This PDF file contains the front matter associated with SPIE Proceedings Volume 8937, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

A freehand, non-contact diffuse optical tomography (DOT) system has been developed for multimodal imaging with intraoperative cone-beam CT (CBCT) during minimally-invasive cancer surgery. The DOT system is configured for near-infrared fluorescence imaging with indocyanine green (ICG) using a collimated 780 nm laser diode and a nearinfrared CCD camera (PCO Pixelfly USB). Depending on the intended surgical application, the camera is coupled to either a rigid 10 mm diameter endoscope (Karl Storz) or a 25 mm focal length lens (Edmund Optics). A prototype flatpanel CBCT C-Arm (Siemens Healthcare) acquires low-dose 3D images with sub-mm spatial resolution. A 3D mesh is extracted from CBCT for finite-element DOT implementation in NIRFAST (Dartmouth College), with the capability for soft/hard imaging priors (e.g., segmented lymph nodes). A stereoscopic optical camera (NDI Polaris) provides real-time 6D localization of reflective spheres mounted to the laser and camera. Camera calibration combined with tracking data is used to estimate intrinsic (focal length, principal point, non-linear distortion) and extrinsic (translation, rotation) lens parameters. Source/detector boundary data is computed from the tracked laser/camera positions using radiometry models. Target registration errors (TRE) between real and projected boundary points are ~1-2 mm for typical acquisition geometries. Pre-clinical studies using tissue phantoms are presented to characterize 3D imaging performance. This translational research system is under investigation for clinical applications in head-and-neck surgery including oral cavity tumour resection, lymph node mapping, and free-flap perforator assessment.

Screening cancer in excision margins with confocal microscopy may potentially save time and cost over the gold standard histopathology (H and E). However, diagnostic accuracy requires sufficient contrast and resolution to reveal pathological traits in a growing set of tumor types. Reflectance mode images structural details due to microscopic refractive index variation. Nuclear contrast with acridine orange fluorescence provides enhanced diagnostic value, but fails for in situ squamous cell carcinoma (SCC), where the cytoplasm is important to visualize. Combination of three modes [eosin (Eo) fluorescence, reflectance (R) and acridine orange (AO) fluorescence] enable imaging of cytoplasm, collagen and nuclei respectively. Toward rapid intra-operative pathological margin assessment to guide staged cancer excisions, multimodal confocal mosaics can image wide surgical margins (~1cm) with sub-cellular resolution and mimic the appearance of conventional H and E. Absorption contrast is achieved by alternating the excitation wavelength: 488nm (AO fluorescence) and 532nm (Eo fluorescence). Superposition and false-coloring of these modes mimics H and E, enabling detection of the carcinoma in situ in the epidermal layer The sum mosaic Eo+R is false-colored pink to mimic eosins’ appearance in H and E, while the AO mosaic is false-colored purple to mimic hematoxylins’ appearance in H and E. In this study, mosaics of 10 Mohs surgical excisions containing SCC in situ and 5 containing only normal tissue were subdivided for digital presentation equivalent to 4X histology. Of the total 16 SCC in situ multimodal mosaics and 16 normal cases presented, two reviewers made 1 and 2 (respectively) type-2 errors (false positives) but otherwise scored perfectly when using the confocal images to screen for the presence of SCC in situ as compared to the gold standard histopathology. Limitations to precisely mimic H and E included occasional elastin staining by AO. These results suggest that confocal mosaics may effectively guide staged SCC excisions in skin and other tissues.

