This PDF file contains the front matter associated with SPIE Proceedings Volume 6850, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

We discuss the possibility of Near Infrared Spectroscopy (NIRS) application to the educational research. NIRS system was used for prefrontal cortex measurement of children, when they were solving Mushi-kuizan problems. The Mushi-kuizan task is one of the mathematical puzzles. Subjects were four children in fifth grade. Hemoglobin parameters such as oxygenated hemoglobin and deoxygenated hemoglobin were calculated during Mushi-kuizan problems. The parameters were compared with the performance data of each subject. Changes Hb parameters described how children use their brain. NIRS evaluated the thinking process of mathematics task. It is very useful for mathematics teachers to catch the children's thinking process dynamically because they can consider the way of teaching for each child. It was shown that NIRS may be able to apply to education.

In order to precisely recover fluorescence lifetimes from bulk tissues, one needs to employ complex light propagation models (e.g., the radiative transfer equation or a simpler yet consistent approximation, the diffusion equation) requiring knowledge of the tissue optical properties. This can be computationally expensive and therefore not practical in many applications. We present a novel method to estimate the fluorescence lifetimes of multiple fluorophores embedded in mice. By assuming that the photon diffusion does not significantly change the fluorescence decay slope, the light propagation is simply modeled as a time-delay during lifetime estimation. Applications of this approach are demonstrated by simulation, phantom data, and in vivo experiments.

One important challenge for in-vivo imaging fluorescence in cancer research and related pharmaceutical studies is to discriminate the exogenous fluorescence signal of the specific tagged agents from the natural fluorescence. For mice, natural fluorescence is composed of endogenous fluorescence from organs like the skin, the bladder, etc. and from ingested food. The discrimination between the two kinds of fluorescence makes easy monitoring the targeted tissues. Generally, the amplitude of the fluorescence signal depends on the location and on the amount of injected fluorophore, which is limited in in-vivo experiments. This paper exposes some results of natural fluorescence analysis from in-vivo mice experiments using a time domain small animal fluorescence imaging system: eXplore Optix^TM. Fluorescence signals are expressed by a Time Point Spread Function (TPSF) at each scan point. The study uses measures of similarity applied purposely to the TPSF to evaluate the discrepancy and/or the homogeneity of scanned regions of a mouse. These measures allow a classification scheme to be performed on the TPSF's based on their temporal shapes. The work ends by showing how the exogenous fluorescence can be distinguished from natural fluorescence by using the TPSF temporal shape.

We show some limitations of the standard t test when used together with typical data processing methods in functional Near Infrared Spectroscopy of the brain to assess the significance of multiple correlated points. We studied the occurrence of errors type I (that is the occurrence of false positive points) when typical processing methods are applied to time series of normal random numbers and to time series of simulated baseline systemic fluctuations. Since the results of the two studies are very similar we concluded that normal random numbers can be used to assess the occurrence of error type I due to certain algorithms of data processing. In order to decrease the occurrence of false positive points we propose to use some modified stepwise Bonferroni procedures, among which we studied the performance of Dubey/Armitage-Parmar algorithm. The results of the algorithm are shown for both simulated and experimental data.

We present a new method to reconstruct arbitrary large volumes in (fluorescence) diffuse optical tomography by splitting the volume of reconstruction into sub-volumes. This allows to perform nonlinear reconstruction on large grids with a larger number of measurement data and more grid nodes than conventional reconstruction schemes, where images are reconstructed on a single grid. We investigate how the reconstructed spatial distributions of diffusion and absorption coefficients using the new method depend on the size of the sub-volumes, compare the convergence to the conventional nonlinear approach, and present an error estimation.

In fluorescence diffuse optical tomography, the error due to discretization of the forward and inverse problems leads to an error in the reconstructed image. Using a Galerkin formulation, we consider zeroth and first order Tikhonov regularization terms and analyze the forward and inverse problems under an optimization formulation which incorporates a priori information. We derive error estimates to describe the impact that discretization of the forward and inverse problems due to finite element method has on the accuracy of the reconstructed optical absorbtion image.

