Absorption and scattering images of heterogeneous scattering media can be simultaneously reconstructed by use of dc data

Efficient optical parameter mapping based on time-domain radiative transfer equation combined with parallel programming

A two-dimensional optical parameter mapping based on the time-domain radiative transfer equation (TD-RTE) is studied in this work. The finite element method with structured and unstructured grids is employed to solve TD-RTE and OpenMP parallel technology is employed to improve the computing efficiency. The sequential quadratic programming algorithm is used as a powerful optimization method to reconstruct absorption and scattering parameter fields and the maximum a posteriori estimation is employed by introducing the regularization term into the objective function to improve the ill-posed inverse problem. In addition, the effects of measurement errors on reconstruction accuracy are investigated thoroughly. All the simulation results demonstrate that the reconstructed scheme we developed is accurate and efficient in optical parameter mapping based on TD-RTE.

Pre-seizure state identified by diffuse optical tomography

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Here we demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking such brain activities with high spatiotemporal resolution. We detected early hemodynamic responses with heterogeneous patterns, along with intracranial electroencephalogram gamma power changes, several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state. We also observed the decoupling between local hemodynamic and neural activities. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.

Joint sparsity-driven non-iterative simultaneous reconstruction of absorption and scattering in diffuse optical tomography

Some optical properties of a highly scattering medium, such as tissue, can be reconstructed non-invasively by diffuse optical tomography (DOT). Since the inverse problem of DOT is severely ill-posed and nonlinear, iterative methods that update Green's function have been widely used to recover accurate optical parameters. However, recent research has shown that the joint sparse recovery principle can provide an important clue in achieving reconstructions without an iterative update of Green's function. One of the main limitations of the previous work is that it can only be applied to absorption parameter reconstruction. In this paper, we extended this theory to estimate the absorption and scattering parameters simultaneously when the background optical properties are known. The main idea for such an extension is that a joint sparse recovery step gives us unknown fluence on the estimated support set, which eliminates the nonlinearity in an integral equation for the simultaneous estimation of the optical parameters. Our numerical results show that the proposed algorithm reduces the cross-talk artifacts between the parameters and provides improved reconstruction results compared to existing methods.

Near-infrared spectral tomography integrated with digital breast tomosynthesis: effects of tissue scattering on optical data acquisition design

PURPOSE

Design optimization and phantom validation of an integrated digital breast tomosynthesis (DBT) and near-infrared spectral tomography (NIRST) system targeting improvement in sensitivity and specificity of breast cancer detection is presented. Factors affecting instrumentation design include minimization of cost, complexity, and examination time while maintaining high fidelity NIRST measurements with sufficient information to recover accurate optical property maps.

METHODS

Reconstructed DBT slices from eight patients with abnormal mammograms provided anatomical information for the NIRST simulations. A limited frequency domain (FD) and extensive continuous wave (CW) NIRST system was modeled. The FD components provided tissue scattering estimations used in the reconstruction of the CW data. Scattering estimates were perturbed to study the effects on hemoglobin recovery. Breast mimicking agar phantoms with inclusions were imaged using the combined DBT∕NIRST system for comparison with simulation results.

RESULTS

Patient simulations derived from DBT images show successful reconstruction of both normal and malignant lesions in the breast. They also demonstrate the importance of accurately quantifying tissue scattering. Specifically, 20% errors in optical scattering resulted in 22.6% or 35.1% error in quantification of total hemoglobin concentrations, depending on whether scattering was over- or underestimated, respectively. Limited frequency-domain optical signal sampling provided two regions scattering estimates (for fat and fibroglandular tissues) that led to hemoglobin concentrations that reduced the error in the tumor region by 31% relative to when a single estimate of optical scattering was used throughout the breast volume of interest. Acquiring frequency-domain data with six wavelengths instead of three did not significantly improve the hemoglobin concentration estimates. Simulation results were confirmed through experiments in two-region breast mimicking gelatin phantoms.

CONCLUSIONS

Accurate characterization of scattering is necessary for quantification of hemoglobin. Based on this study, a system design is described to optimally combine breast tomosynthesis with NIRST.

