A spatial and cellular distribution of rabies virus infection in the mouse brain revealed by fMOST and single-cell RNA sequencing.

BACKGROUND: Neurotropic virus infection can cause serious damage to the central nervous system (CNS) in both humans and animals. The complexity of the CNS poses unique challenges to investigate the infection of these viruses in the brain using traditional techniques. METHODS: In this study, we explore the use of fluorescence micro-optical sectioning tomography (fMOST) and single-cell RNA sequencing (scRNA-seq) to map the spatial and cellular distribution of a representative neurotropic virus, rabies virus (RABV), in the whole brain. Mice were inoculated with a lethal dose of a recombinant RABV encoding enhanced green fluorescent protein (EGFP) under different infection routes, and a three-dimensional (3D) view of RABV distribution in the whole mouse brain was obtained using fMOST. Meanwhile, we pinpointed the cellular distribution of RABV by utilizing scRNA-seq. RESULTS: Our fMOST data provided the 3D view of a neurotropic virus in the whole mouse brain, which indicated that the spatial distribution of RABV in the brain was influenced by the infection route. Interestingly, we provided evidence that RABV could infect multiple nuclei related to fear independent of different infection routes. More surprisingly, our scRNA-seq data revealed that besides neurons RABV could infect macrophages and the infiltrating macrophages played at least three different antiviral roles during RABV infection. CONCLUSION: This study draws a comprehensively spatial and cellular map of typical neurotropic virus infection in the mouse brain, providing a novel and insightful strategy to investigate the pathogenesis of RABV and other neurotropic viruses.

Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information.

Multimodal imaging is an active branch of research as it has the potential to improve common medical imaging techniques. Diffuse optical tomography (DOT) is an example of a low resolution, functional imaging modality that typically has very low resolution due to the ill-posedness of its underlying inverse problem. Combining the functional information of DOT with a high resolution structural imaging modality has been studied widely. In particular, the combination of DOT with ultrasound (US) could serve as a useful tool for clinicians for the formulation of accurate diagnosis of breast lesions. In this paper, we propose a novel method for US-guided DOT reconstruction using a portable time-domain measurement system. B-mode US imaging is used to retrieve morphological information on the probed tissues by means of a semi-automatical segmentation procedure based on active contour fitting. A two-dimensional to three-dimensional extrapolation procedure, based on the concept of distance transform, is then applied to generate a three-dimensional edge-weighting prior for the regularization of DOT. The reconstruction procedure has been tested on experimental data obtained on specifically designed dual-modality silicon phantoms. Results show a substantial quantification improvement upon the application of the implemented technique. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Spectral unmixing techniques for optoacoustic imaging of tissue pathophysiology.

A key feature of optoacoustic imaging is the ability to illuminate tissue at multiple wavelengths and therefore record images with a spectral dimension. While optoacoustic images at single wavelengths reveal morphological features, in analogy to ultrasound imaging or X-ray imaging, spectral imaging concedes sensing of intrinsic chromophores and externally administered agents that can reveal physiological, cellular and subcellular functions. Nevertheless, identification of spectral moieties within images obtained at multiple wavelengths requires spectral unmixing techniques, which present a unique mathematical problem given the three-dimensional nature of the optoacoustic images. Herein we discuss progress with spectral unmixing techniques developed for multispectral optoacoustic tomography. We explain how different techniques are required for accurate sensing of intrinsic tissue chromophores such as oxygenated and deoxygenated haemoglobin versus extrinsically administered photo-absorbing agents and nanoparticles. Finally, we review recent developments that allow accurate quantification of blood oxygen saturation (sO2) by transforming and solving the sO2 estimation problem from the spatial to the spectral domain.This article is part of the themed issue 'Challenges for chemistry in molecular imaging'.

Reconstruction Method for Optical Tomography Based on the Linearized Bregman Iteration with Sparse Regularization.

