This PDF file contains the front matter associated with SPIE Proceedings Volume 9319, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

This paper presents a safe, affordable, and noninvasive approach to estimate subcutaneous fat thickness by using a multi-distance near infrared (MD-NIR) interactance-based wireless sensing platform. In order to perform the simultaneous measurements at several distances, two light sources with different wavelengths are located at one end of a line followed by seven photo diodes. Bluetooth Low Energy are adopted as their primary communication protocol as a wireless communication. The measured data from the MD-NIR interactance sensors are wirelessly transmitted to a smartphone or a tablet for analysis. The feasibility of the approach and wireless platform is demonstrated using the ex vivo pig fat layer phantoms.

Diffuse optical tomography (DOT) for brain imaging has the potential to be an alternative human brain mapping technique when MRI imaging is not applicable. It recovers tissue chromophore concentrations of brain tissue through measures of light transmission to monitor for example the resting-state brain dynamics. This imaging technique relies on simulation of the light propagation which can be generated based on a subject-specific model. There has been some study on using rigid atlas models as alternatives for model based DOT when subject-specific anatomical data is not available; but there is still a lack of detailed analysis between geometrical accuracy and internal light propagation in tissue for atlas-based DOT. This work is focused on High-Density DOT (HD-DOT) of the whole cortex based on atlas models from 11 different rigid registration algorithms across 24 subjects, and the results are evaluated in 19 areas of the human head. The correlation between geometrical surface error and internal light propagation errors is strong in most area but varies in different regions from R² = 0.74 in the region around top of the head to R² = 0.98 in the region around the temples. In the 11 registration methods, basic-4-landmark registration with 4.2mm average surface error and 50% average internal light propagation errors is shown to be the least accurate registration method whereas full-head landmark with non-iterative point to point with 1.7mm average surface error and 32% average internal light propagation error is shown to be the most accurate registration method for atlas-based DOT.

Dilation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). This post hemorrhagic ventricle dilation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure (ICP). Interventions, such as ventricular tapping to remove cerebrospinal fluid (CSF), are used to prevent injury, but determining the optimal time for treatment is difficult as clinical signs of increased ICP lack sensitivity. There is a growing interest in using near-infrared spectroscopy (NIRS) because of its ability to monitor cerebral oxygen saturation (S_tO₂) at the bedside. However, the accuracy of NIRS may be affected by signal contamination from enlarged ventricles, especially if there are blood breakdown products (bbp) in CSF following IVH. To investigate this, serial NIR spectra from the head and from CSF samples were acquired over a month from seven IVH patients undergoing treatment for PHVD. Over time, the visual appearance of the CSF samples progressed from dark brown (“tea color”) to clear yellow, reflecting the reduction in bbp concentration as confirmed by the stronger absorption around 760 nm at the earlier time points. All CSF samples contained strong absorption at 960 nm due to water. More importantly the same trend in these absorption features was observed in the in vivo spectra, and Monte Carlo simulations confirmed the potential for signal contamination from enlarged ventricles. These findings highlight the challenges of accurately measuring S_tO₂ in this patient population and the necessity of using a hyperspectral NIRS system to resolve the additional chromophores.

A portable hybrid frequency domain (FD)-continuous wave (CW) Near-Infrared spectroscopy NIRS system has been developed for quantifying changes in total hemoglobin, oxygen saturation and water content in the breast during neoadjuvant chemotherapy. Simultaneous acquisition of two sets of 3 FD channels and 3 CW channels could be completed within 1 min. System calibration and homogeneous phantom measurement show phase variation less than 3% when PMT gain from 0.7 to 1.1 was used. The study of integrating this system into the workflow of clinical oncology practice is ongoing.

We have developed a dynamic diffuse optical tomography imaging system that is capable of 3D imaging of both breasts simultaneously. In an ongoing study subjects receiving neoadjuvant chemotherapy are imaged at 6 time points throughout their 5-month treatment. At each time point the subjects preform a breath hold to observe the hemodynamic effects in the breasts. For each session the percent change of various hemodynamic parameters during the breath hold is determined. Preliminary results from show statistically significant differences in washout rates and deoxyhemoglobin changes at the 2-week imaging point between subjects that respond and do not respond to treatment.

Breast cancer is one of the most common cancers for females. To monitor chemotherapeutic efficacy of breast cancer, medical imaging systems such as X-ray mammography, computed tomography, magnetic resonance imaging, and ultrasonography have been used. Currently, it can take up to 3 to 6 weeks to see the tumor response from chemotherapy by monitoring tumor volume changes. In this study, we used near infrared spectroscopy to see if we can predict breast cancer treatment efficacy earlier than tumor volume changes by monitoring tumor vascular reactivity during inhalational gas interventions. The results show the amplitude of oxy-hemoglobin changes (vascular reactivity) during hyperoxic gas inhalation is well correlated with tumor growth, and responded 1 day earlier than tumor volume changes after chemotherapy. In addition, we fitted oxyhemoglobin concentration increase during hyperoxic gas intervention using a double exponential fitting model. From these, we found the change of amplitude 1 value is well matched with tumor growth and regression. Especially, it predicts the chemotherapeutic response of breast tumor better than the amplitude of oxyhemoglobin concentration change during hyperoxic gas intervention. These results may imply that near infrared spectroscopy with respiratory challenges can be useful in early detection of tumor and also in prediction of tumor response to chemotherapy.