Implementation of edge-preserving regularization for frequency-domain diffuse optical tomography

In this study, we first propose the use of edge-preserving regularization in optimizing an ill-conditioned problem in the reconstruction procedure for diffuse optical tomography to prevent unwanted edge smoothing, which usually degrades the attributes of images for distinguishing tumors from background tissues when using Tikhonov regularization. In the edge-preserving regularization method presented here, a potential function with edge-preserving properties is introduced as a regularized term in an objective function. With the minimization of this proposed objective function, an iterative method to solve this optimization problem is presented in which half-quadratic regularization is introduced to simplify the minimization task. Both numerical and experimental data are employed to justify the proposed technique. The reconstruction results indicate that edge-preserving regularization provides a superior performance over Tikhonov regularization.

Direct-current-based image reconstruction versus direct-current included or excluded frequency-domain reconstruction in diffuse optical tomography

We study the level of image artifacts in optical tomography associated with measurement uncertainty under three reconstruction configurations, namely, by using only direct-current (DC), DC-excluded frequency-domain, and DC-included frequency-domain data. Analytic and synthetic studies demonstrate that, at the same level of measurement uncertainty typical to optical tomography, the ratio of the standard deviation of mu(a) over mu(a) reconstructed by DC only is at least 1.4 times lower than that by frequency-domain methods. The ratio of standard deviations of D (or mu(s)') over D (or mu(s)') reconstructed by DC only are slightly lower than those by frequency-domain methods. Frequency-domain reconstruction including DC generally outperforms that excluding DC, but as the amount of measurements increases, the difference between the two diminishes. Under the condition of a priori structural information, the performances of three reconstruction configurations are seemingly equivalent.

Depth dependence of estimated optical properties of a scattering inclusion by time-resolved contrast functions

In this study we have theoretically and experimentally investigated the behavior of first order approximation contrast function when purely scattering inhomogeneities located at different depths inside a turbid thick slab are considered. Results of model predictions have been compared with Finite element method simulations and tested on phantoms. To this aim, we have developed for the first time to our knowledge a fitting algorithm for estimating both the scattering perturbation parameter and the shift of the inhomogeneity from the middle plane, allowing one to reduce the uncertainties due to depth. This is important for optical mammography because effects of the depth can cause uncertainties in the derived tumor optical properties that are above 20% and the scattering properties of tumors differ from those of the sourrounding healthy tissue by a comparable extent.

Automated breast cancer classification using near-infrared optical tomographic images

An automated procedure for detecting breast cancer using near-infrared (NIR) tomographic images is presented. This classification procedure automatically extracts attributes from three imaging parameters obtained by an NIR imaging system. These parameters include tissue absorption and reduced scattering coefficients, as well as a tissue refractive index obtained by a phase-contrast-based reconstruction approach. A support vector machine (SVM) classifier is utilized to distinguish the malignant from the benign lesions using the automatically extracted attributes. The classification results of in vivo tomographic images from 35 breast masses using absorption, scattering, and refractive index attributes demonstrate high sensitivity, specificity, and overall accuracy of 81.8%, 91.7%, and 88.6% respectively, while the classification sensitivity, specificity, and overall accuracy are 63.6%, 83.3%, and 77.1%, respectively, when only the absorption and scattering attributes are used. Furthermore, the automated classification procedure provides significantly improved specificity and overall accuracy for breast cancer detection compared to those by an experienced technician through visual examination.

Noninvasive in vivo tomographic optical imaging of cellular morphology in the breast: possible convergence of microscopic pathology and macroscopic radiology

This article presents a pilot study of multispectral diffuse optical tomography for noninvasively imaging volume fraction and mean size of cellular scattering components in the breast. Cellular morphology images for a total of 14 cases (four malignant breast and ten benign lesions) were obtained. Analyzing the images based on the pathological findings of the cases studied, we found that light scattering in the breast was contributed from both the nucleus and organelles such as mitochondria and nucleolus. Based on the image analysis of these 14 cases, we found that the differences in the mean size and volume fraction between the malignant and benign lesions are significant. The contrast ratio of the average mean size and volume fraction between malignant and benign lesions were calculated to be 3.38 and 2.63. These initial results suggest that cellular mean size and volume fraction may be two new criteria that could be used to differentiate malignant from 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.