Simultaneous and quantitative assessment of skin functional characteristics in different modalities will facilitate diagnosis and therapy in many clinical applications such as wound healing. However, many existing clinical practices and multimodal imaging systems are subjective, qualitative, sequential for multimodal data collection, and need co-registration between different modalities. To overcome these limitations, we developed a multimodal imaging system for quantitative, non-invasive, and simultaneous imaging of cutaneous tissue oxygenation and blood perfusion parameters. The imaging system integrated multispectral and laser speckle imaging technologies into one experimental setup. A Labview interface was developed for equipment control, synchronization, and image acquisition. Advanced algorithms based on a wide gap second derivative reflectometry and laser speckle contrast analysis (LASCA) were developed for accurate reconstruction of tissue oxygenation and blood perfusion respectively. Quantitative calibration experiments and a new style of skinsimulating phantom were designed to verify the accuracy and reliability of the imaging system. The experimental results were compared with a Moor tissue oxygenation and perfusion monitor. For In vivo testing, a post-occlusion reactive hyperemia (PORH) procedure in human subject and an ongoing wound healing monitoring experiment using dorsal skinfold chamber models were conducted to validate the usability of our system for dynamic detection of oxygenation and perfusion parameters. In this study, we have not only setup an advanced multimodal imaging system for cutaneous tissue oxygenation and perfusion parameters but also elucidated its potential for wound healing assessment in clinical practice.

Coherent anti-Stokes Raman scattering (CARS) and four-wave-mixing (FWM) microscopy are a related pair of powerful nonlinear optical characterization tools. These techniques often yield strong signals from concentrated samples, but because of their quadratic dependence on concentration, they are not typically employed for imaging or identifying dilute cellular constituents. We report here that, depending on the excitation wavelengths employed, both CARS and degenerate-FWM signals from carotenoid accumulations in alga cysts can be exceptionally large, allowing for low-power imaging of astaxanthin (AXN) deposits in Haematococcus pluvialis microalga. By use of a broadband laser pulse scheme for CARS and FWM, we are able to simultaneously collect strong intrinsic two-photon-excitation fluorescence signals from cellular chlorophyll in vivo. We show that CARS signals from astaxanthin (AXN) samples in vitro strictly follow the expected quadratic dependence on concentration, and we demonstrate the collection of wellresolved CARS spectra in the fingerprint region with sensitivity below 2mM. We suggest that multimodal nonlinear optical microscopy is sufficiently sensitive to AXN and chlorophyll concentrations that it will allow for non-invasive monitoring of carotenogenesis in live H. pluvialis microalgae.

Cancer cells are characterized by adaptive features that allow them to evade apoptosis and proliferate in an unchecked manner in the host tissue. Therapeutic strategies often involve targeting those adaptive molecular pathways leading to downstream effects such as changes in perfusion, metabolic rate, and/or oxygen utilization in the malignant tissue. Such surrogate biomarkers can be used to monitor therapeutic response, optimize treatment protocols, or assist in development of new therapeutic approaches. In this study, we present an optical methodology to make in vivo measurements of oxygen saturation as a surrogate biomarker in breast cancer xenografts within a mouse mammary window chamber (MWC) model. By using multi-spectral measurements of the reflectance off the tissue under the coverslip of the window chamber, we are able to obtain high resolution maps of the variation of oxygenation levels of the tissue, which allow continuous tracking of the level of tissue oxygenation during tumor growth and following treatment. The MWC, which was designed and fabricated in-house, is compatible with multiple imaging modalities such as MRI and high resolution intravital microscopy, providing the capability for cross validation of oxygenation measurements on multiple imaging platforms.

Concurrent fNIRS/fMRI recordings represent multiple, simultaneously active, regionally overlapping neural hemodynamic responses. In this study, we propose a novel parallel framework for the spatiotemporal fNIRS/fMRI fusion to address the issues due to the overlapping nature of these responses. The developed fusion techniques employ the Independent Component Analysis (ICA) to recover the time courses and spatial mapping components from fNIRS and fMRI separately. Then the correlated components from each imaging modality are combined concurrently in the spatial and temporal domain for fMRI-guided fNIRS and fNIRS aided fMRI.