We are developing a new instrument for diffuse optical mammography in parallel plate geometry that operates over a broad spectral range of 600-1000 nm, features a scan time of 1-2 min, and allows for dynamic measurements at a selected region of interest. Furthermore, this new instrument is capable of depth discrimination of optical inhomogeneities embedded in the examined tissue by using multiple off-axis detection fibers. Using a solid silicone phantoms, mimicking breast tissue with 39 mm thickness, we demonstrate the capability of this instrument to recover the depth of blood-vessel-like structures to within ~2 mm. Additionally, we demonstrate the capability of this instrument to perform dynamic optical measurements with a temporal sampling rate as high as 20 Hz. We describe our plans to integrate this rich spectral, spatial, and temporal information into a single instrument for translation into clinical measurements on breast cancer patients.

Diffuse optical imaging with structured-light illumination and detection can provide rapid, wide-field anatomical and functional imaging of the breast with an application for breast cancer screening. Our aims for this study were to test the feasibility of structured-light, test our pattern set, and develop and optimize our image reconstruction algorithm. For our phantom studies, we created an agar phantom with dimensions similar to a compressed breast. A cubic inclusion of 30mm by 30mm by 25mm with twice the amount of absorption contrast than the background was placed at the center. Near-infrared light of eleven patterns including a full illumination and single stripes was illuminated onto the breast phantom and detected with a CCD camera, with integration of the signals according to the patterns performed post-data acquisition, with a total of 121 measurements. These measurements were then used in our reconstruction algorithm that iteratively minimized the difference between the collected data and the estimation from our FEM-based forward model of photon diffusion to calculate the absorption values. Reconstructions of the 3D absorption maps detect an inclusion at the center and indicate that our selected set of patterns may be sufficient for structured-light imaging. We are currently improving our instrumentation and testing with additional phantom studies, while also performing simulations of numerical breast phantoms created from MR images to test structured-light’s ability to image complex and realistic breast tissue composition. We hope to use this technique as optical method to image molecular markers, such as hemoglobin, water and lipid, within the breast.

We present a method to compensate for breast tissue thickness variability in broadband, continuous-wave, parallel plate optical mammography. Tissue thickness information is relevant for the recovery of chromophore concentrations within the breast using continuous-wave, diffusion-based models that assume the breast to be in slab geometry. This method compensates for the discrepancy between the actual phantom or breast shape and the models assumed slab geometry by approximating the thickness of the probed tissue volume. In this work, we applied our tissue thickness compensation algorithm on a breast shaped, homogeneous, tissue-mimicking phantom. Using the thickness found from our algorithm (referred to as our “estimated thickness”) as an input into a continuous-wave, diffusion based model, we recovered the absorption coefficient throughout all scanned pixels in the phantom and found an overall deviation of 12% from the true absorption coefficient. By using the known phantom thickness, we found a strong shape bias within the absorption coefficient recovery and a larger overall deviation of 29%. To test the algorithm on in vivo measurements, we applied this tissue thickness compensation method to a human breast cancer optical mammogram scan. Since the exact thickness of the breast at each pixel is unknown, we compared these results to when a uniform breast thickness is assumed and found a drastic improvement of cancer visualization. This method allows for parallel plate, continuous-wave optical imaging to compensate for the tissue thickness variability at each scanned pixel when modeling the breast data in slab geometry. This compensated thickness is needed as an input to the model in order to accurately map the breast chromophore concentrations and enhance the image contrast of cancer.

Coherent Hemodynamics Spectroscopy (CHS) is a novel technique for non-invasive measurements of local microcirculation quantities such as the capillary blood transit times and dynamic autoregulation. The basis of CHS is to measure, for instance with near-infrared spectroscopy (NIRS), peripheral coherent hemodynamic changes that are induced by controlled perturbations in the systemic mean arterial pressure (MAP). In this study, the MAP perturbation was induced by the fast release of two pneumatic cuffs placed around the subject’s thighs after they were kept inflated (at 200 mmHg) for two minutes. The resulting transient changes in cerebral oxy- (O) and deoxy- (D) hemoglobin concentrations measured with NIRS on the prefrontal cortex are then described by a novel hemodynamic model, from which quantifiable parameters such as the capillary blood transit time and a cutoff frequency for cerebral autoregulation are obtained. We present results on eleven healthy volunteers in a protocol involving measurements during normal breathing and during hyperventilation, which is known to cause a hypocapnia-induced increase in cerebral autoregulation. The measured capillary transit time was unaffected by hyperventilation (normal breathing: 1.1±0.1 s; hyperventilation: 1.1±0.1 s), whereas the cutoff frequency of autoregulation, which increases for higher autoregulation efficiency, was indeed found to be significantly greater during hyperventilation (normal breathing: 0.017±0.002 Hz; hyperventilation: 0.034±0.005 Hz). These results provide a validation of local cerebral autoregulation measurements with the new technique of CHS.

