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

Measurement of brain activation during an upright stepping reaction task using functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is a non-invasive brain imaging technology that uses light to measure changes in cortical hemoglobin concentrations. FNIRS measurements are recorded through fiber optic cables, which allow the participant to wear the fNIRS sensors while standing upright. Thus, fNIRS technology is well suited to study cortical brain activity during upright balance, stepping, and gait tasks. In this study, fNIRS was used to measure changes in brain activation from the frontal, motor, and premotor brain regions during an upright step task that required subjects to step laterally in response to visual cues that required executive function control. We hypothesized that cognitive processing during complex stepping cues would elicit brain activation of the frontal cortex in areas involved in cognition. Our results show increased prefrontal activation associated with the processing of the stepping cues. Moreover, these results demonstrate the potential to use fNIRS to investigate cognitive processing during cognitively demanding balance and gait studies.

Self-calibrated algorithms for diffuse optical tomography and bioluminescence tomography using relative transmission images

Reconstruction algorithms for diffuse optical tomography (DOT) and bioluminescence tomography (BLT) have been developed based on diffusion theory. The algorithms numerically solve the diffusion equation using the finite element method. The direct measurements of the uncalibrated light fluence rates by a camera are used for the reconstructions. The DOT is self-calibrated by using all possible pairs of transmission images obtained with external sources along with the relative values of the simulated data and the calculated Jacobian. The reconstruction is done in the relative domain with the cancelation of any geometrical or optical factors. The transmission measurements for the DOT are used for calibrating the bioluminescence measurements at each wavelength and then a normalized system of equations is built up which is self-calibrated for the BLT. The algorithms have been applied to a three dimensional model of the mouse (MOBY) segmented into tissue regions which are assumed to have uniform optical properties. The DOT uses the direct method for calculating the Jacobian. The BLT uses a reduced space of eigenvectors of the Green's function with iterative shrinking of the permissible source region. The reconstruction results of the DOT and BLT algorithms show good agreement with the actual values when using either absolute or relative data. Even a small calibration error causes significant degradation of the reconstructions based on absolute data.

Automatic and robust calibration of optical detector arrays for biomedical diffuse optical spectroscopy

The design and testing of a new, fully automated, calibration approach is described. The process was used to calibrate an image-guided diffuse optical spectroscopy system with 16 photomultiplier tubes (PMTs), but can be extended to any large array of optical detectors and associated imaging geometry. The design goals were accomplished by developing a routine for robust automated calibration of the multi-detector array within 45 minutes. Our process was able to characterize individual detectors to a median norm of the residuals of 0.03 V for amplitude and 4.4 degrees in phase and achieved less than 5% variation between all the detectors at the 95% confidence interval for equivalent measurements. Repeatability of the calibrated data from the imaging system was found to be within 0.05 V for amplitude and 0.2 degrees for phase, and was used to evaluate tissue-simulating phantoms in two separate imaging geometries. Spectroscopic imaging of total hemoglobin concentration was recovered to within 5% of the true value in both cases. Future work will focus on streamlining the technology for use in a clinical setting with expectations of achieving accurate quantification of suspicious lesions in the breast.

Determination of optical properties in heterogeneous turbid media using a cylindrical diffusing fiber

For interstitial photodynamic therapy (PDT), cylindrical diffusing fibers (CDFs) are often used to deliver light. This study examines the feasibility and accuracy of using CDFs to characterize the absorption (μ(a)) and reduced scattering (μ'(s)) coefficients of heterogeneous turbid media. Measurements were performed in tissue-simulating phantoms with μ(a) between 0.1 and 1 cm(-1) and μ'(s) between 3 and 10 cm(-1) with CDFs 2 to 4 cm in length. Optical properties were determined by fitting the measured light fluence rate profiles at a fixed distance from the CDF axis using a heterogeneous kernel model in which the cylindrical diffusing fiber is treated as a series of point sources. The resulting optical properties were compared with independent measurement using a point source method. In a homogenous medium, we are able to determine the absorption coefficient μ(a) using a value of μ'(s) determined a priori (uniform fit) or μ'(s) obtained by fitting (variable fit) with standard (maximum) deviations of 6% (18%) and 18% (44%), respectively. However, the CDF method is found to be insensitive to variations in μ'(s), thus requiring a complementary method such as using a point source for determination of μ'(s). The error for determining μ(a) decreases in very heterogeneous turbid media because of the local absorption extremes. The data acquisition time for obtaining the one-dimensional optical properties distribution is less than 8 s. This method can result in dramatically improved accuracy of light fluence rate calculation for CDFs for prostate PDT in vivo when the same model and geometry is used for forward calculations using the extrapolated tissue optical properties.