Perturbation approach to the time-resolved transmittance for a spatially varying scattering inclusion in a diffusive slab

In the framework of the perturbation approach to the diffusion equation, an analytical expression is derived to describe the effects on the time-resolved transmittance due to the presence of a spatially varying scattering inclusion hidden inside a diffusive slab. This formula assumes that the reduced scattering coefficient of the inclusion is spatially Gaussian distributed and complements that obtained for the absorptive case. The accuracy and the application range of the perturbed transmittance are investigated through comparisons with the numerical solutions of the time-dependent diffusion equation given by using the finite-element method. The proposed perturbation model is validated through a fitting procedure that determines the relative error in retrieving the scattering perturbation parameter of the inclusion located at the midplane of the slab.

Recent advances in diffuse optical imaging

We review the current state-of-the-art of diffuse optical imaging, which is an emerging technique for functional imaging of biological tissue. It involves generating images using measurements of visible or near-infrared light scattered across large (greater than several centimetres) thicknesses of tissue. We discuss recent advances in experimental methods and instrumentation, and examine new theoretical techniques applied to modelling and image reconstruction. We review recent work on in vivo applications including imaging the breast and brain, and examine future challenges.

Diffuse optical tomography with spectral constraints and wavelength optimization

We present an algorithm that explicitly utilizes the wavelength dependence of tissue optical properties for diffuse optical tomography. We have previously shown that the method gives superior separation of absorption and scattering. Here the technique is described and tested in detail, and optimum wavelength sets for a broad range of chromophore combinations are discovered and analyzed.

Measurement of particle-size distribution and concentration in heterogeneous turbid media with multispectral diffuse optical tomography

We present a method that is capable of extracting particle-size distribution (PSD) and concentration in heterogeneous turbid media by use of multispectral diffuse optical tomography (MSDOT). After the spectroscopic scattering images of the heterogeneous turbid media are obtained with MSDOT, the morphologic information of particles in the heterogeneities is recovered with an iterative regularized reconstruction algorithm based on Mie scattering theory when a particular form of PSD is assumed (Gaussian distribution is used in this study). The method described is tested and evaluated with both simulated and experimental data. The simulations are intended to test the sensitivity of the overall approach to noise effect. A series of phantom experiments are conducted with our newly developed ten-wavelength MSDOT system. Polystyrene microsphere suspensions contain particles of varying size from 2 to 6 microm as targets are embedded in a scattering background medium in these experiments. To achieve optimized results from experimental data, we developed a data preprocessing method for MSDOT as well as a scheme for calibrating scattering spectra. The results from both simulations and experiments show that the particle mean size and concentration can be reconstructed with acceptable accuracy, whereas the recovery of the standard deviation is sensitive to noise effect and can be as large as 86% from the experimental data.

Optical tomographic imaging of small animals

Diffuse optical tomography is emerging as a viable new biomedical imaging modality. Using visible and near-infrared light this technique can probe the absorption and scattering properties of biological tissues. The main applications are currently in brain, breast, limb and joint imaging; however, optical tomographic imaging of small animals is attracting increasing attention. This interest is fuelled by recent advances in the transgenic manipulation of small animals that has led to many models of human disease. In addition, an ever increasing number of optically reactive biochemical markers has become available, which allow diseases to be detected at the molecular level long before macroscopic symptoms appear. The past three years have seen an array of novel technological developments that have led to the first optical tomographic studies of small animals in the areas of cerebral ischemia and cancer.

Differentiation of cysts from solid tumors in the breast with diffuse optical tomography

RATIONALE AND OBJECTIVES

Near-infrared diffuse optical tomography (DOT) is an emerging imaging technology that has the potential to offer enhanced contrast resolution over the existing technologies for detection and diagnosis of breast cancer. Thus far, the clinical evaluation of DOT has been largely limited to solid tumors. A pilot clinical study focused on DOT imaging of breasts with cysts is presented.

MATERIALS AND METHODS

Six cases were studied using the recently developed compact, parallel-detection DOT system. Images characterizing the tissue absorption and scattering were obtained with a finite element-based reconstruction algorithm. The optical images were compared with the mammograms and sonograms. In one case, in vitro measurements of optical properties were conducted for the fluid obtained from needle aspiration.