We present a brain-computer interface (BCI) that detects, analyzes and responds to user cognitive state in real-time using machine learning classifications of functional near-infrared spectroscopy (fNIRS) data. Our work is aimed at increasing the narrow communication bandwidth between the human and computer by implicitly measuring users' cognitive state without any additional effort on the part of the user. Traditionally, BCIs have been designed to explicitly send signals as the primary input. However, such systems are usually designed for people with severe motor disabilities and are too slow and inaccurate for the general population. In this paper, we demonstrate with previous work¹ that a BCI that implicitly measures cognitive workload can improve user performance and awareness compared to a control condition by adapting to user cognitive state in real-time. We also discuss some of the other applications we have used in this field to measure and respond to cognitive states such as cognitive workload, multitasking, and user preference.

Correct identification of different fluorophores in the fluorescence lifetime imaging in vivo requires accounting for distortion of the measured fluorescent kinetics curve due to light scattering and absorption in medium. This distortion induces the difference between real and measured lifetimes of a fluorophore. We obtained analytical expression based on diffuse approximation of radiation transfer equation that allows to refine estimating the lifetime of a fluorophore. It was shown that our approach can be applied both for analytic kinetics curves obtained by diffuse approximation, Monte Carlo simulated curves and results of model experiment. Analytical and Monte Carlo simulated curves were obtained for media with different optical properties and lifetimes corresponding to those of real fluorophores. Results of numerical simulation are confirmed by the results of the model experiment.

We have developed a new fluorescence molecular tomography (FMT) imaging system, in which we utilized a phase shifting method to extract the mouse surface geometry optically and a rotary laser scanning approach to excite fluorescence molecules and acquire fluorescent measurements on the whole mouse body. Nine fringe patterns with a phase shifting of 2π/9 are projected onto the mouse surface by a projector. The fringe patterns are captured using a webcam to calculate a phase map that is converted to the geometry of the mouse surface with our algorithms. We used a DigiWarp approach to warp a finite element mesh of a standard digital mouse to the measured mouse surface thus the tedious and time-consuming procedure from a point cloud to mesh is avoided. Experimental results indicated that the proposed method is accurate with errors less than 0.5 mm. In the FMT imaging system, the mouse is placed inside a conical mirror and scanned with a line pattern laser that is mounted on a rotation stage. After being reflected by the conical mirror, the emitted fluorescence photons travel through central hole of the rotation stage and the band pass filters in a motorized filter wheel, and are collected by a CCD camera. Phantom experimental results of the proposed new FMT imaging system can reconstruct the target accurately.

Fluorescence molecular tomography (FMT) is a significant preclinical imaging modality that has been actively studied in the past two decades. However, it remains a challenging task to obtain fast and accurate reconstruction of fluorescent probe distribution in small animals due to the large computational burden and the ill-posed nature of the inverse problem. We have recently studied a non-uniform multiplicative updating algorithm, and obtained some further speed gain with the ordered subsets (OS) method. However, increasing the number of OS leads to larger approximation errors and the speed gain from larger number of OS is marginal. In this paper, we propose to further enhance the convergence speed by incorporating the first order momentum method that uses previous iterations to achieve a quadratic convergence rate. Using cubic phantom experiment, we have shown that the proposed method indeed leads to a much faster convergence.

Fluorescence tomography is a non invasive, non ionizing imaging technique able to provide a 3D distribution of fluorescent agents within thick highly scattering mediums, using low cost instrumentation. However, its low spatial resolution due to undetermined and ill-posed nature of its inverse problem has delayed its integration into the clinical settings. In addition, the quality of the fluorescence tomography images is degraded due to the excitation light leakage contaminating the fluorescence measurements. This excitation light leakage results from the excitation photons that cannot be blocked by the fluorescence filters. In this contribution, we present a new method to remove this excitation light leakage noise based on the use of a temperature sensitive fluorescence agents. By performing different sets of measurements using this temperature sensitive agents at multiple temperatures, the excitation light leakage can be estimated and then removed from the measured fluorescence signals . The results obtained using this technique demonstrate its potential for use in in-vivo small animal imaging.