Multichannel diffuse optical Raman tomography for bone characterization in vivo: a phantom study

Raman spectroscopy is used to gather information on the mineral and organic components of bone tissue to analyze their composition. By measuring the Raman signal of bone through spatially offset Raman spectroscopy the health of the bone can be determined. We've customized a system with 8 collection channels that consist of individual fibers, which are coupled to separate spectrometers and cooled CCDs. This parallel detection system was used to scan gelatin phantoms with Teflon inclusions of two sizes. Raman signals were decoupled from the autofluorescence background using channel specific polynomial fitting. Images with high contrast to background ratios of Raman yield and accurate spatial resolution were recovered using a model-based diffuse tomography approach.

Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise

Bioluminescence Tomography attempts to quantify 3-dimensional luminophore distributions from surface measurements of the light distribution. The reconstruction problem is typically severely under-determined due to the number and location of measurements, but in certain cases the molecules or cells of interest form localised clusters, resulting in a distribution of luminophores that is spatially sparse. A Conjugate Gradient-based reconstruction algorithm using Compressive Sensing was designed to take advantage of this sparsity, using a multistage sparsity reduction approach to remove the need to choose sparsity weighting a priori. Numerical simulations were used to examine the effect of noise on reconstruction accuracy. Tomographic bioluminescence measurements of a Caliper XPM-2 Phantom Mouse were acquired and reconstructions from simulation and this experimental data show that Compressive Sensing-based reconstruction is superior to standard reconstruction techniques, particularly in the presence of noise.

Singular value decomposition based regularization prior to spectral mixing improves crosstalk in dynamic imaging using spectral diffuse optical tomography

The spectrally constrained diffuse optical tomography (DOT) method relies on incorporating spectral prior information directly into the image reconstruction algorithm, thereby correlating the underlying optical properties across multiple wavelengths. Although this method has been shown to provide a solution that is stable, the use of conventional Tikhonov-type regularization techniques can lead to additional crosstalk between parameters, particularly in linear, single-step dynamic imaging applications. This is due mainly to the suboptimal regularization of the spectral Jacobian matrix, which smoothes not only the image-data space, but also the spectral mapping space. In this work a novel regularization technique based on the singular value decomposition (SVD) is presented that preserves the spectral prior information while regularizing the Jacobian matrix, leading to dramatically reduced crosstalk between the recovered parameters. Using simulated data, images of changes in oxygenated and deoxygenated hemoglobin concentrations are reconstructed via the SVD-based approach and compared with images reconstructed by using non-spectral and conventional spectral methods. In a 2D, two wavelength example, it is shown that the proposed approach provides a 98% reduction in crosstalk between recovered parameters as compared with conventional spectral reconstruction algorithms, and 60% as compared with non-spectrally constrained algorithms. Using a subject specific multilayered model of the human head, a noiseless dynamic simulation of cortical activation is performed to further demonstrate such improvement in crosstalk. However, with the addition of realistic noise in the data, both non-spectral and proposed algorithms perform similarly, indicating that the use of spectrally constrained reconstruction algorithms in dynamic DOT may be limited by the contrast of the signal as well as the noise characteristics of the system.

Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography

High-density diffuse optical tomography (HD-DOT) is an emerging technique for visualizing the internal state of biological tissues. The large number of overlapping measurement channels due to the use of high-density probe arrays permits the reconstruction of the internal optical properties, even with a reflectance-only measurement. However, accurate three-dimensional reconstruction is still a challenging problem. First, the exponentially decaying sensitivity causes a systematic depth-localization error. Second, the nature of diffusive light makes the image blurred. In this paper, we propose a three-dimensional reconstruction method that overcomes these two problems by introducing sensitivity-normalized regularization and sparsity into the hierarchical Bayesian method. Phantom experiments were performed to validate the proposed method under three conditions of probe interval: 26 mm, 18.4 mm, and 13 mm. We found that two absorbers with distances shorter than the probe interval could be discriminated under the high-density conditions of 18.4-mm and 13-mm intervals. This discrimination ability was possible even if the depths of the two absorbers were different from each other. These results show the high spatial resolution of the proposed method in both depth and horizontal directions.

A digital x-ray tomosynthesis coupled near infrared spectral tomography system for dual-modality breast imaging

A Near Infrared Spectral Tomography (NIRST) system has been developed and integrated into a commercial Digital Breast Tomosynthesis (DBT) scanner to allow structural and functional imaging of breast in vivo. The NIRST instrument uses an 8-wavelength continuous wave (CW) laser-based scanning source assembly and a 75-element silicon photodiode solid-state detector panel to produce dense spectral and spatial projection data from which spectrally constrained 3D tomographic images of tissue chromophores are produced. Integration of the optical imaging system into the DBT scanner allows direct co-registration of the optical and DBT images, while also facilitating the synergistic use of x-ray contrast as anatomical priors in optical image reconstruction. Currently, the total scan time for a combined NIRST-DBT exam is ~50s with data collection from 8 wavelengths in the optical scan requiring ~42s to complete. The system was tested in breast simulating phantoms constructed using intralipid and blood in an agarose matrix with a 3 cm x 2 cm cylindrical inclusion at 1 cm depth from the surface. Diffuse image reconstruction of total hemoglobin (HbT) concentration resulted in accurate recovery of the lateral size and position of the inclusion to within 6% and 8%, respectively. Use of DBT structural priors in the NIRST reconstruction process improved the quantitative accuracy of the HbT recovery, and led to linear changes in imaged versus actual contrast, underscoring the advantages of dual-modality optical imaging approaches. The quantitative accuracy of the system can be further improved with independent measurements of scattering properties through integration of frequency or time domain data.

Computed tomography-guided time-domain diffuse fluorescence tomography in small animals for localization of cancer biomarkers

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals. Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity, while our group and a few others have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model. The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control, laser referencing, and co-registration with a small animal computed tomography (microCT) system. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging. Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Photon diffusion in a homogeneous medium bounded externally or internally by an infinitely long circular cylindrical applicator. IV. Frequency-domain analysis

Part IV examines frequency-domain photon diffusion in a homogeneous medium enclosed by a "concave" circular cylindrical applicator or enclosing a "convex" circular cylindrical applicator, both geometries being infinite in the longitudinal dimension. The aim is to assess by analogical and finite-element methods the changes of AC amplitude, modulation depth, and phase with respect to the line-of-sight source-detector distance for a source and a detector located along the azimuthal or longitudinal direction on the concave or convex medium-applicator interface. By comparing to their counterparts along a straight line on a semi-infinite medium-applicator interface, for the same line-of-sight source-detector distance, it is found that: (1) the decay-rate of AC photon fluence is smaller along the azimuthal direction and greater along the longitudinal direction on the concave interface, (2) the decay-rate of AC photon fluence is greater along the azimuthal direction and smaller along the longitudinal direction on the convex interface, (3) the modulation depth along both azimuthal and longitudinal directions decays more slowly on the concave interface and faster on the convex interface, and (4) the phase along both azimuthal and longitudinal directions increases more slowly on the concave interface and faster on the convex interface.