Multi-modality imaging leverages the competitive advantage of different imaging systems to improve the overall resolution and quantitative accuracy. Our new technique, Photo-Magnetic Imaging (PMI) is one of these true multi-modality imaging approaches, which can provide quantitative optical absorption map at MRI spatial resolution. PMI uses laser light to illuminate tissue and elevate its temperature while utilizing MR thermometry to measure the laser-induced temperature variation with high spatial resolution. The high-resolution temperature maps are later converted to tissue absorption maps by a finite element based inverse solver that is based on modeling of photon migration and heat diffusion in tissue. Previously, we have demonstrated the feasibility of PMI with phantom studies. Recently, we have managed to reduce the laser power under ANSI limit for maximum skin exposure therefore, we have well positioned PMI for in vivo imaging. Currently we are expanding our system by adding multi-wavelength imaging capability. This will allow us not only to resolve spatial distribution of tissue chromophores but also exogenous contrast agents. Although we test PMIs feasibility with animal studies, our future goal is to use PMI for breast cancer imaging due to its high translational potential.

To overcome the strong scattering in biological tissue that has long afflicted fluorescence tomography, we have developed a novel technique, "temperature-modulated fluorescence tomography" (TM-FT) to combine the sensitivity of fluorescence imaging with focused ultrasound resolution. TM-FT relies on two key elements: temperature sensitive ICG loaded pluronic nanocapsules we termed ThermoDots and high intensity focused ultrasound (HIFU). TM-FT localizes the position of the fluorescent ThermoDots by irradiating and scanning a HIFU beam across the tissue while conventional fluorescence tomography measurements are acquired. The HIFU beam produces a local hot spot, in which the temperature suddenly increases changing the quantum efficiency of the ThermoDots. The small size of the focal spot (~1 mm) up to a depth of 6 cm, allows imaging the distribution of these temperature sensitive agents with not only high spatial resolution but also high quantitative accuracy in deep tissue using a proper image reconstruction algorithm. Previously we have demonstrated this technique with a phantom study with ThermoDots sensitive in the 20-25°C range. We recently optimized the ThermoDots for physiological temperatures. In this work, we will demonstrate a new HIFU scanning method which is optimized for in vivo studies. The performance of the system is tested using a phantom that resembles a small animal bearing a small tumor targeted by ThermoDots.

Silver nanoparticles and perfluorocarbon are encapsulated in multilayered lipid microbubbles by a coaxial electro-flow focusing process. The process is characterized as a coaxial liquid jet in the core of a high-speed coflowing gas stream under an axial electric field. Different flow modes are identified and the stable cone-jet structure is formed in a wide range of process parameters. Core-shell structures of microbubbles with nanoparticles inside the shell are clearly observed. The effects of the main process parameters on the process outcome are studied systemically for the enhanced microbubble morphology. The preliminary elevation of the temperature in silver nanoparticle suspended perfluorcarbon is observed upon exposure to broadband light illumination, indicating the technical potential for light-activated drug delivery.

A concept of single snapshot multispectral imaging by standard RGB image sensors under spectrally-specific illumination comprising a fixed number of narrow spectral lines is discussed and experimentally validated. The limiting conditions, RGB band spectral crosstalk corrections and potential applications for parametric mapping of skin are regarded, along with the preliminary results of the proof-of-concept measurements.

Microcapsules with multiple components inside a biodegradable shell are of great significance in various applications such as biomedicine, biochemistry, sustained drug delivery and image-guided therapy. Here we report a compoundfluidic electro-flow focusing (CFEFF) process that has the potential to one-step envelope multiple drugs and imaging agents separately into a single microcapsule. In this method, a compound needle is assembled by embedding two parallel thin inner needles into a relatively large outer needle. Two kinds of core fluids flow through the inner needles separately and the shell fluid flows through the outer needle. Under the action of aerodynamic and electric driving forces, stable cone-jet configurations can be obtained, resulting in multilayered microcapsules after the breakup of the compound liquid jet because of flow instability. The feasibility and effectiveness of using this CFEFF method to encapsulate multiple components into one shell is verified experimentally. The effects of various process parameters on the morphology and size of the microcapsules are further studied.