Diffuse optical imaging (DOI) is a relatively new functional imaging modality offering the possibility to record changes in hemoglobin concentrations. It is based on the propagation of near-infrared light through biological tissues. By measuring the optical absorption of the blood in the cortex, DOI enables the estimation of changes of deoxy-hemoglobin (HbR) and oxy-hemoglobin (HbO₂) concentrations. It thus provides indirect information on neuronal activity. Drawbacks of optical imaging are its lack of quantification abilities as well as poor spatial resolution. Although not much can be done concerning the second issue, diffusion being the limiting factor, one can aim at more quantitative data by the use of extra information. As an example, the determination of baseline concentrations done by fitting a temporal or frequency curve to recover background concentrations is not expected to be accurate due to the heterogeneity of the underlying tissues. The vascular architecture, unknown when doing DOI alone, also plays a significant role in the signal detected. Partial volume effects due to an optode pair overlapping a large vein will lead to confounding data and create difficulties in analyzing the neuronal activation. Here we show that fusion with MRI, but done outside the scanner, may help solving some of these issues.

The trans-rectal implementation of NIR optical tomography makes it possible to assess functional status like hemoglobin concentration and oxygen saturation in prostate non-invasively. Trans-rectal NIR tomography may provide tissue-specific functional contrast that is potentially valuable for differentiation of cancerous lesions from normal tissues. Such information will help to determine if a prostate biopsy is needed or can be excluded for an otherwise ambiguous lesion. The relatively low spatial resolution due to the diffuse light detection in trans-rectal NIR tomography, however, limits the accuracy of localizing a suspicious tissue volume. Trans-rectal ultrasound (TRUS) is the clinical standard for guiding the positioning of biopsy needle owing to its resolution and convenience; nevertheless, TRUS lacks the pathognomic specificity to guide biopsy to only the suspicious lesions. The combination of trans-rectal NIR tomography with TRUS could potentially give better differentiation of cancerous tissue from normal background and to accurately localize the cancer-suspicious contrast obtained from NIR tomography. This paper will demonstrate the design and initial evaluation of a trans-rectal NIR tomography probe that can conveniently integrate with a commercial TRUS transducer. The transrectal NIR tomography obtained from this probe is concurrent with TRUS at matching sagittal imaging plane. This design provides the flexibility of simple correlation of trans-rectal NIR with TRUS, and using TRUS anatomic information as spatial prior for NIR image reconstruction.

We found that using more than one parameter derived from optical tomographic images can lead to better image classification results compared to cases when only one parameter is used.. In particular we present a multi-parameter classification approach, called self-organizing mapping (SOM), for detecting synovitis in arthritic finger joints based on sagittal laser optical tomography (SLOT). This imaging modality can be used to determine various physical parameters such as minimal absorption and scattering coefficients in an image of the proximal interphalengeal joint. Results were compared to different gold standards: magnet resonance imaging, ultra-sonography and clinical evaluation. When compared to classifications based on single-parameters, e.g., absorption minimum only, the study reveals that multi-parameter classifications lead to higher classification sensitivities and specificities and statistical significances with p-values <5 per cent. Finally, the data suggest that image analyses are more reliable and avoid ambiguous interpretations when using more than one parameter.

Video rate diffuse tomography can be implemented within the magnetic resonance breast exam. The following paper outlines the basics of a spectrally encoded source set up, being designed and tested for use in breast imaging within a specialized breast surface coil. The system design maximizes input power to the breast, while confining the spectrum to a 10 nm bandwidth of near-infrared light. The center spectral band can be varied, since it is supplied by a tunable Ti:Sapphire laser. The encoding of each source is achieved by splitting the signal into individual nanometer bands through a high resolution grating, and focusing the output of this into each source fiber. This source configuration then requires spectral detection at the output, and so each detection fiber is delivered to a high resolution spectrometer to resolve the detected intensities. Breast imaging with this system has some subtle dynamic range issues, which means that light from sources farthest from the detector pickup are likely not providing useful data, but the closest 4-6 fibers near each source can provide useful data. The implementation of this is being carried out within a magnetic resonance breast array, and initial testing of the signals is shown, along with diagrams and photographs of the system configuration.

