3-D Image-guided diffuse optical tomography using boundary element method and MPI implementation.

Boundary elements provide an attractive method for image-guided multi-modality near infrared spectroscopy in three dimensions using only surface discretization. This method operates under the assumption that the underlying tissue contains piece-wise constant domains whose boundaries are known a priori from an alternative imaging modality such as MRI or microCT. This significantly simplifies the meshing process providing both speed-up and accuracy in the forward solution.

NIRViz: 3D visualization software for multimodality optical imaging using visualization toolkit (VTK) and insight segmentation toolkit (ITK).

Optical imaging using near-infrared light is used for noninvasive probing of tissues to recover vascular and molecular status of healthy and diseased tissues using hemoglobin contrast arising due to absorption of light. While multimodality optical techniques exist, visualization techniques in this area are limited. Addressing this issue, we present a simple framework for image overlay of optical and magnetic resonance (MRI) or computerized tomographic images which is intuitive and easily usable, called NIRViz.

Image guided near-infrared spectroscopy of breast tissue in vivo using boundary element method.

We demonstrate quantitative functional imaging using image-guided near-infrared spectroscopy (IG-NIRS) implemented with the boundary element method (BEM) for reconstructing 3-D optical property estimates in breast tissue in vivo. A multimodality MRI-NIR system was used to collect measurements of light reflectance from breast tissue. The BEM was used to model light propagation in 3-D based only on surface discretization in order to reconstruct quantitative values of total hemoglobin (HbT), oxygen saturation, water, and scatter.

A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging.

Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3D volume meshing to incorporate constraints related to anatomical structure via techniques such as regularization. Alternate approaches such as the boundary element method (BEM) require only surface discretization but assume homogeneous or piece-wise constant domains that can be limiting.

Rapid magnetic resonance-guided near-infrared mapping to image pulsatile hemoglobin in the breast.

A near-IR (NIR) tomography system with spectral-encoded sources was built to quantify the temporal contrast in human breast tissue using guidance from magnetic resonance imaging. The systems were integrated with a custom breast coil interface to provide simultaneous acquisition. The NIR signal was synchronized to simultaneous finger pulse oximeter plethysmogram, which offered a frequency reference.

Characterizing accuracy of total hemoglobin recovery using contrast-detail analysis in 3D image-guided near infrared spectroscopy with the boundary element method.

The quantification of total hemoglobin concentration (HbT) obtained from multi-modality image-guided near infrared spectroscopy (IG-NIRS) was characterized using the boundary element method (BEM) for 3D image reconstruction. Multi-modality IG-NIRS systems use a priori information to guide the reconstruction process. While this has been shown to improve resolution, the e(R)ect on quantitative accuracy is unclear.

Imaging targeted-agent binding in vivo with two probes.

An approach to quantitatively image targeted-agent binding rate in vivo is demonstrated with dual-probe injection of both targeted and nontargeted fluorescent dyes. Images of a binding rate constant are created that reveal lower than expected uptake of epidermal growth factor in an orthotopic xenograft pancreas tumor (2.3 x 10(-5) s(-1)), as compared to the normal pancreas (3.

OPTIMIZATION OF 3-D IMAGE-GUIDED NEAR INFRARED SPECTROSCOPY USING BOUNDARY ELEMENT METHOD.

Multimodality imaging systems combining optical techniques with MRI/CT provide high-resolution functional characterization of tissue by imaging molecular and vascular biomarkers. To optimize these hybrid systems for clinical use, faster and automatable algorithms are required for 3-D imaging. Towards this end, a boundary element model was used to incorporate tissue boundaries from MRI/CT into image formation process.

Sensitivity of hemoglobin concentration on optical probe positioning in image-guided near infrared spectroscopy.

Multi-modality image-guided near infrared spectroscopy provides volume-based quantification of total hemoglobin, oxygen saturation, water and scatter in various tissue types in-vivo. The accuracy of these parameters depends on the location of the imaging probe and its distance from the tumor. In a numerical study, we have performed simulation to analyze this effect in a breast-specific imaging domain.

Video-rate near infrared tomography to image pulsatile absorption properties in thick tissue.

A high frame-rate near-infrared (NIR) tomography system was created to allow transmission imaging of thick tissues with spectral encoding for parallel source implementation. The design was created to maximize tissue penetration through up to 10 cm of tissue, allowing eventual use in human imaging. Eight temperature-controlled laser diodes (LD) are used in parallel with 1.

Numerical modelling and image reconstruction in diffuse optical tomography.

The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue.

Imaging of glioma tumor with endogenous fluorescence tomography.

Tomographic imaging of a glioma tumor with endogenous fluorescence is demonstrated using a noncontact single-photon counting fan-beam acquisition system interfaced with microCT imaging. The fluorescence from protoporphyrin IX (PpIX) was found to be detectable, and allowed imaging of the tumor from within the cranium, even though the tumor presence was not visible in the microCT image. The combination of single-photon counting detection and normalized fluorescence to transmission detection at each channel allowed robust imaging of the signal.

Diagnostic detection of diffuse glioma tumors in vive with molecular fluorescent probe-based transmission spectroscopy.