Optical molecular imaging is a promising technique and has been widely used in physiology, and pathology at cellular and molecular levels, which includes different modalities such as bioluminescence tomography, fluorescence molecular tomography and Cerenkov luminescence tomography. The inverse problem is ill-posed for the above modalities, which cause a nonunique solution. In this paper, we propose an effective reconstruction method based on the linearized Bregman iterative algorithm with sparse regularization (LBSR) for reconstruction. Considering the sparsity characteristics of the reconstructed sources, the sparsity can be regarded as a kind of a priori information and sparse regularization is incorporated, which can accurately locate the position of the source. The linearized Bregman iteration method is exploited to minimize the sparse regularization problem so as to further achieve fast and accurate reconstruction results. Experimental results in a numerical simulation and in vivo mouse demonstrate the effectiveness and potential of the proposed method.

Microperimetría en la cirugía del agujero macular idiopático / Microperimetry in the idiopathic macular hole surgery

Objetivo: demostrar la utilidad de la microperimetría pre y posoperatoria en operados de agujero macular idiopático entre 2010-2012, en el Instituto Cubano de Oftalmología Ramón Pando Ferrer. Métodos: en una investigación longitudinal-prospectiva de 17 operados de agujero macular, se estudiaron la agudeza visual corregida y la microperimetría preoperatoria y posoperatoria. Se estableció como mejoría de la agudeza visual corregida si mejoraban dos líneas o más y como mejoría de la microperimetría si cumplían al menos dos de los parámetros: desaparición de escotoma absoluto, desaparición de escotoma relativo y mejoría de la sensibilidad retineana. Se efectuó el examen oftalmológico y la tomografía óptica coherente pre y posoperatorios, en los que se precisó la presencia y el cierre del agujero. Resultados: en la microperimetría preoperatoria presentaban escotoma absoluto el 64,71 por ciento, y escotoma relativo el 94,12 por ciento; la sensibilidad retiniana media fue de 8,40 ± 4,39 y la fijación era estable en el 81,82 por ciento de los pacientes. La sensibilidad retineana media preoperatoria presentó significación estadística respecto a la mejoría de la agudeza visual (p= 0,012). De los pacientes con cierre del agujero (64,71 por ciento), el 72,73 por ciento mejoró la agudeza visual (p= 0,006), y el 54,55 por ciento mejoró la microperimetría (p= 0,002). Se encontró significación estadística entre el cierre del agujero macular y la mejoría de la agudeza visual corregida (p= 0,009) y entre el cierre y la mejoría de la microperimetría (p= 0,043). Conclusiones: la sensibilidad retineana preoperatoria puede constituir un factor predictivo para la recuperación funcional del agujero macular. La recuperación de la agudeza visual tras el cierre del agujero conlleva la mejoría de la microperimetría. Esta última constituye un punto de apoyo para continuar la recuperación funcional(AU)

Objetive: to demonstrate utility of microperimetry to the surgery of idiopathic macular hole, among 2010-2012, in the "Ramón Pando Ferrer" Cuban Ophthalmology Institute. Methods: a longitudinal-prospective study of 17 patients who underwent surgery for idiopathic macular hole was carried out. The corrected visual acuity and microperimetry were studied before and after the surgery. If patient improved 2 lines or more of corrected visual acuity and if they having 2 of the items: disappearance of absolute scotoma, disappearance of scotoma relative, improvement of retinal sensitivity; were established improvement of them. Oftalmology exam and optic coherent tomography were studied before and after surgery, specifying the presence and close of the hole. Results: 64,71 percent of patients presented absolute scotoma and 94,12 percent of them had relative scotoma. The mean retinal sensitivity was 8,40 ± 4,39 and fixation was stable in 81,82 percent of them. Better preoperative mean retinal sensitivity showed statistical significance to best corrected visual acuity (p= 0,012). 72,73 percent of patients with close surgical of the hole (64,71 percent) improved corrected visual acuity (p= 0,006), and 54,55 percent of them improved the microperimetry (p= 0,002). The anatomical closing of hole showed statistical significance for the improvement of corrected visual acuity (p=0,009) and for the improvement of microperimetry (p= 0,043). Conclusions: the preoperative retinal sensitivity can predict the functional recovery of the macular hole. After close of the hole, the recovery of visual acuity can precede to improvement of microperimetry. Microperimetry can constitute a support point to continue the functional recovery(AU)

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available.