A unique fluorescence imaging system incorporates multi-channel spectrometer-based optical detection directly into clinical MRI for simultaneous MR and spectrally-resolved fluorescence tomography acquisition in small animal and human breast-sized volumes. A custom designed MRI rodent coil adapted to accommodate optical fibers in a circular geometry for contact mode acquisition provides small animal imaging capabilities, and human breast-sized volumes are imaged using a clinical breast coil modified with an optical fiber patient array. Spectroscopy fibers couple light emitted from the tissue surface to sixteen highly sensitive CCD-based spectrometers operating in parallel. Tissue structural information obtained from standard and contrast enhanced T1-weighted images is used to spatially constrain the diffuse fluorescence tomography reconstruction algorithm, improving fluorescence imaging capabilities qualitatively and quantitatively. Simultaneous acquisition precludes the use of complex co-registration processes. Calibration procedures for the optical acquisition system are reviewed and the imaging limits of the system are investigated in homogeneous and heterogeneous gelatin phantoms containing Indocyanine Green (ICG). Prior knowledge of fluorescence emission spectra is used to de-couple fluorescence emission from residual excitation laser cross-talk. Preliminary in vivo data suggests improved fluorescence imaging in mouse brain tumors using MR-derived spatial priors. U-251 human gliomas were implanted intracranially into nude mice and combined contrast enhanced MRI/fluorescence tomography acquisition was completed at 24 hour intervals over the course of 72 hours after administration of an EGFR targeted NIR fluorophore. Reconstructed images demonstrate an inability to recover reasonable images of fluorescence activity without the use of MRI spatial priors.

An image reconstruction scheme for time-domain fluorescence diffuse optical tomography is proposed using a reflection-mode for a semi-infinite turbid geometry. The method is based on a generalized pulse spectrum technique that employs analytic expressions of the Laplace-transformed time-domain photon-diffusion model to construct a Born normalized inverse model, and a pair of real domain transform-factors to separate distributions of the fluorescent yield and lifetime. The methodology is validated with a specifically-developed fluorescent Monte-Carlo simulator or finite-element-based methods and its robustness to the background uncertainties is investigated.

A full time-resolved scheme that has been previously applied in diffuse optical tomography is extended to time-domain fluorescence diffuse optical tomography regime, based on a finite-element-finite-time-difference photon diffusion modeling and a Newton-Raphson inversion framework. The merits of using full time-resolved data are twofold: it helps evaluate the intrinsic performance of time-domain mode for improvement of image quality and set up a 'gold standard' for the development of computationally efficient featured-data-based algorithms, and provides a self-normalized implementation to preclude the necessary for the scaling-factor calibration and spectroscopic-feature assessments of the system as well as to overcome the adversity of system instability. We validate the proposed methodology using simulated data, and evaluate its performances in simultaneously recovering the fluorescent yield and lifetime as well as its superiority to the featured-data one in the fidelity of image reconstruction.

A novel application of hyperspectral instrumentation is described here, where a sheet-of-light method, produced by a low power laser light, is used to compute range measurements, and a hyperspectral instrument is used to acquire spectral information in the visible and near-infrared range of the spectrum. This report addresses two problems which in the literature are generally addressed independently; acquisition and analysis of hyperspectral images, and acquisition and analysis of range information. The bimodal instrument described in this report consists of a LCTF-based hyperspectral system which is used to acquire spectral images in the 450-1100 nm range and a multi-line laser light used to acquire range measurements of a scene. This laser light method can be used to acquire fast range measurements as the scene is partitioned into three sub-ranges therefore reducing the acquisition time by threefold. The methods used to get calibrated hyperspectral measurements (to reflectance values) of the proposed 3D hyperspectral instrument, and range measurements (to mm) are described in this paper. A test case shows the capabilities of this instrument for producing 3D hyperspectral imagery of human skin samples.

