Fast multispectral diffuse optical tomography system for in vivo three-dimensional imaging of seizure dynamics

We describe a multispectral continuous-wave diffuse optical tomography (DOT) system that can be used for in vivo three-dimensional (3-D) imaging of seizure dynamics. Fast 3-D data acquisition is realized through a time multiplexing approach based on a parallel lighting configuration--our system can achieve 0.12 ms per source per wavelength and up to a 14 Hz sampling rate for a full set of data for 3-D DOT image reconstruction. The system is validated using both static and dynamic tissue-like phantoms. An initial in vivo experiment using a rat model of seizure is also demonstrated.     

Improvement of image quality in diffuse optical tomography by use of full time-resolved data

In the field of diffuse optical tomography (DOT), it is widely accepted that time-resolved (TR) measurement can provide the richest information on photon migration in a turbid medium, such as biological tissue. However, the currently available image reconstruction algorithms for TR DOT are based mostly on the cw component or some featured data types of original temporal profiles, which are related to the solution of a time-independent diffusion equation. Although this methodology can greatly simplify the reconstruction process, it suffers from low spatial resolution and poor quantitativeness owing to the limitation of effectively applicable data types. To improve image quality, it has been argued that exploiting the full TR data is essential. We propose implementation of a DOT algorithm by using full TR data and furthermore a variant algorithm with time slices of TR data to alleviate the computational complexity and enhance noise robustness. Compared with those algorithms where the featured data types are used, our evaluations on the spatial resolution and quantitativeness show that a significant improvement in imaging quality can be achieved when full TR data are used, which convinces the DOT community of the potential advantage of the TR domain over cw and frequency domains.     

Pseudo-time particle filtering for diffuse optical tomography

We recast the reconstruction problem of diffuse optical tomography (DOT) in a pseudo-dynamical framework and develop a method to recover the optical parameters using particle filters, i.e., stochastic filters based on Monte Carlo simulations. In particular, we have implemented two such filters, viz., the bootstrap (BS) filter and the Gaussian-sum (GS) filter and employed them to recover optical absorption coefficient distribution from both numerically simulated and experimentally generated photon fluence data. Using either indicator functions or compactly supported continuous kernels to represent the unknown property distribution within the inhomogeneous inclusions, we have drastically reduced the number of parameters to be recovered and thus brought the overall computation time to within reasonable limits. Even though the GS filter outperformed the BS filter in terms of accuracy of reconstruction, both gave fairly accurate recovery of the height, radius, and location of the inclusions. Since the present filtering algorithms do not use derivatives, we could demonstrate accurate contrast recovery even in the middle of the object where the usual deterministic algorithms perform poorly owing to the poor sensitivity of measurement of the parameters. Consistent with the fact that the DOT recovery, being ill posed, admits multiple solutions, both the filters gave solutions that were verified to be admissible by the closeness of the data computed through them to the data used in the filtering step (either numerically simulated or experimentally generated).     

Practical fully three-dimensional reconstruction algorithms for diffuse optical tomography

We have developed an efficient fully three-dimensional (3D) reconstruction algorithm for diffuse optical tomography (DOT). The 3D DOT, a severely ill-posed problem, is tackled through a pseudodynamic (PD) approach wherein an ordinary differential equation representing the evolution of the solution on pseudotime is integrated that bypasses an explicit inversion of the associated, ill-conditioned system matrix. One of the most computationally expensive parts of the iterative DOT algorithm, the reevaluation of the Jacobian in each of the iterations, is avoided by using the adjoint-Broyden update formula to provide low rank updates to the Jacobian. In addition, wherever feasible, we have also made the algorithm efficient by integrating along the quadratic path provided by the perturbation equation containing the Hessian. These algorithms are then proven by reconstruction, using simulated and experimental data and verifying the PD results with those from the popular Gauss-Newton scheme. The major findings of this work are as follows: (i) the PD reconstructions are comparatively artifact free, providing superior absorption coefficient maps in terms of quantitative accuracy and contrast recovery; (ii) the scaling of computation time with the dimension of the measurement set is much less steep with the Jacobian update formula in place than without it; and (iii) an increase in the data dimension, even though it renders the reconstruction problem less ill conditioned and thus provides relatively artifact-free reconstructions, does not necessarily provide better contrast property recovery. For the latter, one should also take care to uniformly distribute the measurement points, avoiding regions close to the source so that the relative strength of the derivatives for measurements away from the source does not become insignificant.     

