Total light approach of time-domain fluorescence diffuse optical tomography

Fast and robust reconstruction algorithm for fluorescence diffuse optical tomography assuming a cuboid target

A fast algorithm for fluorescence diffuse optical tomography is proposed. The algorithm is robust against the choice of initial guesses. We estimate the position of a fluorescent target by assuming a cuboid (rectangular parallelepiped) for the fluorophore target. The proposed numerical algorithm is verified by a numerical experiment and an experiment with a meat phantom. The target position is reconstructed with a cuboid from measurements in the time domain. Moreover, the long-time behavior of the emission light is investigated making use of the analytical solution to the diffusion equation.

Time-Domain Near-Infrared Spectroscopy and Imaging: A Review

This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.

Overview of diffuse optical tomography and its clinical applications

Near-infrared diffuse optical tomography (DOT), one of the most sophisticated optical imaging techniques for observations through biological tissue, allows 3-D quantitative imaging of optical properties, which include functional and anatomical information. With DOT, it is expected to be possible to overcome the limitations of conventional near-infrared spectroscopy (NIRS) as well as offering the potential for diagnostic optical imaging. However, DOT has been under development for more than 30 years, and the difficulties in development are attributed to the fact that light is strongly scattered and that diffusive photons are used for the image reconstruction. The DOT algorithm is based on the techniques of inverse problems. The radiative transfer equation accurately describes photon propagation in biological tissue, while, because of its high computation load, the diffusion equation (DE) is often used as the forward model. However, the DE is invalid in low-scattering and/or highly absorbing regions and in the vicinity of light sources. The inverse problem is inherently ill-posed and highly undetermined. Here, we first summarize NIRS and then describe various approaches in the efforts to develop accurate and efficient DOT algorithms and present some examples of clinical applications. Finally, we discuss the future prospects of DOT.

Fluorescence lifetime measurements in heterogeneous scattering medium

Fluorescence lifetime in heterogeneous multiple light scattering systems is analyzed by an algorithm without solving the diffusion or radiative transfer equations. The algorithm assumes that the optical properties of medium are constant in the excitation and emission wavelength regions. If the assumption is correct and the fluorophore is a single species, the fluorescence lifetime can be determined by a set of measurements of temporal point-spread function of the excitation light and fluorescence at two different concentrations of the fluorophore. This method is not dependent on the heterogeneity of the optical properties of the medium as well as the geometry of the excitation–detection on an arbitrary shape of the sample. The algorithm was validated by an indocyanine green fluorescence in phantom measurements and demonstrated by an in vivo measurement.

Reconstruction of localized fluorescent target from multi-view continuous-wave surface images of small animal with lp sparsity regularization

Fluorescence diffuse optical tomography using a multi-view continuous-wave and non-contact measurement system and an algorithm incorporating the lp (0 < p ≤ 1) sparsity regularization reconstructs a localized fluorescent target in a small animal. The measurement system provides a total of 25 fluorescence surface 2D-images of an object, which are acquired by a CCD camera from five different angles of view with excitation from five different angles. Fluorescence surface emissions from five different angles of view are simultaneously imaged on the CCD sensor, thus leading to fast acquisition of the 25 images within three minutes. The distributions of the fluorophore are reconstructed by solving the inverse problem based on the photon diffusion equations. In the reconstruction process incorporating the lp sparsity regularization, the regularization term is reformulated as a differentiable function for gradient-based non-linear optimization. Numerical simulations and phantom experiments show that the use of the lp sparsity regularization improves the localization of the target and quantitativeness of the fluorophore concentration. A mouse experiment demonstrates that a localized fluorescent target in a mouse is successfully reconstructed.