The investigations on the optical mammography have attracted many clinical attentions, since the conventional X-ray mammography has shown some deficiencies in sensitivity, specificity, security and comfortableness. In this study, we propose an image reconstruction technique of time-domain diffuse optical tomography (DOT) for the optical mammography in the first place. This technique uses the finite-element method (FEM) solution to the Laplace-transformed coupled diffusion equations as the forward model, and develops an inverse model based on a Newton-Raphson scheme. On the basis of the preliminary reconstructed image of this technique, we also present an efficient Jacobian reduction method by the aid of image segmentation to obtain a more accurate image reconstruction. The simulative experiments reveal that the performance of reconstructed image by the aid of the image segmentation makes a notable improvement on the conventional algorithm in breast phantom image.

We present the sensitivity improvement of total internal reflection fluorescence microscopy for imaging intracellular molecular movements near cell membranes. We investigated employing dielectric films on a prism substrate for the enhancement of fluorescence emission intensity. A two-layer dielectric thin film structure using Al2O3 and SiO2 was designed and fabricated to provide the maximal field enhancement for 442 nm excitation at a reasonable angle of incidence (&Thgr;). The field enhancement achieved by the design was 8.5 at &Thgr; = 53.8º for TE polarization and confirmed experimentally using microbeads. Preliminary results in live cell imaging were obtained using quantum dots.

This paper presents a camera-based imaging photoplethysmographic (PPG) system in the remote detection of PPG signals, which can contribute to construct a 3-D blood pulsation mapping for the assessment of skin blood microcirculation at various vascular depths. Spot measurement and contact sensor have been currently addressed as the primary limitations in the utilization of conventional PPG system. The introduction of the fast digital camera inspires the development of the imaging PPG system to allow ideally non-contact monitoring from a larger field of view and different tissue depths by applying multi-wavelength illumination sources. In the present research, the imaging PPG system has the capability of capturing the PPG waveform at dual wavelengths simultaneously: 660 and 880nm. A selected region of tissue is remotely illuminated by a ring illumination source (RIS) with dual-wavelength resonant cavity light emitting diodes (RCLEDs), and the backscattered photons are captured by a 10-bit CMOS camera at a speed of 21 frames/second for each wavelength. The waveforms from the imaging system exhibit comparable functionality characters with those from the conventional contact PPG sensor in both time domain and frequency domain. The mean amplitude of PPG pulsatile component is extracted from the PPG waveforms for the mapping of blood pulsation in a 3-D format. These results strongly demonstrate the capability of the imaging PPG system in displaying the waveform and the potential in 3-D mapping of blood microcirculation by a non-contact means.

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

Diffuse Optical Tomography (DOT) involves a nonlinear optimization problem to find the tissue optical properties by measuring near-infrared light noninvasively. Many researchers used linearization methods to obtain the optical image in real time. However, the linearization procedure may neglect small but sometimes important regions such as small tumors at an early stage. Therefore, nonlinear optimization methods such as gradient- or Newton- type methods are exploited, resulting in better resolution image than that of linearization methods. But the disadvantage of nonlinear methods is that they need much computation time. To solve this trade-off dilemma between image resolution and computing time, we suggest second order inverse Born expansion algorithm in this paper. It is known that a small perturbation of photon density is represented by Born expansion with respect to the perturbation of optical coefficients, which is an infinite series of integral operators having Robin function kernel. Whereas, inverse Born expansion is an implicit representation of a small perturbation of optical coefficients by an infinite series of the integral operators with respect to the photon density and its perturbation, which is appropriate series expansion for inverse DOT problem. Solving the inverse Born expansion itself and the first order approximation correspond to nonlinear and linear method, respectively. We formulated a second order approximation of the inverse Born expansion explicitly to make numerical implementation possible and showed the convergence order of the proposed method is higher than the linear method.