Time-resolved diffuse optical tomographic imaging for the provision of both anatomical and functional information about biological tissue

We present in vivo images of near-infrared (NIR) diffuse optical tomography (DOT) of human lower legs and forearm to validate the dual functions of a time-resolved (TR) NIR DOT in clinical diagnosis, i.e., to provide anatomical and functional information simultaneously. The NIR DOT system is composed of time-correlated single-photon-counting channels, and the image reconstruction algorithm is based on the modified generalized pulsed spectral technique, which effectively incorporates the TR data with reasonable computation time. The reconstructed scattering images of both the lower legs and the forearm revealed their anatomies, in which the bones were clearly distinguished from the muscles. In the absorption images, some of the blood vessels were observable. In the functional imaging, a subject was requested to do handgripping exercise to stimulate physiological changes in the forearm tissue. The images of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentration changes in the forearm were obtained from the differential images of the absorption at three wavelengths between the exercise and the rest states, which were reconstructed with a differential imaging scheme. These images showed increases in both blood volume and oxyhemoglobin concentration in the arteries and simultaneously showed hypoxia in the corresponding muscles. All the results have demonstrated the capability of TR NIR DOT by reconstruction of the absolute images of the scattering and the absorption with a high spatial resolution that finally provided both the anatomical and functional information inside bulky biological tissues.     

Robust inference of baseline optical properties of the human head with three-dimensional segmentation from magnetic resonance imaging

We model the capability of a small (6-optode) time-resolved diffuse optical tomography (DOT) system to infer baseline absorption and reduced scattering coefficients of the tissues of the human head (scalp, skull, and brain). Our heterogeneous three-dimensional diffusion forward model uses tissue geometry from segmented magnetic resonance (MR) data. Handling the inverse problem by use of Bayesian inference and introducing a realistic noise model, we predict coefficient error bars in terms of detected photon number and assumed model error. We demonstrate the large improvement that a MR-segmented model can provide: 2-10% error in brain coefficients (for 2 x 10(6) photons, 5% model error). We sample from the exact posterior and show robustness to numerical model error. This opens up the possibility of simultaneous DOT and MR for quantitative cortically constrained functional neuroimaging.     

Optical tomographic image reconstruction from ultrafast time-sliced transmission measurements

Optical imaging and localization of objects inside a highly scattering medium, such as a tumor in the breast, is a challenging problem with many practical applications. Conventional imaging methods generally provide only two-dimensional (2-D) images of limited spatial resolution with little diagnostic ability. Here we present an inversion algorithm that uses time-resolved transillumination measurements in the form of a sequence of picosecond-duration intensity patterns of transmitted ultrashort light pulses to reconstruct three-dimensional (3-D) images of an absorbing object located inside a slab of a highly scattering medium. The experimental arrangement used a 3-mm-diameter collimated beam of 800-nm, 150-fs, 1-kHz repetition rate light pulses from a Ti:sapphire laser and amplifier system to illuminate one side of the slab sample. An ultrafast gated intensified camera system that provides a minimum FWHM gate width of 80 ps recorded the 2-D intensity patterns of the light transmitted through the opposite side of the slab. The gate position was varied in steps of 100 ps over a 5-ns range to obtain a sequence of 2-D transmitted light intensity patterns of both less-scattered and multiple-scattered light for image reconstruction. The inversion algorithm is based on the diffusion approximation of the radiative transfer theory for photon transport in a turbid medium. It uses a Green s function perturbative approach under the Rytov approximation and combines a 2-D matrix inversion with a one-dimensional Fourier-transform inversion to achieve speedy 3-D image reconstruction. In addition to the lateral position, the method provides information about the axial position of the object as well, whereas the 2-D reconstruction methods yield only lateral position.     

Quantitative photoacoustic tomography from boundary pressure measurements: noniterative recovery of optical absorption coefficient from the reconstructed absorbed energy map

We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.     

Three-dimensional unconstrained and constrained image-reconstruction techniques applied to fluorescence, frequency-domain photon migration

The development of near-infrared (NIR) optical imaging for biomedical optical imaging is hampered by the computational intensiveness of large-scale three-dimensional (3-D) image reconstruction and the potential lack of endogenous contrast for detection of relevant tissue features. In this contribution the inverse optical imaging problem is formulated in three dimensions in a noncompressive geometry as a simple-bound constrained minimization problem in order to recover the interior fluorescence properties of exogenous contrast agent from frequency-domain photon migration measurements at the boundary. The solution of the forward optical diffusion problem for the frustum shape containing fluorescence inclusions of 10:1 contrast is accomplished by use of the Galerkin finite-element formulation. The inverse approach employs the truncated Newton method with trust region and a modification of automatic reverse differentiation to speed the computation of the optimization problem. The image-reconstruction results confirm that the constrained minimization may offer a more logical approach for the 3-D optical imaging problem than unconstrained optimization.     