Statistical analysis of high density diffuse optical tomography.

High density diffuse optical tomography (HD-DOT) is a noninvasive neuroimaging modality with moderate spatial resolution and localization accuracy. Due to portability and wear-ability advantages, HD-DOT has the potential to be used in populations that are not amenable to functional magnetic resonance imaging (fMRI), such as hospitalized patients and young children. However, whereas the use of event-related stimuli designs, general linear model (GLM) analysis, and imaging statistics are standardized and routine with fMRI, such tools are not yet common practice in HD-DOT. In this paper we adapt and optimize fundamental elements of fMRI analysis for application to HD-DOT. We show the use of event-related protocols and GLM de-convolution analysis in un-mixing multi-stimuli event-related HD-DOT data. Statistical parametric mapping (SPM) in the framework of a general linear model is developed considering the temporal and spatial characteristics of HD-DOT data. The statistical analysis utilizes a random field noise model that incorporates estimates of the local temporal and spatial correlations of the GLM residuals. The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory. These analysis tools provide access to a wide range of experimental designs necessary for the study of the complex brain functions. In addition, they provide a foundation for understanding and interpreting HD-DOT results with quantitative estimates for the statistical significance of detected activation foci.

Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head.

One of the main challenges in functional diffuse optical tomography (DOT) is to accurately recover the depth of brain activation, which is even more essential when differentiating true brain signals from task-evoked artifacts in the scalp. Recently, we developed a depth-compensated algorithm (DCA) to minimize the depth localization error in DOT. However, the semi-infinite model that was used in DCA deviated significantly from the realistic human head anatomy. In the present work, we incorporated depth-compensated DOT (DC-DOT) with a standard anatomical atlas of human head. Computer simulations and human measurements of sensorimotor activation were conducted to examine and prove the depth specificity and quantification accuracy of brain atlas-based DC-DOT. In addition, node-wise statistical analysis based on the general linear model (GLM) was also implemented and performed in this study, showing the robustness of DC-DOT that can accurately identify brain activation at the correct depth for functional brain imaging, even when co-existing with superficial artifacts.

Flux density calibration in diffuse optical tomographic systems.

The solution of the forward equation that models the transport of light through a highly scattering tissue material in diffuse optical tomography (DOT) using the finite element method gives flux density (Φ) at the nodal points of the mesh. The experimentally measured flux (Umeasured) on the boundary over a finite surface area in a DOT system has to be corrected to account for the system transfer functions (R) of various building blocks of the measurement system. We present two methods to compensate for the perturbations caused by R and estimate true flux density (Φ) from Umeasuredcal. In the first approach, the measurement data with a homogeneous phantom (Umeasuredhomo) is used to calibrate the measurement system. The second scheme estimates the homogeneous phantom measurement using only the measurement from a heterogeneous phantom, thereby eliminating the necessity of a homogeneous phantom. This is done by statistically averaging the data (Umeasuredhetero) and redistributing it to the corresponding detector positions. The experiments carried out on tissue mimicking phantom with single and multiple inhomogeneities, human hand, and a pork tissue phantom demonstrate the robustness of the approach.

Diffuse optical tomography in the presence of a chest wall.

Diffuse optical tomography (DOT) has been employed to derive spatial maps of physiologically important chromophores in the human breast, but the fidelity of these images is often compromised by boundary effects such as those due to the chest wall. We explore the image quality in fast, data-intensive analytic and algebraic linear DOT reconstructions of phantoms with subcentimeter target features and large absorptive regions mimicking the chest wall. Experiments demonstrate that the chest wall phantom can introduce severe image artifacts. We then show how these artifacts can be mitigated by exclusion of data affected by the chest wall. We also introduce and demonstrate a linear algebraic reconstruction method well suited for very large data sets in the presence of a chest wall.