Wide-field optical tissue characterization has a large clinical potential that is currently not exploited due to the lack of realtime imaging methods. In this work we propose 3D single shot optical properties imaging (3D-SSOP) a new acquisition and processing method for obtaining surface profile corrected tissue absorption and reduced scattering coefficient maps from a single image. A profile is projected that is sensitive to both optical properties and surface profile. With image processing, the two responses are separated and surface profile corrected tissue optical properties as with profile corrected spatial frequency domain imaging (3D-SFDI). Overall, 3D-SSOP estimates showed a small bias of -1.2% in both μ_a and μ'_s in comparison with 3D-SFDI. Standard deviations on flat surfaces for 3D-SSOP were 7% (μ_a) and 17% (μ'_s) lower than for 3D-SFDI. However, 3D-SSOP showed significant artifacts near edges, where spatial averaging caused inaccuracies in diffuse reflectance estimates, as well as the surface profile. In an in-vivo experiment of a hand optical property estimates were equivalent, but processing artifacts suppressed smaller details with 3D-SSOP. To our knowledge, this method is the first method to estimate surface profile corrected tissue optical properties from a single image. Therefore we expect this method to be an important step in bringing real-time wide-field tissue characterization to the operating room.

Many biomedical applications require an efficient combination and localization of multiple discrete light sources. In this paper, we present a compact six-channel combiner of optical sub-assembly type that couples the output of independent solid-state light sources into a single 400 μm diameter optical fiber. It is equipped with six discrete laser diodes, 658, 690, 705, 785, 830, and 850 nm for the measurement of the tissue optical properties from optical spectroscopy and imaging. We demonstrate coupling efficiencies ≥ 77% and output optical power ≥ 20 mW for each of the 6 laser diodes installed into the prototype. The design supports the use of continuous wave and intensity modulated laser diodes (with bandwidth ≥ 3 GHz). The developed light source could be used to construct custom multi-wavelength sources for tissue oximeters, diffuse optical imaging, and molecular imaging technologies.

A recently proposed linear time-invariant hemodynamic model for coherent hemodynamics spectroscopy1 (CHS) relates the tissue concentrations of oxy- and deoxy-hemoglobin (outputs of the system) to given dynamics of the tissue blood volume, blood flow and rate constant of oxygen diffusion (inputs of the system). This linear model was derived in the limit of “small” perturbations in blood flow velocity. We have extended this model to a more general model (which will be referred to as the nonlinear extension to the original model) that yields the time-dependent changes of oxy and deoxy-hemoglobin concentrations in response to arbitrary dynamic changes in capillary blood flow velocity. The nonlinear extension to the model relies on a general solution of the partial differential equation that governs the spatio-temporal behavior of oxygen saturation of hemoglobin in capillaries and venules on the basis of dynamic (or time resolved) blood transit time. We show preliminary results where the CHS spectra obtained from the linear and nonlinear models are compared to quantify the limits of applicability of the linear model.

Diffuse correlation spectroscopy (DCS) can measure perfusion changes in deep tissue. However, DCS requires solving the diffusion equation with the proper boundary conditions which can be very difficult and even impossible in many cases. We present a DCS approach that is independent of boundary conditions. The approach is based on measuring the probability distribution function (PDF) of the photons’ pathlengths by deconvolving the temporal point-spread function and the instrument-response function obtained from time-resolved measurements. The recovered PDF was then used to fit the field correlation function to extract perfusion changes. This approach can be applied to any geometry and is valid for diffusive, single-scattering and multiple-scattering, but non-diffusive media.

Monte Carlo models are widely used to model light transport in turbid media, however their results implicitly contain stochastic variations. These fluctuations are not ideal, especially for inverse problems where Jacobian matrix errors can lead to large uncertainties upon matrix inversion. Yet Monte Carlo approaches are more computationally favorable than solving the full Radiative Transport Equation. Here, a non-stochastic computational method of estimating fluence distributions in turbid media is proposed, which is called the Non-Stochastic Propagation by Iterative Radiance Evaluation method (NSPIRE). Rather than using stochastic means to determine a random walk for each photon packet, the propagation of light from any element to all other elements in a grid is modelled simultaneously. For locally homogeneous anisotropic turbid media, the matrices used to represent scattering and projection are shown to be block Toeplitz, which leads to computational simplifications via convolution operators. To evaluate the accuracy of the algorithm, 2D simulations were done and compared against Monte Carlo models for the cases of an isotropic point source and a pencil beam incident on a semi-infinite turbid medium. The model was shown to have a mean percent error less than 2%. The algorithm represents a new paradigm in radiative transport modelling and may offer a non-stochastic alternative to modeling light transport in anisotropic scattering media for applications where the diffusion approximation is insufficient.

