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'.

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.

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.

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.

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.

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.

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.

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.

T-matrix-based inverse algorithm for morphologic characterization of nonspherical particles using multispectral diffuse optical tomography.

An inverse algorithm is presented for tomographically imaging morphologic characteristics of nonspherical particles in heterogeneous turbid media. The particles are assumed to have spheroidal shapes with random orientations. The inverse algorithm is based on a relationship of the particle scattering spectra, obtained from multispectral diffuse optical tomography, and the size, concentration, and aspect ratio of spheroidal particles through the T-matrix method. The algorithm is implemented based on Tikhonov-Marquardt regularization techniques that minimize the difference between the observed and calculated scattering spectra. Different statistical models are assumed for the suspended nonspherical particles and the performance of the inverse algorithm is tested using noise-corrupted data up to 50% noise added to the observed scattering spectra.

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.

Visible and near-infrared laser radiation in a biological tissue. A forward model for medical imaging by optical tomography.

We present a numerical model for the study of a general, two-dimensional, time-dependent, laser radiation transfer problem in a biological tissue. The model is suitable for many situations, especially when the external laser source is pulsed or continuous. We used a control volume discrete-ordinate method associated with an implicit, three-level, second-order, time-differencing scheme. In medical imaging by laser techniques, this could be an optical tomography forward model. We considered a very thin rectangular biological tissue-like medium submitted to a visible or a near-infrared laser source. Different cases were treated numerically. The source was assumed to be monochromatic and collimated. We used either a continuous source or a short-pulsed source. The transmitted radiance was computed in detector points on the boundaries. Also, the distribution of the internal radiation intensity for different instants is presented. According to the source type, we examined either the steady-state response or the transient response of the medium. First, our model was validated by experimental results from the literature for a homogeneous biological tissue. The space and angular grid independency of our results is shown. Next, the proposed model was used to study changes in transmitted radiation for a homogeneous background medium in which were imbedded two heterogeneous objects. As a last investigation, we studied a multilayered biological tissue. We simulated near-infrared radiation in human skin, fat and muscle. Some results concerning the effects of fat thickness and positions of the detector source on the reflected radiation are presented.

Sensitivity of molecular target detection by multispectral optoacoustic tomography (MSOT).

Optoacoustic imaging is emerging as a noninvasive imaging modality that can resolve optical contrast through several millimeters to centimeters of tissue with the resolution achieved by ultrasound imaging. More recently, applied at multiple illumination wavelengths, multispectral optoacoustic tomography (MSOT) offered the ability to effectively visualize tissue biomarkers by resolving their distinct spectral signatures. While the imaging potential of the method has been demonstrated, little is known on the sensitivity performance in resolving chromophoric and fluorescent substances, such as optical functional and molecular reporters. Herein the authors investigate the detection capacity and physical limits of tomographic optoacoustic imaging by simulating signals originating from absorbing spheres in tissue-mimicking media. To achieve this, a modified optoacoustic equation is employed to incorporate wavelength-dependent propagation and attenuation of diffuse light and ultrasound. The theoretical predictions are further validated in phantom experiments involving Cy5.5, a common near-infrared fluorescent molecular agent.

Investigation of detection limits for diffuse optical tomography systems: I. Theory and experiment.

We present a statistical test using simulated photon migration data and a noise model derived from the hardware of a particular diffuse optical tomography system to predict its detection limits. Our method allows us to assess the spatial distribution of the detection sensitivity of arbitrary geometries and noise without requiring phantom measurements and reconstructions. We determine the minimal detectable lesion size at selected lesion positions and compare the predicted results with phantom measurements carried out in a cup geometry.

Investigation of detection limits for diffuse optical tomography systems: II. Analysis of slab and cup geometry for breast imaging.

Using a statistical (chi-square) test on simulated data and a realistic noise model derived from the system's hardware we study the performance of diffuse optical tomography systems for fluorescence imaging. We compare the predicted smallest size of detectable lesions at various positions in slab and cup geometry and model how detection sensitivity depends on breast compression and lesion fluorescence contrast. Our investigation shows that lesion detection is limited by relative noise in slab geometry and by absolute noise in cup geometry.

Nonlinear reconstruction of absorption and fluorescence contrast from measured diffuse transmittance and reflectance of a compressed-breast-simulating phantom.

We report on the nonlinear reconstruction of local absorption and fluorescence contrast in tissuelike scattering media from measured time-domain diffuse reflectance and transmittance of laser as well as laser-excited fluorescence radiation. Measurements were taken at selected source-detector offsets using slablike diffusely scattering and fluorescent phantoms containing fluorescent heterogeneities. Such measurements simulate in vivo data that would be obtained employing a scanning, time-domain fluorescence mammograph, where the breast is gently compressed between two parallel glass plates, and source and detector optical fibers scan synchronously at various source-detector offsets, allowing the recording of laser and fluorescence mammograms. The diffusion equations modeling the propagation of the laser and fluorescence radiation were solved in frequency domain by the finite element method simultaneously for several modulation frequencies using Fourier transformation and preprocessed experimental data. To reconstruct the concentration of the fluorescent contrast agent, the Born approximation including higher-order reconstructed photon densities at the excitation wavelength was used. Axial resolution was determined that can be achieved by various detection schemes. We show that remission measurements increase the depth resolution significantly.

Phase-contrast diffuse optical tomography for in vivo breast imaging: a two-step method.

We present a two-step reconstruction method that can qualitatively and quantitatively improve the reconstruction of tissue refractive index (RI) distribution by phase-contrast diffuse optical tomography (PCDOT). In this two-step method, we first recover the distribution of tissue absorption and scattering coefficients by conventional diffuse optical tomography to obtain the geometrical information of lesions, allowing the incorporation of geometrical information as a priori in the PCDOT reconstruction using a locally refined mesh. The method is validated by a series of phantom experiments and evaluated using in vivo data from 42 human subjects. The results demonstrate clear contrast of RI between the lesion and the surroundings, making the image interpretation straightforward. The sensitivity and specificity from these 42 cases are both 81% when RI is used as an imaging parameter for distinguishing between malignant and benign lesions.

Time-resolved diffuse optical tomography and its application to in vitro and in vivo imaging.

This work reviews our research during the past several years on time-resolved (TR) near-infrared diffuse optical tomography (DOT). Following an introduction of the measuring modes, two proposed schemes of image reconstruction in TR-DOT are described: one utilizes the full TR data, and the other, referred to as the modified generalized pulse spectrum technique (GPST), uses the featured data extracted from the TR measurement. The performances of the two algorithms in quantitativeness and spatial resolution are comparatively investigated with 2-D simulated data. TR-DOT images are then presented for phantom experiments, which are obtained by using a 16-channel time-correlated single photon counting system, and the factors affecting the quantification of the reconstruction are discussed. Finally, in vitro and in vivo imaging examples are illustrated for validating the capibility of TR-DOT to provide not only the anatomical but also the physiological information of the objects.

Imaging using parallel integrals in optical projection tomography.

We develop and demonstrate improved image-forming optics for optical projection tomography (OPT), with which the parallel integral throughout an object can be obtained. This method results in an improved resolution for OPT images, especially for the cross sections far from the optical axis of the image-forming optics. We find the optimal configuration used in our OPT system by use of a point spread function and simulation technique. The new method is validated by both numerical simulations and experimental results. The spatial resolution of the OPT system presented is approximately 40 microm.

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.