A multi-view time-domain non-contact diffuse optical tomography scanner with dual wavelength detection for intrinsic and fluorescence small animal imaging

We present a non-contact diffuse optical tomography (DOT) scanner with multi-view detection (over 360°) for localizing fluorescent markers in scattering and absorbing media, in particular small animals. It relies on time-domain detection after short pulse laser excitation. Ultrafast time-correlated single photon counting and photomultiplier tubes are used for time-domain measurements. For light collection, seven free-space optics non-contact dual wavelength detection channels comprising 14 detectors overall are placed around the subject, allowing the measurement of time point-spread functions at both excitation and fluorescence wavelengths. The scanner is endowed with a stereo camera pair for measuring the outer shape of the subject in 3D. Surface and DOT measurements are acquired simultaneously with the same laser beam. The hardware and software architecture of the scanner are discussed. Phantoms are used to validate the instrument. Results on the localization of fluorescent point-like inclusions immersed in a scattering and absorbing object are presented. The localization algorithm relies on distance ranging based on the measurement of early photons arrival times at different positions around the subject. This requires exquisite timing accuracy from the scanner. Further exploiting this capability, we show results on the effect of a scattering hetereogenity on the arrival time of early photons. These results demonstrate that our scanner provides all that is necessary for reconstructing images of small animals using full tomographic reconstruction algorithms, which will be the next step. Through its free-space optics design and the short pulse laser used, our scanner shows unprecedented timing resolution compared to other multi-view time-domain scanners.

Image quality analysis of high-density diffuse optical tomography incorporating a subject-specific head model

High-density diffuse optical tomography (HD-DOT) methods have shown significant improvement in localization accuracy and image resolution compared to traditional topographic near infrared spectroscopy of the human brain. In this work we provide a comprehensive evaluation of image quality in visual cortex mapping via a simulation study with the use of an anatomical head model derived from MRI data of a human subject. A model of individual head anatomy provides the surface shape and internal structure that allow for the construction of a more realistic physical model for the forward problem, as well as the use of a structural constraint in the inverse problem. The HD-DOT model utilized here incorporates multiple source-detector separations with continuous-wave data with added noise based on experimental results. To evaluate image quality we quantify the localization error and localized volume at half maximum (LVHM) throughout a region of interest within the visual cortex and systematically analyze the use of whole-brain tissue spatial constraint within image reconstruction. Our results demonstrate that an image quality with less than 10 mm in localization error and 1000 m³ in LVHM can be obtained up to 13 mm below the scalp surface with a typical unconstrained reconstruction and up to 18 mm deep when a whole-brain spatial constraint based on the brain tissue is utilized.

Model-resolution based regularization improves near infrared diffuse optical tomography

Diffuse optical tomographic imaging is known to be an ill-posed problem, and a penalty/regularization term is used in image reconstruction (inverse problem) to overcome this limitation. Two schemes that are prevalent are spatially varying (exponential) and constant (standard) regularizations/penalties. A scheme that is also spatially varying but uses the model information is introduced based on the model-resolution matrix. This scheme, along with exponential and standard regularization schemes, is evaluated objectively based on model-resolution and data-resolution matrices. This objective analysis showed that resolution characteristics are better for spatially varying penalties compared to standard regularization; and among spatially varying regularization schemes, the model-resolution based regularization fares well in providing improved data-resolution and model-resolution characteristics. The verification of the same is achieved by performing numerical experiments in reconstructing 1% noisy data involving simple two- and three-dimensional imaging domains.

Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe

We quantify the variability in diffuse optical tomography (DOT) sensitivity over the cortical surface in eight young adult subjects. We use the 10/5 electroencephalography system as a basis for our whole-head optical high-density probe design. The contrast-to-noise ratio (CNR) is calculated along with the percentage of the cortex that is above a CNR = 0 dB threshold. We also quantify the effect of including vasculature on the forward model and list our assumptions that allow us to estimate light penetration depth in the head. We show that using the 10/5 system for the optical probe design allows for the measurement of 37% of the cortical surface on average, with a mean CNR in the visible region of 5.5 dB. Certain anatomical regions, such as the lateral occipital cortex, had a very high percentage above the CNR threshold, while other regions such as the cingulate cortex were not measurable. Vasculature blocked optical sensitivity over 1% of the cortex. Cortical coverage was positively correlated with intracranial volume and relative cerebrospinal fluid volume, and negatively correlated with relative scalp volume and skull volume. These contributions allow experimenters to understand how anatomical variation in a subject population may impact DOT or functional near-infrared spectroscopy measurements.

