmable scanner to implement both surface extraction and optical tomography functions. A unified pinhole model is used to describe both the illumination and detection procedures for capturing 3D point cloud. Line-shaped scanning is adopted to improve both spatial resolution and speed of surface extraction. Finally, we integrate the extracted surface information into the optical tomographic reconstruction to more accurately map the fluorescence distribution. RESULT: Comprehensive phantom experiments with different levels of complexity were designed to evaluate the performance of surface extraction and fluorescence tomography. We also imaged the axillary lymph nodes in living mice after injection of fluorophore, demonstrating the proposed system facilitates more reliable fluorescence tomography. CONCLUSION: We have successfully developed a versatile optical tomography system by leveraging concise hardware design and unified pinhole modeling. Phantom validation demonstrates that our system provides high-precision surface information with a maximum error of 0.1 mm, while the surface-guided FMT reconstruction is more reliable than the blind reconstruction using simplified surface geometry, elevating several quantitative metrics including RMSE, CNR, and Dice. SIGNIFICANCE: Our work explores the feasibility of obtaining additional surface information using existing components of standalone optical tomography. This makes the optical tomographic technique more accurate and more accessible to biomedical researchers.

Monitoring mouse brain perfusion with hybrid magnetic resonance optoacoustic tomography.

Progress in brain research critically depends on the development of next-generation multi-modal imaging tools capable of capturing transient functional events and multiplexed contrasts noninvasively and concurrently, thus enabling a holistic view of dynamic events in vivo. Here we report on a hybrid magnetic resonance and optoacoustic tomography (MROT) system for murine brain imaging, which incorporates an MR-compatible spherical matrix array transducer and fiber-based light illumination into a 9.4 T small animal scanner. An optimized radiofrequency coil has further been devised for whole-brain interrogation. System's utility is showcased by acquiring complementary angiographic and soft tissue anatomical contrast along with simultaneous dual-modality visualization of contrast agent dynamics in vivo.

Hybrid magnetic resonance and optoacoustic tomography (MROT) for preclinical neuroimaging.

Multi-modal imaging is essential for advancing our understanding of brain function and unraveling pathophysiological processes underlying neurological and psychiatric disorders. Magnetic resonance (MR) and optoacoustic (OA) imaging have been shown to provide highly complementary contrasts and capabilities for preclinical neuroimaging. True integration between these modalities can thus offer unprecedented capabilities for studying the rodent brain in action. We report on a hybrid magnetic resonance and optoacoustic tomography (MROT) system for concurrent noninvasive structural and functional imaging of the mouse brain. Volumetric OA tomography was designed as an insert into a high-field MR scanner by integrating a customized MR-compatible spherical transducer array, an illumination module, and a dedicated radiofrequency coil. A tailored data processing pipeline has been developed to mitigate signal crosstalk and accurately register image volumes acquired with T1-weighted, angiography, and blood oxygenation level-dependent (BOLD) sequences onto the corresponding vascular and oxygenation data recorded with the OA modality. We demonstrate the concurrent acquisition of dual-mode anatomical and angiographic brain images with the scanner, as well as real-time functional readings of multiple hemodynamic parameters from animals subjected to oxygenation stress. Our approach combines the functional and molecular imaging advantages of OA with the superb soft-tissue contrast of MR, further providing an excellent platform for cross-validation of functional readings by the two modalities.

Deep learning facilitates fully automated brain image registration of optoacoustic tomography and magnetic resonance imaging.

Multispectral optoacoustic tomography (MSOT) is an emerging optical imaging method providing multiplex molecular and functional information from the rodent brain. It can be greatly augmented by magnetic resonance imaging (MRI) which offers excellent soft-tissue contrast and high-resolution brain anatomy. Nevertheless, registration of MSOT-MRI images remains challenging, chiefly due to the entirely different image contrast rendered by these two modalities. Previously reported registration algorithms mostly relied on manual user-dependent brain segmentation, which compromised data interpretation and quantification. Here we propose a fully automated registration method for MSOT-MRI multimodal imaging empowered by deep learning. The automated workflow includes neural network-based image segmentation to generate suitable masks, which are subsequently registered using an additional neural network. The performance of the algorithm is showcased with datasets acquired by cross-sectional MSOT and high-field MRI preclinical scanners. The automated registration method is further validated with manual and half-automated registration, demonstrating its robustness and accuracy.

Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography.

Abnormal cerebral accumulation of amyloid-beta peptide (Aß) is a major hallmark of Alzheimer's disease. Non-invasive monitoring of Aß deposits enables assessing the disease burden in patients and animal models mimicking aspects of the human disease as well as evaluating the efficacy of Aß-modulating therapies. Previous in vivo assessments of plaque load have been predominantly based on macroscopic fluorescence reflectance imaging (FRI) and confocal or two-photon microscopy using Aß-specific imaging agents. However, the former method lacks depth resolution, whereas the latter is restricted by the limited field of view preventing a full coverage of the large brain region. Here, we utilized a fluorescence molecular tomography (FMT)-magnetic resonance imaging (MRI) pipeline with the curcumin derivative fluorescent probe CRANAD-2 to achieve full 3D brain coverage for detecting Aß accumulation in the arcAß mouse model of cerebral amyloidosis. A homebuilt FMT system was used for data acquisition, whereas a customized software platform enabled the integration of MRI-derived anatomical information as prior information for FMT image reconstruction. The results obtained from the FMT-MRI study were compared to those from conventional planar FRI recorded under similar physiological conditions, yielding comparable time courses of the fluorescence intensity following intravenous injection of CRANAD-2 in a region-of-interest comprising the brain. In conclusion, we have demonstrated the feasibility of visualizing Aß deposition in 3D using a multimodal FMT-MRI strategy. This hybrid imaging method provides complementary anatomical, physiological and molecular information, thereby enabling the detailed characterization of the disease status in arcAß mouse models, which can also facilitate monitoring the efficacy of putative treatments targeting Aß.