Ultrasound modulated imaging of luminescence generated within a scattering medium.

Ultrasound modulated optical tomography modulates scattered light within tissue by deterministically altering the optical properties of the sample with the ultrasonic pressure. This allows the light to be "tagged" and the degradation in spatial resolution associated with light scattering to be reduced. To our knowledge, this is the first demonstration of ultrasound modulated imaging of light generated within a scattering medium without an external light source. The technique has the potential to improve the spatial resolution of chemi- or bioluminescence imaging of tissue. Experimental results show that ultrasound modulated luminescence imaging can resolve two chemiluminescent objects separated by 5 mm at a 7 mm depth within a tissue phantom with a scattering coefficient of 30 cm-1. The lateral resolution is estimated to be 3 mm. Monte Carlo simulations indicate that, with the current system signal to noise ratio, it is feasible to apply the approach to bioluminescence imaging when the concentration of bacteria in the animal organ is above 3.4×105/µL.

Fluorescence molecular tomography of an animal model using structured light rotating view acquisition.

In recent years, an increasing effort has been devoted to the optimization of acquisition and reconstruction schemes for fluorescence molecular tomography (FMT). In particular, wide-field structured illumination and compression of the measured images have enabled significant reduction of the data set and, consequently, a decrease in both acquisition and processing times. FMT based on this concept has been recently demonstrated on a cylindrical phantom with a rotating-view scheme that significantly increases the reconstruction quality. In this work, we generalize the rotating-view scheme to arbitrary geometries and experimentally demonstrate its applicability to murine models. To the best of our knowledge this is the first time that FMT based on a rotating-view scheme with structured illumination and image compression has been applied to animals.

Parallel acoustic delay lines for photoacoustic tomography.

Achieving real-time photoacoustic (PA) tomography typically requires multi-element ultrasound transducer arrays and their associated multiple data acquisition (DAQ) electronics to receive PA waves simultaneously. We report the first demonstration of a photoacoustic tomography (PAT) system using optical fiber-based parallel acoustic delay lines (PADLs). By employing PADLs to introduce specific time delays, the PA signals (on the order of a few micro seconds) can be forced to arrive at the ultrasonic transducers at different times. As a result, time-delayed PA signals in multiple channels can be ultimately received and processed in a serial manner with a single-element transducer, followed by single-channel DAQ electronics. Our results show that an optically absorbing target in an optically scattering medium can be photoacoustically imaged using the newly developed PADL-based PAT system. Potentially, this approach could be adopted to significantly reduce the complexity and cost of ultrasonic array receiver systems.

Artefact reduction in optoacoustic tomographic imaging by estimating the distribution of acoustic scatterers.

The quality of optoacoustic tomographic reconstructions can be severely affected by acoustic reflections or scattering arising at interfaces of highly mismatched organs, such as bones, lungs, or other air-containing cavities. We present a procedure to reduce the associated artefacts based on estimation of the acoustic scatterers distribution within the imaged object. Signals generated by a strong optical absorber are processed and used in a weighted back-projection algorithm. Experimental results in a tissue-mimicking phantom clearly demonstrate improved performance as compared to the case in which no information on the distribution of acoustic scatterers is available.

The structure of postural disorders and spinal deformities in age and gender according to computer optical topography.

Since 1996 in Russia the screening of the child population is carried out using the diagnostic system TODP. The purpose of the study - to explore gender and age features of the postural formation. The most significant differences in the postural formation between boys and girls have been identified in the sagittal plane. A strong correlation between the development of structural scoliosis and growth of the body for both genders was revealed in the frontal plane.

High dynamic range optical projection tomography (HDR-OPT).