Photon diffusion in a homogeneous medium bounded externally or internally by an infinitely long circular cylindrical applicator. III. Synthetic study of continuous-wave photon fluence rate along unique spiral paths

This is Part III of the work that examines photon diffusion in a scattering-dominant medium enclosed by a "concave" circular cylindrical applicator or enclosing a "convex" circular cylindrical applicator. In Part II of this work Zhang et al. [J. Opt. Soc. Am. A, 66 (2011)] predicted that, on the tissue-applicator interface of either "concave" or "convex" geometry, there exists a unique set of spiral paths, along which the steady-state photon fluence rate decays at a rate equal to that along a straight line on a planar semi-infinite interface, for the same line-of-sight source-detector distance. This phenomenon of steady-state photon diffusion is referred to as "straight-line-resembling-spiral paths" (abbreviated as "spiral paths"). This Part III study develops analytic approaches to the spiral paths associated with geometry of a large radial dimension and presents spiral paths found numerically for geometry of a small radial dimension. This Part III study also examines whether the spiral paths associated with a homogeneous medium are a good approximation for the medium containing heterogeneity. The heterogeneity is limited to an anomaly that is aligned azimuthally with the spiral paths and has either positive or negative contrast of the absorption or scattering coefficient over the background medium. For a weak-contrast anomaly the perturbation by it to the photon fluence rate along the spiral paths is found by applying a well-established perturbation analysis in cylindrical coordinates. For a strong-contrast anomaly the change by it to the photon fluence rate along the spiral paths is computed using the finite-element method. For the investigated heterogeneous-medium cases the photon fluence rate along the homogeneous-medium associated spiral paths is macroscopically indistinguishable from, and microscopically close to, that along a straight line on a planar semi-infinite interface.

Information loss and reconstruction in diffuse fluorescence tomography

This paper is a theoretical exploration of spatial resolution in diffuse fluorescence tomography. It is demonstrated that, given a fixed imaging geometry, one cannot-relative to standard techniques such as Tikhonov regularization and truncated singular value decomposition-improve the spatial resolution of the optical reconstructions via increasing the node density of the mesh considered for modeling light transport. Using techniques from linear algebra, it is shown that, as one increases the number of nodes beyond the number of measurements, information is lost by the forward model. It is demonstrated that this information cannot be recovered using various common reconstruction techniques. Evidence is provided showing that this phenomenon is related to the smoothing properties of the elliptic forward model that is used in the diffusion approximation to light transport in tissue. This argues for reconstruction techniques that are sensitive to boundaries, such as L1-reconstruction and the use of priors, as well as the natural approach of building a measurement geometry that reflects the desired image resolution.

Functional near-infrared spectroscopy (fNIRS) of brain function during active balancing using a video game system

Functional near-infrared spectroscopy (fNIRS) is a portable, non-invasive, brain imaging technology that uses low levels of non-ionizing light to record changes in cerebral blood flow in the brain through optical sensors placed on the surface of the scalp. These signals are recorded via flexible fiber optic cables, which allow neuroimaging experiments to be conducted on participants while performing tasks such as standing or walking. FNIRS has the potential to provide new insights into the evolution of brain activation during ambulatory motor learning tasks and standing tasks to probe balance and vestibular function. In this study, a 32 channel fNIRS system was used to record blood flow changes in the frontal, motor, sensory, and temporal cortices during active balancing associated with playing a video game simulating downhill skiing (Nintendo Wii™; Wii-fit™). Using fNIRS, we found activation of superior temporal gyrus, which was modulated by the difficulty of the balance task. This region had been previously implicated in vestibular function from other animal and human studies.