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

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.

PET Imaging of Neuroinflammation in Alzheimer's Disease.

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.

Noninvasive multimodal fluorescence and magnetic resonance imaging of whole-organ intervertebral discs.

Low back pain (LBP) is a commonly experienced symptom posing a tremendous healthcare burden to individuals and society at large. The LBP pathology is strongly linked to degeneration of the intervertebral disc (IVD), calling for development of early-stage diagnostic tools for visualizing biomolecular changes in IVD. Multimodal measurements of fluorescence molecular tomography (FMT) and magnetic resonance imaging (MRI) were performed on IVD whole organ culture model using an in-house built FMT system and a high-field MRI scanner. The resulted multimodal images were systematically validated through epifluorescence imaging of the IVD sections at a microscopic level. Multiple image contrasts were exploited, including fluorescence distribution, anatomical map associated with T1-weighted MRI contrast, and water content related with T2 relaxation time. The developed multimodality imaging approach may thus serve as a new assessment tool for early diagnosis of IVD degeneration and longitudinal monitoring of IVD organ culture status using fluorescence markers.

Development of concurrent magnetic resonance imaging and volumetric optoacoustic tomography: A phantom feasibility study.

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.

Multimodal imaging combining time-domain near-infrared optical tomography and continuous-wave fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) emerges as a powerful non-invasive imaging tool with the ability to resolve fluorescence signals from sources located deep in living tissues. Yet, the accuracy of FMT reconstruction depends on the deviation of the assumed optical properties from the actual values. In this work, we improved the accuracy of the initial optical properties required for FMT using a new-generation time-domain (TD) near-infrared optical tomography (NIROT) system, which effectively decouples scattering and absorption coefficients. We proposed a multimodal paradigm combining TD-NIROT and continuous-wave (CW) FMT. Both numerical simulation and experiments were performed on a heterogeneous phantom containing a fluorescent inclusion. The results demonstrate significant improvement in the FMT reconstruction by taking the NIROT-derived optical properties as prior information. The multimodal method is attractive for preclinical studies and tumor diagnostics since both functional and molecular information can be obtained.

Validation and Comparison of Monte Carlo and Finite Element Method in Forward Modeling for Near Infrared Optical Tomography.

Near infrared optical tomography (NIROT) is a non-invasive imaging technique to provide physiological information e.g. the oxygenation of tissue. For image reconstruction in clinical and preclinical scenarios, models to accurately describe light propagation are needed. This work aims to assess the accuracy and efficiency of different models, which paves the way for an optimal design of model-based image reconstruction algorithms in NIROT for realistic tissue geometries and heterogeneities. Two popular simulators were evaluated: the Monte Carlo (MC) method based MCX and the finite element method (FEM) based Toast++. We compared simulated results with experimental data measured on a homogeneous silicone phantom with well-calibrated parameters. The laser light was focused on the center of the phantom surface and images were captured by a CCD camera in both reflection and transmission modes. For transmittance measurements, the two models showed good agreement. Both achieve a cosine similarity of ~99%. In contrast, for reflectance measurements, FEM results deviated more from the measured values than MC, yielding similarity values of 86% and 94%, respectively. This study recommends the use of MC for NIROT in reflection mode and both MC and FEM yield excellent results for transmission mode.

Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation.

OBJECTIVE: 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.

Automated registration of magnetic resonance imaging and optoacoustic tomography data for experimental studies.

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.

Noninvasive detection of acute cerebral hypoxia and subsequent matrix-metalloproteinase activity in a mouse model of cerebral ischemia using multispectral-optoacoustic-tomography.

Oxygen metabolism and matrix metalloproteinases (MMPs) play important roles in the pathophysiology of cerebral ischemia. Using multispectral optoacoustic tomography (MSOT) imaging, we visualized in vivo 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). Ex vivo near-infrared fluorescence imaging of MMP signal in brain slices was used to validate in vivo MSOT measurements. In conclusion, noninvasive MSOT imaging can provide visualization of hemodynamic alterations and MMP activity in a mouse model of cerebral ischemia.

Dynamic Measurement of Tumor Vascular Permeability and Perfusion using a Hybrid System for Simultaneous Magnetic Resonance and Fluorescence Imaging.

PURPOSE: Assessing tumor vascular features including permeability and perfusion is essential for diagnostic and therapeutic purposes. The aim of this study was to compare fluorescence and magnetic resonance imaging (MRI)-based vascular readouts in subcutaneously implanted tumors in mice by simultaneous dynamic measurement of tracer uptake using a hybrid fluorescence molecular tomography (FMT)/MRI system. PROCEDURE: Vascular permeability was measured using a mixture of extravascular imaging agents, GdDOTA and the dye Cy5.5, and perfusion using a mixture of intravascular agents, Endorem and a fluorescent probe (Angiosense). Dynamic fluorescence reflectance imaging (dFRI) was integrated into the hybrid system for high temporal resolution. RESULTS: Excellent correspondence between uptake curves of Cy5.5/GdDOTA and Endorem/Angiosense has been found with correlation coefficients R > 0.98. The two modalities revealed good agreement regarding permeability coefficients and centers-of-gravity of the imaging agent distribution. CONCLUSION: The FMT/dFRI protocol presented is able to accurately map physiological processes and poses an attractive alternative to MRI for characterizing tumor neoangiogenesis.