The modified Beer-Lambert law is among the most widely used approaches for analysis of near-infrared spectroscopy (NIRS) reflectance signals for measurements of tissue blood volume and oxygenation. Briefly, the modified Beer-Lambert paradigm is a scheme to derive changes in tissue optical properties based on continuous-wave (CW) diffuse optical intensity measurements. In its simplest form, the scheme relates differential changes in light transmission (in any geometry) to differential changes in tissue absorption. Here we extend this paradigm to the measurement of tissue blood flow by diffuse correlation spectroscopy (DCS). In the new approach, differential changes of the intensity temporal auto-correlation function at a single delay-time are related to differential changes in blood flow. The key theoretical results for measurement of blood flow changes in any tissue geometry are derived, and we demonstrate the new method to monitor cerebral blood flow in a pig under conditions wherein the semi-infinite geometry approximation is fairly good. Specifically, the drug dinitrophenol was injected in the pig to induce a gradual 200% increase in cerebral blood flow, as measured with MRI velocity flow mapping and by DCS. The modified Beer-Lambert law for flow accurately recovered these flow changes using only a single delay-time in the intensity auto-correlation function curve. The scheme offers increased DCS measurement speed of blood flow. Further, the same techniques using the modified Beer-Lambert law to filter out superficial tissue effects in NIRS measurements of deep tissues can be applied to the DCS modified Beer-Lambert law for blood flow monitoring of deep tissues.

We present here an analytical model describing light reflectance at an arbitrary source-detector separation covering both sub-diffusive and diffusion regimes for forward-peaked scattering media such as biological tissue. The model incorporates the small-angle scattering approximation (SAA) to radiative transfer for sub-diffusive light reflectance at a source-detector separation less than one single scattering length where the details of the phase function of light scattering dominate. The performance of the model is verified by Monte Carlo simulations. We also present the application of this analytical model in spatial frequency-domain imaging, in particular, when the spatial frequency is pushed below the reduced scattering coefficient.

The imaging of shape perturbation and chromophore concentration using Diffuse Optical Tomography (DOT) data can be mathematically described as an ill-posed and non-linear inverse problem. The reconstruction algorithm for hyperspectral data using a linearized Born model is prohibitively expensive, both in terms of computation and memory. We model the shape of the perturbation using parametric level-set approach (PaLS). We discuss novel computational strategies for reducing the computational cost based on a Krylov subspace approach for parameteric linear systems and a compression strategy for the parameter-to-observation map. We will demonstrate the validity of our approach by comparison with experiments.

We have performed a pre-clinical study on 13 rats to investigate the potential of near-infrared spectroscopy for quantification of hemoglobin concentration and oxygen saturation of hemoglobin in the renal cortex of small animals. These measurements were combined with laser-Doppler fluxmetry and a fluorescence quenching technique for quantification of tissue oxygen tension. Hemoglobin concentration and oxygen saturation were determined from experimental data by a Monte Carlo model. The methods were applied to investigate and compare temporal changes during several types of interventions such as arterial and venous occlusions, as well as hyperoxia, hypoxia and hypercapnia induced by different mixtures of the inspired gas.

Rheumatoid arthritis (RA) is characterized by chronic synovial inflammation, which can cause progressive joint damage and disability. Diffuse optical spectroscopy (DOS) and imaging have the potential to become potent monitoring tools for RA. We devised a method that combined time-resolved DOS and tracer kinetics modeling to rapidly and reliably quantify blood flow in the joint. Preliminary results obtained from two animals show that the technique can detect joint inflammation as early as 5 days after onset.

The absorption and reduced scattering coefficients ( μ_a and μ'_s) of adult heads were determined by multidistance timeresolved reflectance measurements. The finite difference time domain analysis was used to calculate the time-resolved reflectance from adult head models. In vivo time-resolved reflectances of human heads was measured at wavelengths of 680 and 780 nm. By minimizing the objective functions that compare the theoretical and experimental time-resolved reflectances, μ_a and μ'_s of the brains were determined. The results show that the time shift tolerance of measured reflectance for reducing to less than 10% the deviations in μ_a and μ'_s due to their coupling from the values obtained by optimum time shifts is more than 20 ps at both wavelengths.

Optical imaging techniques provide a means of monitoring haemodynamics and tissue oxygenation by virtue of the differing absorption spectra of relevant endogenous chromophores. Whilst time-domain diffuse optical tomography offers sufficient sensitivity to produce full three dimensional images of such properties through the entire infant brain, standard approaches to the imaging protocol and reconstruction methods limit the temporal resolution which can be achieved without an unacceptable degradation in the image quality. In this work we employ spatio-temporal regularisation by means of a variational form Kalman filter to achieve significantly improved temporal resolution whilst maintaining image quality. We demonstrate this approach in a dynamic phantom study where we successfully track moving absorbing and scattering targets using the MONSTIR II instrument developed at University College London.