The diffuse spread of glioma tumors leads to the inability to image and properly treat this disease. The optical spectral signature of targeted fluorescent probes provides molecular signals from the diffuse morphologies of glioma tumors, which can be a more effective diagnostic probe than standard morphology-based magnetic resonance imaging (MRI) sequences. Three orthotopic xenograft glioma models were used to examine the potential for transmitted optical fluorescence signal detection in vivo, using endogenously produced protoporphyrin IX (PpIX) and exogenously administered fluorescently labeled epidermal growth factor (EGF).

Image-guided near infrared spectroscopy using boundary element method: phantom validation.

Image-guided near infrared spectroscopy (IG-NIRS) can provide high-resolution vascular, metabolic and molecular characterization of localized tissue volumes in-vivo. The approach for IG-NIRS uses hybrid systems where the spatial anatomical structure of tissue obtained from standard imaging modalities (such as MRI) is combined with tissue information from diffuse optical imaging spectroscopy. There is need to optimize these hybrid systems for large-scale clinical trials anticipated in the near future in order to evaluate the feasibility of this technology across a larger population.

Spectral tomography with diffuse near-infrared light: inclusion of broadband frequency domain spectral data.

Near-infrared (NIR) region-based spectroscopy is examined for accuracy with spectral recovery using frequency domain data at a discrete number of wavelengths, as compared to that with broadband continuous wave data. Data with more wavelengths in the frequency domain always produce superior quantitative spectroscopy results with reduced noise and error in the chromophore concentrations. Performance of the algorithm in the situation of doing region-guided spectroscopy within the MRI is also considered, and the issue of false positive prior regions being identified is examined to see the effect of added wavelengths.

Methodology development for three-dimensional MR-guided near infrared spectroscopy of breast tumors.

Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect the tissue composition.

Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction.

Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for non-invasive functional imaging of tissue, specifically for the detection and characterization of breast cancer or other soft tissue lesions. Much work has been carried out for accurate modeling and image reconstruction from clinical data. NIRFAST, a modeling and image reconstruction package has been developed, which is capable of single wavelength and multi-wavelength optical or functional imaging from measured data.

Image-guided Raman spectroscopic recovery of canine cortical bone contrast in situ.

Raman scattering provides valuable biochemical and molecular markers for studying bone tissue composition with use in predicting fracture risk in osteoporosis. Raman tomography can image through a few centimeters of tissue but is limited by low spatial resolution. X-ray computed tomography (CT) imaging can provide high-resolution image-guidance of the Raman spectroscopic characterization, which enhances the quantitative recovery of the Raman signals, and this technique provides additional information to standard imaging methods.

Noninvasive Raman tomographic imaging of canine bone tissue.

Raman spectroscopic diffuse tomographic imaging has been demonstrated for the first time. It provides a noninvasive, label-free modality to image the chemical composition of human and animal tissue and other turbid media. This technique has been applied to image the composition of bone tissue within an intact section of a canine limb.

3D Multi-spectral Image-guided Near-infrared Spectroscopy using Boundary Element Method.

Image guided (IG) Near-Infrared spectroscopy (NIRS) has the ability to provide high-resolution metabolic and vascular characterization of tissue, with clinical applications in diagnosis of breast cancer. This method is specific to multimodality imaging where tissue boundaries obtained from alternate modalities such as MRI/CT, are used for NIRS recovery. IG-NIRS is severely limited in 3D by challenges such as volumetric meshing of arbitrary anatomical shapes and computational burden encountered by existing models which use finite element method (FEM).

A boundary element approach for image-guided near-infrared absorption and scatter estimation.

Multimodality NIR spectroscopy systems offer the possibility of region-based vascular and molecular characterization of tissue in vivo. However, computationally efficient 3D image reconstruction algorithms specific to these image-guided systems currently do not exist. Image reconstruction is often based on finite-element methods (FEMs), which require volume discretization.

Computationally efficient methods for incorporation of spectral priors in 3-d optical tomography.

Use of spectral prior in optical tomography has significantly improved accuracy and quality of images, when applied in two-dimensional (2-D) models. However, the size of the problem increases substantially when applied in 3-D. Two methods are presented here that make 3-D spectral imaging computationally feasible.

Developments in quantitative oxygen-saturation imaging of breast tissue in vivo using multispectral near-infrared tomography.

Imaging of oxygen saturation provides a spatial map of the tissue metabolic activity and has potential in diagnosis and treatment monitoring of breast cancer. Oxygen-saturation imaging is possible through near-infrared (NIR) tomography, but has low signal-to-noise ratio (SNR). This can be augmented by using NIR tomography as an add-on to MRI.

Image reconstruction of effective Mie scattering parameters of breast tissue in vivo with near-infrared tomography.

A method for image reconstruction of the effective size and number density of scattering particles is discussed within the context of interpreting near-infrared (NIR) tomography images of breast tissue. An approach to use Mie theory to estimate the effective scattering parameters is examined and applied, given some assumptions about the index of refraction change expected in lipid membrane-bound scatterers. When using a limited number of NIR wavelengths in the reduced scattering spectra, the parameter extraction technique is limited to representing a continuous distribution of scatterer sizes, which is modeled as a simple exponentially decreasing distribution function.

Data subset algorithm for computationally efficient reconstruction of 3-D spectral imaging in diffuse optical tomography.

Three-dimensional (3-D) models of light propagation in diffuse optical tomography provide an accurate representation of scattering in tissue. Here the use of spectral priors, shown to improve quantification of functional parameters in 2-D, has been extended to 3-D. To make 3-D spectral imaging computationally tractable, a novel technique is presented to deal with the large data set.