RESULTS

Substantial contrast between cyst and adjacent parenchyma is observed. For the six cases evaluated, the locations and sizes of cysts imaged optically are accurate and consistent with the mammographic and sonographic findings. For the case that aspiration was performed, the absorption and scattering coefficients imaged in the cyst region are quantitatively accurate compared with that measured in vitro from the fluid aspirated.

CONCLUSION

This pilot study shows that cysts ranging from 1-4 cm in diameter can be quantitatively imaged. They can be differentiated from solid breast tumors because cysts generally demonstrate lower absorption and scattering coefficients compared with the surrounding normal tissue, whereas solid tumors show concurrent higher absorption and scattering related to the normal tissue.

Sagittal laser optical tomography for imaging of rheumatoid finger joints

We present a novel optical tomographic imaging system that was designed to determine two-dimensional spatial distribution of optical properties in a sagittal plane through finger joints. The system incorporates a single laser diode and a single silicon photodetector into a scanning device that records spatially resolved light intensities as they are transmitted through a finger. These data are input to a model-based iterative image reconstruction (MOBIIR) scheme, which uses the equation of radiative transfer (ERT) as a forward model for light propagation through tissue. We have used this system to obtain tomographic images of six proximal interphalangeal finger joints from two patients with rheumatoid arthritis. The optical images were compared to clinical symptoms and ultrasound images.

Time-resolved contrast function and optical characterization of spatially varying absorptive inclusions at different depths in diffusing media

The role of a spatially varying absorptive inhomogeneity located at different depths within a turbid material has been investigated. This inhomogeneity has been characterized by a spatially dependent Gaussian distribution of its absorption coefficient. The present study has been performed calculating the time-resolved contrast function in the framework of the first-order perturbative approach to the diffusion equation for a slab geometry and a coaxial measurement scheme. The model has allowed us to take into account different locations of the inclusion along the source-detector axis. The accuracy of time-resolved contrast predictions has been analyzed through comparisons with results of the finite element method that has been used to numerically solve the diffusion equation. Recovery of the absorption perturbation parameter of the inhomogeneity for different axial positions has also been investigated.

Uniqueness and wavelength optimization in continuous-wave multispectral diffuse optical tomography

We derive conditions for the unique and simultaneous recovery of chromophore concentrations and scattering coefficients in multispectral continuous-wave diffuse optical tomography. These conditions depend strongly on measurement wavelengths. We introduce and demonstrate a general methodology for choosing those wavelengths, which yields superior separation of scattering from absorption and superior separation of one chromophore from another. Application of these concepts should significantly improve the fidelity of continuous-wave diffuse near-infrared optical tomography in tissues.

In vivo breast imaging with diffuse optical tomography based on higher-order diffusion equations

We report on in vivo absorption and scattering imaging of a human breast cyst and implant, using a reconstruction algorithm based on our third-order diffusion equations. To validate these in vivo images, a series of phantom experiments were conducted, in which we used low-absorbing and low-scattering heterogeneities to mimic a breast cyst or implant. These heterogeneities or targets were composed of pure water or a mixture of water and very dilute Intralipid (0.05% and 0.1%). The phantom experiment confirmed the quantitative imaging capability of our improved algorithm for reconstructing heterogeneities where the conventional diffusion approximation is inadequate. Pilot clinical results from female volunteers indicate that enhanced diffuse optical tomography can quantitatively image findings such as breast cysts or implants in which the absorption and scattering coefficients are usually low.

Mesh-based enhancement schemes in diffuse optical tomography

Two mesh-based methods including dual meshing and adaptive meshing are developed to improve the finite element-based reconstruction of both absorption and scattering images of heterogeneous turbid media. The idea of dual meshing scheme is to use a fine mesh for the solution of photon propagation and a coarse mesh for the inversion of optical property distributions. The adaptive meshing method is accomplished by the automatic mesh refinement in the region of heterogeneity during reconstruction. These schemes are validated using tissue-like phantom measurements. Our results demonstrate the capabilities of the dual meshing and adaptive meshing in both qualitative and quantitative improvement of optical image reconstruction.