Diffuse Optics is growing in terms of applications ranging from e.g. oximetry, to mammography, molecular imaging, quality assessment of food and pharmaceuticals, wood optics, physics of random media. Time-domain (TD) approaches, although appealing in terms of quantitation and depth sensibility, are presently limited to large fiber-based systems, with limited number of source-detector pairs. We present a miniaturized TD source-detector probe embedding integrated laser sources and single-photon detectors. Some electronics are still external (e.g. power supply, pulse generators, timing electronics), yet full integration on-board using already proven technologies is feasible. The novel devices were successfully validated on heterogeneous phantoms showing performances comparable to large state-of-the-art TD rack-based systems. With an investigation based on simulations we provide numerical evidence that the possibility to stack many TD compact source-detector pairs in a dense, null source-detector distance arrangement could yield on the brain cortex about 1 decade higher contrast as compared to a continuous wave (CW) approach. Further, a 3-fold increase in the maximum depth (down to 6 cm) is estimated, opening accessibility to new organs such as the lung or the heart. Finally, these new technologies show the way towards compact and wearable TD probes with orders of magnitude reduction in size and cost, for a widespread use of TD devices in real life.

Diffuse Optical Tomography (DOT) and Fluorescence Molecular Tomography (FMT) generally require a huge data set which poses severe limits to acquisition and computational time, especially with a multidimensional data set. The highly scattering behavior of biological tissue leads to a low bandwidth of the information spatial distribution and hence the sampling can be preferably carried out in the spatial frequency source/detector space. In this work, a time-resolved single pixel camera scheme combined with structured light illumination is presented and experimentally validated on phantoms measurements. This approach leads to a significant reduction of the data set while preserving the information content.

We proposed a new technology for tomographic imaging based on beam diffusion and wavefront reconstruction through digital phase conjugation (DPC). The principle of this technology is highly unique and completely different from that of well-known optical coherence tomography (OCT) because it does not utilize the coherence property of light. In our experiment, it was shown that the depth resolution of smaller than 5μm is obtained when using the objective lens with NA of 0.42. In addition, we achieved the extraction of the information from a specific specimen among several specimens arranged along optical axis.

We present a simple, non-destructive photoacoustic spectroscopy method utilizing a unique open-microcavity optoacoustic sensor to measure the concentration ratio of Methemoglobin (MetHb) in an optically scattering medium. Elevated levels of MetHb, present for example in the blood disorder Methemeglobinemia, cannot be detected by conventional pulse oximetry, and may result in inaccurate arterial oxygen saturation measurements. Samples with different ratios of Oxygenated Hemoglobin (HbO₂), Deoxygenated Hemoglobin (HHb), and MetHb were obtained and mixed with nanoscale latex beads to present an optical scattering effect. Polymer encapsulated hemoglobin (PEH) samples were also studied. A sample chamber containing 20 μL of each sample was positioned directly underneath our patented optoacoustic sensor. Unlike a piezoelectric transducer, our optoacoustic sensor allows an excitation laser beam from an OPO laser to pass through and be absorbed by the sample to produce a photoacoustic signal. The cavity layer of the optoacoustic sensor is exposed directly to the resulting ultrasound signal, which causes an intensity modulation of a HeNe laser that is used to monitor the resonance condition of the sensor. A probe laser beam is total internally reflected off of the sensor and detected with a fiber-coupled APD detector. Three wavelengths are chosen for our excitation laser based on the absorption peaks and isobestic points of HHb, HbO₂, and MetHb. Using established values of the molar extinction coefficients of HbO₂, HHb, and MetHb a set of three simultaneous equations can be solved to accurately determine the concentration ratio of MetHb.

In diffuse florescence tomography (DFT), the radiative transfer equation (RTE) and its P1 approximation, i.e. the diffuse equation (DE), have been used as the forward models. Since the assumptions of the diffusion approximation are not valid in particular regions of biological tissue which are close to the collimated light sources and boundaries, not scattering dominated or having void-like sub-domains, the RTE-based DFT methodology has become a focus of investigation. Therefore, we present a RTE-based featured-data scheme for time-domain DFT, which combines the discrete solidangle- element method and the finite element method to obtain numerical solutions of the Laplace-transformed 2D timedomain RTE, with the natural boundary condition and collimating light source model. The scheme is validated using the measurement data from phantom and in-vivo small-animal experiments compared to the DE-based scheme.

Decreasing the acquisition time in bioluminescence imaging (BLI) and bioluminescence tomography (BLT) will enable animals to be imaged within the window of stable emission of the bioluminescent source, a higher imaging throughput and minimisation of the time which an animal is anaesthetised. This work investigates, through simulation using a heterogeneous mouse model, two methods of decreasing acquisition time: 1. Imaging at fewer wavelengths (a reduction from five to three); and 2. Increasing the bandwidth of filters used for imaging. The results indicate that both methods are viable ways of decreasing the acquisition time without a loss in quantitative accuracy. Importantly, when choosing imaging wavelengths, the spectral attenuation of tissue and emission spectrum of the source must be considered, in order to choose wavelengths at which a high signal can be achieved. Additionally, when increasing the bandwidth of the filters used for imaging, the bandwidth must be accounted for in the reconstruction algorithm.