In this paper, we analyze the error resulting from the discretization of the forward and inverse problems in simultaneously reconstructed optical absorption and scattering images. Our analysis indicates the mutual dependence of the forward and inverse problems, the number of sources and detectors, their configuration and the location of optical heterogeneities with respect to sources and detectors affect the extent of the error in the reconstructed optical images resulting from discretization. One important implication of the error analysis is that poor discretization of one optical coefficient results in error in the other, resulting in inter-parameter "cross-talk" due entirely to discretization.

Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

Near infrared spectroscopy (NIRS) is a relatively new non-invasive brain imaging method to measure brain activities associated with regional changes of the oxy- and deoxy- hemoglobin concentration. Typically, functional MRI or PET data are analyzed using the general linear model (GLM), in which measurements are modeled as a linear combination of explanatory variables plus an error term. However, the GLM often fails in NIRS if there exists an unknown global trend due to breathing, cardiac, vaso- motion and other experimental errors. In order to overcome these problems, we propose a wavelet-MDL based detrending algorithm. Specifically, the wavelet transform is applied to NIRS measurements to decompose them into global trends, signals and uncorrelated noise components in distinct scales. In order to prevent the over-fitting the minimum length description (MDL) principle is applied. Experimental results demonstrate that the new detrending algorithm outperforms the conventional approaches.

Fluorescence diffuse optical tomography (FT) is an emerging molecular imaging technique that can spatially resolve both fluorophore concentration and lifetime parameters. In this study, we investigated the performance of a frequency domain FT system for inclusions with various sizes and contrast levels. Due to the ill-posedness of the FT problem, the fluorescence parameters can not be recovered accurately. The reconstructed fluorescence parameters depend on the signal to background contrast and size of the compartments containing the fluorophores. Recently, imaging with multiple modalities has become a popular trend. Different modalities give different information on the subject under investigation. Here, we evaluated the improvement in FT reconstruction when structural a priori information from a second imaging modality was incorporated. The results demonstrated that the structural a priori information was crucial to be able to recover both parameters with high accuracy. Without such a priori information, the same fluorophore concentration for different object sizes could not be recovered to the same value. On the other hand, when the structural a priori information was available, both fluorescence parameters could be recovered within 15% error for all the cases.

Time variation of the bioluminescence source can cause artifacts in the tomographic images. We showed that the a priori knowledge of the light kinetics could be used to eliminate these artifacts. We performed two-dimensional simulations. We considered a 40-mm-diameter circular region with an inclusion of 6-mm-diameter located 10-mm away from the center. The measurement data was simulated using a finite element based forward solver. We modeled the non-contact measurements such that four-wavelength data was collected from four 90-degree-apart views. The results showed that the ratio of the total imaging time to the half-life of the exponentially decaying bioluminescent source was the deciding factor in the reconstruction of the source. It was also demonstrated that a priori knowledge of the source kinetics was required to perform tomographic bioluminescence imaging of short half-life bioluminescent sources and the use of spatial a priori information alone was not adequate.

A multi-dimensional thermal model was presented to explore the relationship between an embedded tumor and the resulting temperature distributions on the breast surface on purpose to be an adjunct tool for interpreting thermograms. Steady-state temperature distributions on the skin of the breast were attained by numerically solving the heat diffusion equation. The numerical results show that the temperature distributions in the thermal images of breast tumor can be significantly influenced by surface air flow and environmental temperature. Furthermore, the simulated results also show that thermography do not have sufficient sensitivity for detection of a small tumor in deeper region. Finally, the feasibility and limitations of capturing tumor information by infrared thermal imaging is discussed. Our study shows that the heat patterns over breasts can be well simulated with this comprehensive thermal model, which may be helpful for the doctor to interpret the thermograms.