Fluorescence molecular tomography (FMT), which is a promising tomographic method for in vivo small animal imaging, has many successful applications. However, FMT reconstruction is usually an ill-posed problem because only the photon distribution over the body surface is measurable. The Lp-norm regularization is generally adopted to stabilize the solution, which can be regarded as a type of a priori information of the fluorescent probe bio-distribution. When FMT is used for the early detection of tumors, an important feature is the sparsity of the fluorescent sources because tumors are usually very small and sparse at early stage. Considering this, we propose a fast and effective method with L1-norm based on sparsity adaptive subspace pursuit to solve the FMT problem in this paper. Our proposed method treats FMT problem with sparsity-promoting L1-norm as the basis pursuit problem. At each iteration, a sparsity factor that indicates the number of unknowns is estimated and updated adaptively. Then our method seeks a small index set which indicates atoms exhibiting highest correlation with the current residual, and updates the current supporting set by merging the newly selected index set. It can be regarded as a kind of sparse approximation reconstruction strategy. To evaluate our proposed method, we compare it to the iterated-shrinkage-based method with L1-norm regularization in numerical experiments. The results demonstrate that the proposed algorithm is able to obtain satisfactory reconstruction results. In addition, the proposed method is about two orders of magnitude faster compared to the iterated-shrinkage-based method. Our method is a practical and effective FMT reconstruction method.

The full time-resolved methods of diffuse fluorescence tomography (DFT) are known to improve image resolution and accuracy significantly. However, these methods usually suffer from low practical efficacy due to the influence of the instrumental response function (IRF) and the tradeoff between the used data time-resolution and the required signal-to-noise ratio (SNR). We herein present a full time-resolved approach that combines an IRF-calibrated time-resolved Born normalization and an overlap-delaying time-gating strategy for attaining high SNR without sacrificing the time-resolved information content. Phantom experiments demonstrate that the approach outperforms the traditional DFT methods in spatial resolution and reconstruction fidelity.

Dental lesions located in the pulp are quite difficult to identify based on anatomical contrast, and, hence, to diagnose using traditional imaging methods such as dental CT. However, such lesions could lead to functional and/or molecular optical contrast. Herein, we report on the preliminary investigation of using Laminar Optical Tomography (LOT) to image the pulp and root canals in teeth. LOT is a non-contact, high resolution, molecular and functional mesoscopic optical imaging modality. To investigate the potential of LOT for dental imaging, we injected an optical dye into ex vivo teeth samples and imaged them using LOT and micro-CT simultaneously. A rigid image registration between the LOT and micro-CT reconstruction was obtained, validating the potential of LOT to image molecular optical contrast deep in the teeth with accuracy, non-invasively. We demonstrate that LOT can retrieve the 3D bio-distribution of molecular probes at depths up to 2mm with a resolution of several hundred microns in teeth.

Laminar optical tomography (LOT) combines the advantages of diffuse optical tomography image reconstruction and a microscopy-based setup to allow non-contact imaging at depth up to a few millimeters. However, LOT image reconstruction paradigm is inherently an ill-posed and computationally expensive inverse problem. Herein, we cast the LOT inverse problem in the compressive sensing (CS) framework to exploit the sparsity of the fluorophore yield in the image domain and to address the ill-posedness of the LOT inverse problem. We apply this new approach to thick tissue engineering applications. We demonstrate the enhanced resolution of our method in 3-D numerical simulations of anatomically accurate microvasculature and using real data obtained from phantom experiments. Furthermore, CS is shown to be more robust against the reduction of measurements in comparison to the classic methods for such application. Potential benefits and shortcomings of the CS approach in the context of LOT are discussed.