Traditional optical projection tomography (OPT) acquires a single image at each rotation angle, thereby suffering from limitations in CCD dynamic range; this conventional usage cannot resolve features in samples with highly heterogeneous absorption, such as in small animals with organs of varying size. We present a novel technique, applying multiple-exposure high dynamic range (HDR) imaging to OPT, and demonstrate its ability to resolve fine details in zebrafish embryos, without complicated chemical clearing. We implement the tomographic reconstruction algorithm on the GPU, yielding a performance increase of two orders of magnitude. These features give our method potential application in high-throughput, high-resolution in vivo 3D imaging.

Joint L1 and total variation regularization for fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) is an imaging modality that exploits the specificity of fluorescent biomarkers to enable 3D visualization of molecular targets and pathways in vivo in small animals. Owing to the high degree of absorption and scattering of light through tissue, the FMT inverse problem is inherently ill-conditioned making image reconstruction highly susceptible to the effects of noise and numerical errors. Appropriate priors or penalties are needed to facilitate reconstruction and to restrict the search space to a specific solution set. Typically, fluorescent probes are locally concentrated within specific areas of interest (e.g., inside tumors). The commonly used L(2) norm penalty generates the minimum energy solution, which tends to be spread out in space. Instead, we present here an approach involving a combination of the L(1) and total variation norm penalties, the former to suppress spurious background signals and enforce sparsity and the latter to preserve local smoothness and piecewise constancy in the reconstructed images. We have developed a surrogate-based optimization method for minimizing the joint penalties. The method was validated using both simulated and experimental data obtained from a mouse-shaped phantom mimicking tissue optical properties and containing two embedded fluorescent sources. Fluorescence data were collected using a 3D FMT setup that uses an EMCCD camera for image acquisition and a conical mirror for full-surface viewing. A range of performance metrics was utilized to evaluate our simulation results and to compare our method with the L(1), L(2) and total variation norm penalty-based approaches. The experimental results were assessed using the Dice similarity coefficients computed after co-registration with a CT image of the phantom.

Reconstruction for limited-projection fluorescence molecular tomography based on projected restarted conjugate gradient normal residual.

Limited-projection fluorescence molecular tomography (FMT) can greatly reduce the acquisition time, which is suitable for resolving fast biology processes in vivo but suffers from severe ill-posedness because of the reconstruction using only limited projections. To overcome the severe ill-posedness, we report a reconstruction method based on the projected restarted conjugate gradient normal residual. The reconstruction results of two phantom experiments demonstrate that the proposed method is feasible for limited-projection FMT.

Early-photon fluorescence tomography of a heterogeneous mouse model with the telegraph equation.

In this study, we investigate the performance of early-photon fluorescence tomography based on a heterogeneous mouse model. The telegraph equation is used to accurately describe the propagation of light in tissues at short times. The optimal time gate for early photons is determined by singular value analysis at first. Then, fluorescent targets located in different organs of the mouse model are investigated. The simulation results demonstrate that the reconstructed tomographic images based on early photons yield improvement in spatial resolution and quantification than the quasi-CW measurements. Meanwhile, compared with the homogeneous model, the use of the heterogeneous model can improve the accuracy of fluorescence distribution and quantification in early-photon fluorescence tomography.

Monte Carlo fluorescence microtomography.

Fluorescence microscopy allows real-time monitoring of optical molecular probes for disease characterization, drug development, and tissue regeneration. However, when a biological sample is thicker than 1 mm, intense scattering of light would significantly degrade the spatial resolution of fluorescence microscopy. In this paper, we develop a fluorescence microtomography technique that utilizes the Monte Carlo method to image fluorescence reporters in thick biological samples. This approach is based on an l(0)-regularized tomography model and provides an excellent solution. Our studies on biomimetic tissue scaffolds have demonstrated that the proposed approach is capable of localizing and quantifying the distribution of optical molecular probe accurately and reliably.