Characterisation of PRESAGE: A new 3-D radiochromic solid polymer dosemeter for ionising radiation

For the past 50 years there has been interest in developing 3-D dosemeters for ionising radiation. Particular emphasis has been put on those dosemeters that change their optical properties in proportion to the absorbed dose. Many of the dosemeters that have been evaluated have had limitations such as lack of transparency, diffusion of the image of the dose distribution or poor stability of baseline optical density. Many of these performance limitations have been overcome by the development of PRESAGE, an optically clear polyurethane-based radiochromic 3-D dosemeter. The solid PRESAGE dosemeter is formulated with a free radical initiator and a leuco dye and it does not require a container to maintain its shape. The polyurethane matrix is tissue equivalent and prevents the diffusion of the dose distribution image. There is a linear dose-response, which is independent of both photon energy and dose rate. Simple precautions such as preventing long-term exposure to additional ionising radiation including ultraviolet and controlling storage temperatures prevent the bleaching of the radiochromic response field within the irradiated dosemeter.     

Simultaneous mapping of absorption and scattering coefficients from a three-dimensional model of time-resolved optical tomography

A Newton-Raphson inversion algorithm has been extended for simultaneous absorption and scattering reconstruction of fully three-dimensional (3D) diffuse optical tomographic imaging from time-resolved measurements. The proposed algorithm is derived from the efficient computation of the Jacobian matrix of the forward model and uses either the algebraic reconstruction technique or truncated singular-value decomposition as the linear inversion tool. Its validation was examined with numerically simulated data from 3-D finite-element discretization models of tissuelike phantoms, with several combinations of geometric and optical properties, as well as two commonly used source-detector configurations. Our results show that the fully 3-D image reconstruction of an object can be achieved with reasonable quality when volumetric light propagation in tissues is considered, and temporal information from the measurements can be effectively employed. Also, we investigated the conditions under which 3-D issues could be approximately addressed with two-dimensional reconstruction algorithms and further demonstrated that these conditions are seldom predictable or attainable in practice. Thus the application of 3-D algorithms to realistic situations is necessary.     

Diffuse optical tomography guided quantitative fluorescence molecular tomography

We describe a method that combines fluorescence molecular tomography (FMT) with diffuse optical tomography (DOT), which allows us to study the impact of heterogeneous optical property distribution on FMT, an issue that has not been systemically studied. Both numerical simulations and phantom experiments were performed based on our finite-element reconstruction algorithms. The experiments were conducted using a noncontact optical fiber free, multiangle transmission system. In both the simulations and experiments, a fluorescent target was embedded in an optically heterogeneous background medium. The simulation results clearly suggest the necessity of considering the absorption coefficient (mu(a)) and reduced scattering coefficient (mu'(s)) distributions for quantitatively accurate FMT, especially in terms of the accuracy of reconstructed fluorophore absorption coefficient (mu(a(x-->m))). Subsequent phantom experiments with an indocyanine green (ICG)-containing target confirm the simulation findings. In addition, we performed a series of phantom experiments with low ICG concentration (0.1, 0.2, 0.4, 0.6 and 1.0 microM) in the target to systematically evaluate the quantitative accuracy of our FMT approach. The results indicate that, with the knowledge of optical property distribution, the accuracy of the recovered fluorophore concentration is improved significantly over that without such a priori information. In particular absolute value of mu(a(x-->m) ) from our DOT guided FMT are quantitatively consistent with that obtained using spectroscopic methods.     

Improved accuracy of reconstructed diffuse optical tomographic images by means of spatial deconvolution: two-dimensional quantitative characterization

Systematic characterization studies are presented, relating to a previously reported spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. In simulation results that are presented, this deconvolution operation has been applied to two-dimensional DOT images reconstructed by solving a first-order perturbation equation. Under study was the effect on algorithm performance of control parameters in the measurement (number and spatial distribution of sources and detectors, presence of noise, and presence of systematic error), target (medium shape; and number, location, size, and contrast of inclusions), and computational (number of finite-element-method mesh nodes, length of filter-generating linear system, among others) parameter spaces associated with computation and the use of the deconvolution operators. Substantial improvements in reconstructed image quality, in terms of recovered inclusion location, size, and contrast, are found in all cases. A finding of practical importance is that the method is robust to appreciable differences between the optical coefficients of the media used for filter generation and those of the target media to which the filters are subsequently applied.     