Fluorescence Molecular Tomography is an optical imaging technique which aims at reconstructing the 3D distribution of fluorescent markers in bio-tissues based on surface measurements of emitted photons and a model of light propagation. The gold standard of accuracy in creating this light propagation model is the Monte Carlo method (MC), which simulates the path of photon packets through a discretized model of the tissue. One drawback of MC is the computational burden associated with its stochastic nature. Mesh based MC are computational implementations of MC techniques with favorable computational costs. Herein, we investigate the effects of locally refining a mesh discretization on reconstruction accuracy in mesh based Fluorescence Molecular Tomography. Using a mouse model created from μCT data and average murine optical properties, we are investigating the performances of mesh refinement strategies in reconstructing an 48.9 mm³ fluorescence inclusion in the center of the model. Iterative mesh optimization is applied to the inverse problem in which after each reconstruction, the mesh is refined in the area of interest. Performance of the method is evaluated in terms of in volume and center of mass position of the inclusion compared to the ground truth. Our preliminary results indicate that accuracy improves with each refinement until convergence. Moreover, a method for rescaling analytically the forward model to fit each new mesh is also proposed in order to reduce the computational expense of the procedure while maintaining the improvements in accuracy

Time-resolved Diffuse Optical Tomography (DOT) has experienced rapid progress in recent years. It is a powerful functional imaging technique that allows acquiring abundant quantitative optical information from turbid media. However, the application of time domain DOT systems is hampered by the tradeoff between gathering dense data sets and practical acquisition times. Recently, wide-field structured illumination patterns have been applied in time-resolved DOT platforms to drastically accelerate the data acquisition process. In this work, we present a novel structured light based imaging strategy for DOT that can generate time domain datasets enriched by hyperspectral information with short data acquisition times. We employ two digital light processors to generate wide-field imaging pattern both in the illumination and detection channels to capture tomographic data sets over large areas. The hyperspectral data sets are acquired using a time-resolved spectrophotometer built around a multi-anode photomultiplier tube (PMT) that can detect photons in 16 wavelength channels simultaneously based on time-correlated single photon counting (TCSPC) technique. The characteristics of the system are tested in the spatial, temporal and spectral dimensions. The performance of the imaging system is validated through preliminary 3D reconstruction of absorption heterogeneity distribution within a murine model phantom. The application of digital light modulators in illumination and detection combined with timeresolved PMT spectrophotometer enables our system to acquire dense time domain data sets both in the spatial, temporal and spectral dimensions at an unprecedented speed. The phantom validation shows that proposed strategy is a promising technique for fast, high resolution, quantitative three dimensional volumetric imaging.

Computer-assisted diagnoses (CAD) are performed by systems with embedded knowledge. These systems work as a second opinion to the physician and use patient data to infer diagnoses for health problems. Caries is the most common oral disease and directly affects both individuals and the society. Here we propose the use of dental fluorescence images as input of a caries computer-assisted diagnosis. We use texture descriptors together with statistical pattern recognition techniques to measure the descriptors performance for the caries classification task. The data set consists of 64 fluorescence images of in vitro healthy and carious teeth including different surfaces and lesions already diagnosed by an expert. The texture feature extraction was performed on fluorescence images using RGB and YCbCr color spaces, which generated 35 different descriptors for each sample. Principal components analysis was performed for the data interpretation and dimensionality reduction. Finally, unsupervised clustering was employed for the analysis of the relation between the output labeling and the diagnosis of the expert. The PCA result showed a high correlation between the extracted features; seven components were sufficient to represent 91.9% of the original feature vectors information. The unsupervised clustering output was compared with the expert classification resulting in an accuracy of 96.88%. The results show the high accuracy of the proposed approach in identifying carious and non-carious teeth. Therefore, the development of a CAD system for caries using such an approach appears to be promising.