We are developing a ballistic-photon based approach for improving the spatial resolution of fluorescence tomography using time-domain measurements. This approach uses early photon information contained in measured time-of-fight distributions originating from fluorescence emission. The time point spread functions (TPSF) from both excitation light and emission light are acquired with gated single photon Avalanche detector (SPAD) and time-correlated single photon counting after a short laser pulse. To determine the ballistic photons for reconstruction, the lifetime of the fluorophore and the time gate from the excitation profiles will be used for calibration, and then the time gate of the fluorescence profile can be defined by a simple time convolution. By mimicking first generation CT data acquisition, the sourcedetector pair will translate across and also rotate around the subject. The measurement from each source-detector position will be reshaped into a histogram that can be used by a simple back-projection algorithm in order to reconstruct high resolution fluorescence images. Finally, from these 2D sectioning slides, a 3D inclusion can be reconstructed accurately. To validate the approach, simulation of light transport is performed for biological tissue-like media with embedded fluorescent inclusion by solving the diffusion equation with Finite Element Method using COMSOL Multiphysics simulation. The reconstruction results from simulation studies have confirmed that this approach drastically improves the spatial resolution of fluorescence tomography. Moreover, all the results have shown the feasibility of this technique for high resolution small animal imaging up to several centimeters.

We have proposed a new nonlinear inversion technique to estimate the spatial distribution of the absorption coefficient (μa) in the depth direction of a turbid medium by spatially resolved backscattering measurement. With this technique, we can obtain cross-sectional image of μ_a as deep as the backscattered light traveled even when the transmitted light through the medium cannot be detected. In this technique, the depth distribution of absorption coefficient is determined by iterative calculation using the spatial path-length distribution (SPD) of traveled photons as a function of source-detector distance. In this calculation, the variance of path-length of many photons in each layer is also required. The SPD and the variance of path-length are obtained by Monte Carlo simulation using a known reduced scattering coefficient (μ_s’). Therefore, we need to know the μ_s’ of the turbid medium beforehand. We have shown in computer simulation that this technique works well when the μ_s’ is the typical values of mammalian body tissue, or 1.0 /mm. In this study, the accuracy of the μ_a estimation was analyzed and its dependence on the μ_s’ was clarified quantitatively in various situations expected in practice. 10% deviations in μ_s’ resulted in about 30% error in μ_a estimation, in average. This suggested that the measurement or the appropriate estimation of μ_s’ is required to utilize the proposed technique effectively. Through this analysis, the effectiveness and the limitation of the newly proposed technique were clarified, and the problems to be solved were identified.

Supercontinuum light (SC) at wavelengths in the second (1,100 nm to 1,350 nm) and third (1,600 nm to 1,870 nm) NIR optical windows can be used to improve penetration depths of light through tissue and produce clearer images. Image quality is increased due to a reduction in scattering (inverse wavelength power dependence 1/λn, n≥1). We report on the use of a compact Leukos supercontinuum laser (model STM-2000-IR), which utilizes the spectral range from 700 nm to 2,400 nm and offers between 200 - 500 microwatt/nm power in the second and third NIR windows, with an InGaAs detector to image abnormalities hidden beneath thick tissue.

Near Infrared (NIR) optical spectroscopy and imaging technologies are increasingly applied to clinical and pre-clinical applications due to their strong metabolic sensitivity. These technologies rely upon calibrations to remove system artifacts. The most common calibration method requires a tissue-simulating phantom with known absorption (μ_a) and reduced scattering (μ_s’) coefficients to remove temporal and/or spatial artifacts from the measured data. While this method can be effective under certain conditions, there is no universal agreement on how to measure calibration phantom optical properties. An independent method for measuring calibration phantom broadband optical spectra is desired, especially without calibration with reference to known optical properties. We developed a broadband instrument that recovers absolute μ_a and μ_s’ spectra from 620 to 1050 nm in tissue-simulating phantoms. The instrument scans a supercontinuum laser beam across the phantom surface and collects diffuse reflectance via a spectrometercoupled optical fiber. A Monte Carlo algorithm was used to fit the reflectance as a function of source-detector separation and recover absorption and scattering spectra. The only calibration required is a measurement of the laser spot positions on the phantom surface; no optical properties need be known. Spectral constraints were used to create a robust fitting procedure. We demonstrate experimental repeatability by measuring the same phantom multiple times and recover absolute absorption and scattering spectra with ~10% precision across the entire NIR spectral region.

Infantile hemangiomas (IH) are common vascular growths that occur in 5-10% of neonates and have the potential to cause disfiguring and even life-threatening complications. Currently, no objective tool exist to monitor either progression or treatment of IH. To address this unmet clinical need, we have developed a handheld wireless device (HWD) that uses diffuse optical spectroscopy for the assessment of IH. The system employs 4 wavelengths (l=780nm, 805nm, 850nm, and 905nm) and 6 source-detector pairs with distances between 0.6 and 20 mm. Placed on the skin surface, backreflection data is obtained and a multispectral evolution algorithm is used to determine total hemoglobin concentration and tissue oxygen saturation. First results of an ongoing pilot study involving 13 patients (average enrollment age = 25 months) suggest that an increase in hypoxic stress over time can lead to the proliferation of IH. Involuting IH lesions showed an increase in tissue oxygen saturation as well as a decrease in total hemoglobin.