Restoration of mandibular bone defects with demineralized bone matrix combined with three-dimensional cultured bone marrow-derived mesenchymal stem cells in minipig models

Mandibular defects, caused by congenital, pathological or iatrogenic insults, can significantly affect patient quality of life. The reconstruction of mandible has recently gained the interest of clinical and tissue engineering researchers. The purpose of this study was to evaluate the effectiveness of three-dimensional (3-D) cultured autologous grafts prepared using bone marrow-derived mesenchymal stem cells (BMSCs) combined with demineralized bone matrix (DBM) scaffolds for the restoration of mandibular defects. Cylindrical defects were created in the mandibular body of minipigs and filled with 3D-cultured BMSCs/DBM autografts, 2D-cultured BMSCs/DBM autografts, DBM material (without cells), or were left unfilled (blank). Using computed tomographic (CT) imaging and histological staining, we found that treatment of mandibular defects using 3-D cultured BMSCs/DBM autografts offered improvements in bone formation over both 2-D cultured autografts and cell-free DBM scaffolds. We found increased osteoid formation in 3D and 2D cultures, with more osteogenic cells present in the 3D constructs. We suggest that 3-D cultured homograft BMSCs combined with DBM scaffolds represents a new strategy for bone reconstruction, with potential future clinical applicability.     

Image correction algorithm for functional three-dimensional diffuse optical tomography brain imaging

We outline a computationally efficient image correction algorithm, which we have applied to diffuse optical tomography (DOT) image time series derived from a magnetic resonance imaging (MRI)-based brain model. Results show that the algorithm increases spatial resolution, decreases spatial bias, and only modestly reduces temporal accuracy for noise levels typically seen in experiment, and produces results comparable to image reconstructions that incorporate information from MRI priors. We demonstrate that this algorithm has robust performance in the presence of noise, background heterogeneity, irregular external and internal boundaries, and error in the initial guess. However, the algorithm introduces artifacts when the absorption and scattering coefficients of the reference medium are overestimated--a situation that is easily avoided in practice. The considered algorithm offers a practical approach to improving the quality of images from time-series DOT, even without the use of MRI priors.     

Reconstructions of shear modulus, Poisson's ratio, and density using approximate mean normal stress lambda epsilon alpha alpha as unknown

As a differential diagnosis technique for living soft tissues, we are developing ultrasonic-strain-measurement-based shear modulus reconstruction methods. Previously, we reported three-dimensional (3-D) and 2-D reconstruction methods utilizing a typical Poisson's ratio very close to 0.5 (nearly-incompressible). However, because a decrease in the accuracy of the reconstructed value was confirmed to be due to the difference between the original value and the set value, we proposed 3-D and 2-D methods of reconstructing Poisson's ratio as well. Furthermore, we proposed methods of reconstructing density and dealing with dynamic deformation. However, due to tissue incompressibility, the reconstructions of shear modulus, Poisson's ratio, and density became unstable. In this report, to obtain stable, unique reconstructions, we describe a new reconstruction method using mean normal stress approximated by the product of one of Lame's constants X and volume strain epsilon alpha alpha as an unknown. Regularization is simultaneously applied to the respective distributions to decrease the instability of the reconstructions due to measurement errors of the deformation. This method also enables stable, unique reconstructions of shear modulus and density under the condition that the mean normal stress remains unknown. We also verify the effectiveness of this method through 3-D simulations, while showing erroneous artifacts occurring when 2-D and 1-D reconstructions are performed.     