Time domain florescence molecular tomography (TD-FMT) allows 3D visualization of multiple fluorophores based on lifetime contrast and provides a unique data set for enhanced quantification and spatial resolution. The time-gate data set can be divided into two groups around the maximum gate, which are early gates and late gates. It is well-established that early gates allow for improved spatial resolution of reconstruction. However, photon counts are inherently very low at early gates due to the high absorption and scattering of tissue. It makes image reconstruction highly susceptible to the effects of noise and numerical errors. Moreover, the inverse problem of FMT is the ill-posed and underdetermined. These factors make reconstruction difficult for early time gates. In this work, l_p (0<p≤1) regularization based reconstruction algorithm was developed within our wide-field mesh-based Monte Carlo reconstruction strategy. The reconstructions performances were validated on a synthetic murine model simulating the fluorophores uptake in the kidneys and with experimental preclinical data. We compared the early time-gate reconstructed results using l_1/3, l_1/2 and l₁ regularization methods in terms of quantification and resolution. The regularization parameters were selected by the Lcurve method. The simulation results of a 3D mouse atlas and mouse experiment show that l_p (0<p<1) regularization method obtained more sparse and accurate solutions than l₁ regularization method for early time gates.

Diffuse florescence tomography (DFT) as a high-sensitivity optical molecular imaging tool, can be applied to in vivo visualize interior cellular and molecular events for small-animal disease model through quantitatively recovering biodistributions of specific molecular probes. In DFT, the radiative transfer equation (RTE) and its approximation, such as the diffuse equation (DE), have been used as the forward models. The RTE-based DFT methodology is more suitable for biological tissue having void-like regions and the near-source area as in the situations of small animal imaging. We present a RTE-based scheme for the steady state DFT, which combines the discrete solid angle method and the finite difference method to obtain numerical solutions of the 2D steady RTE, with the natural boundary condition and collimating light source model. The approach is validated using the forward data from the Monte Carlo simulation for its better performances in the spatial resolution and reconstruction fidelity compared to the DE-based scheme.

Transferrin (Tfn) is commonly used as a drug delivery carrier for cancer treatment. Tfn cellular internalization can be observed by Förster resonance energy transfer (FRET), which occurs when two fluorophores - donor and acceptor - are a few nanometers apart. Donor fluorescence lifetime can be used to sense and quantify FRET occurrence. In FRET state, the donor is quenched leading to a significant reduction in its lifetime. In this study, donor and acceptor near-infrared (NIR) fluorophore-labeled Tfn were used to quantify cellular internalization in breast cancer cell line (T47D). Based on donor lifetime, quantum yield and spectral data, seven NIR FRET pairs were chosen for this comparison. Performance of the different NIR FRET pairs was evaluated in vitro in multiwell plate settings and by analyzing the relationship between quenched donor fraction and acceptor:donor ratio. Additionally, we performed brightness comparison between each pairs. Several parameters, such as brightness, lifetime, R0 and FRET donor population values are used to identify the most suitable NIR FRET pair for in vivo studies in preclinical settings.

Fiber optic probes with a width limited to a few centimeters can enable diffuse optical tomography (DOT) in intern organs like the prostate or facilitate the measurements on extern organs like the breast or the brain. We have recently shown on 2D tomographic images that time-resolved measurements with a large dynamic range obtained with fast-gated single-photon avalanche diodes (SPADs) could push forward the imaged depth range in a diffusive medium at short source-detector separation compared with conventional non-gated approaches. In this work, we confirm these performances with the first 3D tomographic images reconstructed with such a setup and processed with the Mellin- Laplace transform. More precisely, we investigate the performance of hand-held probes with short interfiber distances in terms of spatial resolution and specifically demonstrate the interest of having a compact probe design featuring small source-detector separations. We compare the spatial resolution obtained with two probes having the same design but different scale factors, the first one featuring only interfiber distances of 15 mm and the second one, 10 mm. We evaluate experimentally the spatial resolution obtained with each probe on the setup with fast-gated SPADs for optical phantoms featuring two absorbing inclusions positioned at different depths and conclude on the potential of short source-detector separations for DOT.

We demonstrate the loss of depth sensitivity induced by the instrument response function on reflectance time-resolved diffuse optical tomography through the comparison of 3 detection systems: on one hand a photomultiplier tube (PMT) and a hybrid PMT coupled with a time-correlated single-photon counting card and on the other hand a high rate intensified camera. We experimentally evaluate the depth sensitivity achieved for each detection module with an absorbing inclusion embedded in a turbid medium. The different interfiber distances of 5, 10 and 15 mm are considered. Finally, we determine a maximal depth reached for each detection system by using 3D tomographic reconstructions based on the Mellin-Laplace transform.