Phantom and mouse experiments of time-domain fluorescence tomography using total light approach

Phantom and mouse experiments of time-domain fluorescence tomography were conducted to demonstrate the total light approach which was previously proposed by authors. The total light approach reduces the computation time to solve the forward model for light propagation. Time-resolved temporal profiles were acquired for cylindrical phantoms having single or double targets containing indocyanine green (ICG) solutions. The reconstructed images of ICG concentration reflected the true distributions of ICG concentration with a spatial resolution of about 10 mm. In vivo experiments were conducted using a mouse in which an ICG capsule was embedded beneath the skin in the abdomen. The reconstructed image of the ICG concentration again reflected the true distribution of ICG although artifacts due to autofluorescence appeared in the vicinity of the skin. The effectiveness of the total light approach was demonstrated by the phantom and mouse experiments.

Weighted depth compensation algorithm for fluorescence molecular tomography reconstruction

In fluorescence molecular tomography (FMT), diffuse-light measurements are obtained from a series of source-detector pairs placed on the boundary of the medium. The sensitivity of measurements deteriorates quickly with increased distance from the sources and detectors and therefore yields poor depth quantitative recovery. A depth compensation algorithm is presented in this paper to reconstruct fluorescent inclusions in deep tissues. Two weight matrixes are employed to level off sensitivity differences and enhance prominent elements of the solution. Results of numerical and phantom experiments demonstrate that both relative quantitation and spatial resolution of FMT are improved for inclusions at different depths.

Towards the next generation of near-infrared spectroscopy

Although near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, it has also been developing into a useful tool for neuroimaging studies (functional NIRS). Over the past 30 years, technology has developed and NIRS has found a wide range of applications. However, the accuracy and reliability of NIRS have not yet been widely accepted, mainly because of the difficulties in selective and quantitative detection of signals arising in cerebral tissue, which subject the use of NIRS to a number of practical restrictions. This review summarizes the strengths and advantages of NIRS over other neuroimaging modalities and demonstrates specific examples. The issues of selective quantitative measurement of cerebral haemoglobin during brain activation are also discussed, together with the problems of applying the methods of functional magnetic resonance imaging data analysis to NIRS data analysis. Finally, near-infrared optical tomography--the next generation of NIRS--is described as a potential technique to overcome the limitations of NIRS.

A three-dimensional finite element model and image reconstruction algorithm for time-domain fluorescence imaging in highly scattering media

In this work, development and evaluation of a three-dimensional (3D) finite element model (FEM) based on the diffusion approximation of time-domain (TD) near-infrared fluorescence light transport in biological tissue is presented. This model allows both excitation and fluorescence temporal point-spread function (TPSF) data to be generated for heterogeneous scattering and absorbing media of arbitrary geometry. The TD FEM is evaluated via comparisons with analytical and Monte Carlo (MC) calculations and is shown to provide a quantitative accuracy which has less than 0.72% error in intensity and less than 37 ps error for mean time. The use of the Born-Ratio normalized data is demonstrated to reduce data mismatch between MC and FEM to less than 0.22% for intensity and less than 22 ps in mean time. An image reconstruction framework, based on a 3D FEM formulation, is outlined and simulation results based on a heterogeneous mouse model with a source of fluorescence in the pancreas is presented. It is shown that using early photons (i.e. the photons detected within the first 200 ps of the TPSF) improves the spatial resolution compared to using continuous-wave signals. It is also demonstrated, as expected, that the utilization of two time gates (early and latest photons) can improve the accuracy both in terms of spatial resolution and recovered contrast.

Reconstruction of fluorescence/bioluminescence sources in biological medium with spatial filter

We propose a new method for reconstruction of emitting source distributions by use of a spatial filter and a successive updating process of the forward model for fluorescence/bioluminescence diffuse optical tomography. The spatial filter transforms a set of the measurement data to a single source strength at a position of interest, and the forward model is updated by use of the estimated source strengths. This updating process ignores the dispensable source positions from reconstruction according to the reconstructed source distribution, and the spatial resolution of the reconstructed image is improved. The estimated sources are also used for the reduction of artifacts induced by noises based on the singular value decomposition. Some numerical experiments show the advantages of the proposed method by comparing the present results with those obtained by the conventional methods of the least squares method nd Algebraic Reconstruction Technique. Finally the criteria for practical use of the method are quantitatively presented by the simulations for 2D and 3D geometries.