Usefulness of ultrasonic strain measurement-based shear modulus reconstruction for diagnosis and thermal treatment

We previously reported an ultrasonic strain measurement-based one-dimensional (1-D) shear modulus reconstruction technique using a regularization method for differential diagnosis of malignancies on human superficial tissues (e.g., breast tissues). Here, ultrasonic strain measurement-based 2-D and 3-D shear modulus reconstruction techniques are described, and the 1-D technique is reviewed and subsequently applied to various human in vivo tissues, including deeply situated tissues (e.g., liver). Because soft tissues are deformed in 3-D space by externally situated arbitrary mechanical sources, the accuracy of the low-dimensional (i.e., 1-D or 2-D) reconstructions is lower to that of 3-D reconstruction due to occurrence of erroneous reconstruction artifacts (i.e., the reconstructed modulus is different than reality). These artifacts are confirmed on simulated inhomogeneous cubic phantoms containing a spherical homogenous inclusion using numerically calculated deformation data. The superiority of quasi-real-time imaging of the shear modulus is then demonstrated by comparing it with conventional B-mode imaging and strain imaging from the standpoints of monitoring the effectiveness of minimally invasive thermal therapy as well as differential diagnosis. Because the 2-D and 3-D techniques require special ultrasonic (US) equipment, the 1-D technique using conventional US imaging equipment is used, even though erroneous artifacts will occur. Specifically, the 1-D technique is applied as a diagnostic tool for differentiating malignancies in human in vivo liver and breast tissue, and a monitoring technique for determining the effectiveness of interstitial electromagnetic wave (micro and rf) thermal therapy on human in vivo liver and calf in vitro liver. Even when using the 1-D technique, reconstructed shear moduli were confirmed to be a suitable measure for monitoring thermal treatment as well as differential diagnosis. These results are encouraging in that they will promote use of 2-D and 3-D reconstruction techniques.     

Image correction scheme applied to functional diffuse optical tomography scattering images

We have extended our investigation on the use of a linear algorithm for enhancing the accuracy of diffuse optical tomography (DOT) images, to include spatial maps of the diffusion coefficient. The results show that the corrected images are markedly improved in terms of estimated size, spatial resolution, two-object resolving power, and quantitative accuracy. These image-enhancing effects are significant at expected levels of diffusion-coefficient contrast in tissue and noise levels typical of experimental DOT data. Overall, the types and magnitudes of image-enhancing effects obtained here are qualitatively similar to those seen in previous studies on mu(a) perturbations. The implications for practical implementations of DOT time-series imaging are discussed.     

Electrical Capacitance Volume Tomography

A dynamic volume imaging based on the principle of electrical capacitance tomography (ECT), namely, electrical capacitance volume tomography (ECVT), has been developed in this study. The technique generates, from the measured capacitance, a whole volumetric image of the region enclosed by the geometrically three-dimensional capacitance sensor. This development enables a real-time, 3-D imaging of a moving object or a real-time volume imaging (4-D) to be realized. Moreover, it allows total interrogation of the whole volume within the domain (vessel or conduit) of an arbitrary shape or geometry. The development of the ECVT imaging technique primarily encloses the 3-D capacitance sensor design and the volume image reconstruction technique. The electrical field variation in three-dimensional space forms a basis for volume imaging through different shapes and configurations of ECT sensor electrodes. The image reconstruction scheme is established by implementing the neural-network multicriterion optimization image reconstruction (NN-MOIRT), developed earlier by the authors for the 2-D ECT. The image reconstruction technique is modified by introducing into the algorithm a 3-D sensitivity matrix to replace the 2-D sensitivity matrix in conventional 2-D ECT, and providing additional network constraints including 3-to-2-D image matching function. The additional constraints further enhance the accuracy of the image reconstruction algorithm. The technique has been successfully verified over actual objects in the experimental conditions     

Effects of refractive index on near-infrared tomography of the breast

Near infrared (NIR) optical tomography is an imaging technique in which internal images of optical properties are reconstructed with the boundary measurements of light propagation through the medium. Recent advances in instrumentation and theory have led to the use of this method for the detection and characterization of tumors within the female breast tissue. Most image reconstruction approaches have used the diffusion approximation and have assumed that the refractive index of the breast is constant, with a bulk value of approximately 1.4. We have applied a previously reported modified diffusion approximation, in which the refractive index for different tissues can be modeled. The model was used to generate NIR data from a realistic breast geometry containing a localized anomaly. Using this simulated data, we have reconstructed optical images, both with and without correct knowledge of the refractive-index distribution to show that the modified diffusion approximation can accurately recover the anomaly given a priori knowledge of refractive index. But using a reconstruction algorithm without the use of correct a priori information regarding the refractive-index distribution is shown as recovering the anomaly but with a degraded quality, depending on the degree of refractive index mismatch. The results suggest that provided the refractive index of breast tissue is approximately 1.3-1.4, their exclusion will have minimal effect on the reconstructed images.