Diffuse optical imaging (DOI) providing functional information of tissues has drawn great attention for the last two decades. Near infrared (NIR) DOI systems composed of scanning bench, opt-electrical measurement module, system control, and data processing and image reconstruction schemes are developed for the screening and diagnosis of breast tumors. Mostly, the scanning bench belonging to fixed source-and-detector configuration limits computed image resolution to an extent. To cope with the issue, we propose, design and implement a 3D prostrate ring-scanning equipment for NIR DOI with flexible combinations of illumination and detection, and with the function of radial, circular and vertical movement without hard compression of breast tissue like the imaging system using or incorporating with X-ray mammographic bench. Especially, a rotation-sliding-and-moving mechanism was designed for the guidance of source- and detection-channel movement. Following the previous justification for synthesized image reconstruction, in the paper the validation using varied phantoms is further conducted and 3D image reconstruction for their absorption and scattering coefficients is illustrated through the computation of our in-house coded schemes. The source and detection NIR data are acquired to reconstruct the 3D images through the operation of scanning bench in the movement of vertical, radial and circular directions. Rather than the fixed configuration, the addressed screening/diagnosing equipment has the flexibility for optical-channel expansion with a compromise among construction cost, operation time, and spatial resolution of reconstructed μ_a and μ_s’ images.

We propose here a reduced space image reconstruction method that makes use of basis function neural network (BFNN) within a framework of PDE-constrained algorithm. This method reduces the solution space using the basis function approach, and finds the optimal solution through the learning process of neural network. The basis function approach improves the ill-posed nature of an original inverse problem, reducing the number of unknowns as well as regularizing the solution automatically. The proposed method was applied to breast cancer imaging, and the reconstruction performance was evaluated on how well the method can identify the tumor location in breast tissue. The results show that the BFNN method gives better results in the identification of tumor location than the traditional element-based reconstruction method.

Frequency domain photon migration (FDPM) uses modulated laser light to measure the bulk optical properties of turbid media and is increasingly being applied for noninvasive functional medical imaging. Though semiconductor edge emitting laser diodes (EELs) have been traditionally used for this application, we show that VCSELs exhibit performance characteristics suitable for FDPM measurements of tissue optical properties. Their output power and modulation characteristics are more than sufficient for optical property recovery. In addition, their small size, high efficiency, low cost, and simple packaging make them an attractive choice as components in clinical FDPM systems. We demonstrate a unique, compact optical probe that was enabled by VCSEL technology.

Near infrared (NIR) diffuse optical tomography has demonstrated great potential in the initial diagnosis of tumor and in the assessment of tumor vasculature response to neoadjuvant chemotherapy. To reconstruct the absorption map of a breast lesion, perturbation is needed which is the normalized difference between the measurements of lesion-side breast and contralateral reference breast. However, the heterogeneity in the reference breast can produce unwanted perturbation which will result in distortion of the reconstructed target absorption map. This report introduces a filtering method to overcome the reference heterogeneity. This method corrects affected source-detector measurements obtained from the reference side by using averages of unaffected measurements. As a result, the filtered perturbation has decreased the effect of heterogeneity on the reconstructed absorption maps. To evaluate the performance of this filtering method, we have compared the reconstructed results with and without the filtering algorithm using simulated heterogeneous reference with heterogeneous absorbers ranging from 0.05 to 0.20 cm^-1 and heterogeneous scatters ranging from 10 to 20cm^-1. The results show that the algorithm can improve the maximum reconstructed target value up to 99% of the value with homogeneous reference. In the worst case of high absorption heterogeneity in reference breast, the maximum reconstructed value was around 30.85% of the true absorption without filtering correction and was improved to 60.4% of the true absorption value, which is 95% of the reconstructed value when using the homogeneous reference.

Near infrared (NIR) diffuse optical tomography has demonstrated great potential in the initial diagnosis of tumor and the assessment of tumor vasculature response to neoadjuvant chemotherapy. A fast and robust data processing is critical to move this technique from lab research to bench-side application. Our lab developed frequency-domain diffuse optical tomography system for clinical applications. So far, we still collect data at hospital and do the data processing off-line. In this paper, a robust calibration procedure and fast processing program were developed to overcome this limitation. Because each detection channel had its own electronic delay, the calibration procedure measured amplitude linearity and phase linearity of each channel, and formed a look-up table. The experimental measurements were corrected by the table and the fitting accuracy improved by 45.8%. To further improve the processing speed, the data collection and processing program were converted to C++ from matlab program. The overall processing speed was improved by two times. We expect the new processing program can move diffuse optical tomography one step close to bench-side clinical applications.