In mathematics, optical molecular imaging including bioluminescence tomography (BLT), fluorescence tomography (FMT) and Cerenkov luminescence tomography (CLT) are concerned with a similar inverse source problem. They all involve the reconstruction of the 3D location of a single/multiple internal luminescent/fluorescent sources based on 3D surface flux distribution. To achieve that, an accurate fusion between 2D luminescent/fluorescent images and 3D structural images that may be acquired form micro-CT, MRI or beam scanning is extremely critical. However, the absence of a universal method that can effectively convert 2D optical information into 3D makes the accurate fusion challengeable. In this study, to improve the fusion accuracy, a new fusion method for dual-modality tomography (luminescence/fluorescence and micro-CT) based on natural light surface reconstruction (NLSR) and iterated closest point (ICP) was presented. It consisted of Octree structure, exact visual hull from marching cubes and ICP. Different from conventional limited projection methods, it is 360° free-space registration, and utilizes more luminescence/fluorescence distribution information from unlimited multi-orientation 2D optical images. A mouse mimicking phantom (one XPM-2 Phantom Light Source, XENOGEN Corporation) and an in-vivo BALB/C mouse with implanted one luminescent light source were used to evaluate the performance of the new fusion method. Compared with conventional fusion methods, the average error of preset markers was improved by 0.3 and 0.2 pixels from the new method, respectively. After running the same 3D internal light source reconstruction algorithm of the BALB/C mouse, the distance error between the actual and reconstructed internal source was decreased by 0.19 mm.

We report on the design of the technique combining 3D optical imaging and dual-energy absorptiometry body scanning to estimate local body area compositions of three compartments. Dual-energy attenuation and body shape measures are used together to solve for the three compositional tissue thicknesses: water, lipid, and protein. We designed phantoms with tissue-like properties as our reference standards for calibration purposes. The calibration was created by fitting phantom values using non-linear regression of quadratic and truncated polynomials. Dual-energy measurements were performed on tissue-mimicking phantoms using a bone densitometer unit. The phantoms were made of materials shown to have similar x-ray attenuation properties of the biological compositional compartments. The components for the solid phantom were tested and their high energy/low energy attenuation ratios are in good correspondent to water, lipid, and protein for the densitometer x-ray region. The three-dimensional body shape was reconstructed from the depth maps generated by Microsoft Kinect for Windows. We used open-source Point Cloud Library and freeware software to produce dense point clouds. Accuracy and precision of compositional and thickness measures were calculated. The error contributions due to two modalities were estimated. The preliminary phantom composition and shape measurements are found to demonstrate the feasibility of the method proposed.

Breast density is a risk factor for breast cancer and we propose using diffuse optical tomography with structured light illuminations (SLI) to quantify the percentage of the fibroglandular (dense) tissue within the breast. Segmentations of dense tissue from breast MRI cases were used to create a geometric model of the breast. COMSOL-generated Finite Element Method (FEM) meshes were used for simulating photon migration through the breast tissue and reconstructing the absorption maps. In these preliminary simulations, the absorption coefficients of the non-dense and dense tissue were assigned using literature values based on their concentrations of water, lipid, oxy- and deoxyhemoglobin as they are the main chromophores, or absorbers of light, within the breast. Synthetic SLI measurements were obtained using a FEMbased forward solver. During the simulation, 12 distinct patterns consisting of vertical stripes, horizontal stripes, and checkerboard patterns were used for illumination and detection. Using these simulated measurements, FEM-based inverse solvers were used to reconstruct the 3D absorption maps. In this study, the methods are applied to reconstruct the absorption maps for multiple wavelengths (780nm, 830nm, 900nm, 1000nm) using one case as an example. We are currently continuing these simulations with additional cases and reconstructing 3D concentration maps of the chromophores within the dense and non-dense breast tissue.