Quantitative Cherenkov emission spectroscopy for tissue oxygenation assessment

Measurements of Cherenkov emission in tissue during radiation therapy are shown to enable estimation of hemoglobin oxygen saturation non-invasively, through spectral fitting of the spontaneous emissions from the treated tissue. Tissue oxygenation plays a critical role in the efficacy of radiation therapy to kill tumor tissue. Yet in-vivo measurement of this has remained elusive in routine use because of the complexity of oxygen measurement techniques. There is a spectrally broad emission of Cherenkov light that is induced during the time of irradiation, and as this travels through tissue from the point of the radiation deposition, the tissue absorption and scatter impart spectral changes. These changes can be quantified by diffuse spectral fitting of the signal. Thus Cherenkov emission spectroscopy is demonstrated for the first time quantitatively in vitro and qualitatively in vivo, and has potential for real-time online tracking of tissue oxygen during radiation therapy when fully characterized and developed.

Characterization of tissue optical properties for prostate PDT using interstitial diffuse optical tomography

Photodynamic therapy (PDT) is an important treatment modality for localized diseases such as prostate cancer. In prostate PDT, light distribution is an important factor because it is directly related to treatment efficacy. During PDT, light distribution is determined by tissue optical property distributions (or heterogeneity). In this study, an interstitial diffuse optical tomography (iDOT) method was used to characterize optical properties in tissues. Optical properties (absorption and reduced scattering coefficients) of the prostate gland were reconstructed by solving the inverse problem using an adjoint model based on diffusion equation using a modified matlab public user code NIRFAST. In the modified NIRFAST method, linear sources were modeled for the reconstruction. Cross talking between absorption coefficients and reduced scattering coefficients were studied to have minimal effect, and a constrained optical property method (set either absorption coefficient or reduced scattering coefficient to be homogeneous) is also studied. A prostate phantom with optical anomalies was used to verify the iDOT method. The reconstructed results were compared with the known optical properties, and the spatial distribution of optical properties for this phantom was successfully reconstructed.

Low-cost three-dimensional imaging system combining fluorescence and ultrasound

In this paper, we present a dual-modality imaging system combining three-dimensional (3D) continuous-wave transillumination fluorescence tomography with 3D ultrasound (US) imaging. We validated the system with two phantoms, one containing fluorescent inclusions (Cy5.5) at different depths, and another varying-thickness semicylindrical phantom. Using raster scanning, the combined fluorescence/US system was used to collect the boundary fluorescent emission in the X-Y plane, as well as recovered the 3D surface and position of the inclusions from US signals. US images were segmented to provide soft priors for the fluorescence image reconstruction. Phantom results demonstrated that with priors derived from the US images, the fluorescent reconstruction quality was significantly improved. As further evaluation, we show pilot in vivo results using an Apo-E mouse to assess the feasibility and performance of this system in animal studies. Limitations and potential to be used in artherosclerosis studies are then discussed.

Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography

Topographic non-invasive near infrared spectroscopy (NIRS) has become a well-established tool for functional brain imaging. Applying up to 100 optodes over the head of a subject, allows achieving a spatial resolution in the centimeter range. This resolution is poor compared to other functional imaging tools. However, recently it was shown that diffuse optical tomography (DOT) as an extension of NIRS based on high-density (HD) probe arrays and supplemented by an advanced image reconstruction procedure allows describing activation patterns with a spatial resolution in the millimeter range. Building on these findings, we hypothesize that HD-DOT may render very focal activations accessible which would be missed by the traditionally used sparse arrays. We examined activation patterns in the primary somatosensory cortex, since its somatotopic organization is very fine-grained. We performed a vibrotactile stimulation study of the first and fifth finger in eight human subjects, using a 900-channel continuous-wave DOT imaging system for achieving a higher resolution than conventional topographic NIRS. To compare the results to a well-established high-resolution imaging technique, the same paradigm was investigated in the same subjects by means of functional magnetic resonance imaging (fMRI). In this work, we tested the advantage of ultrahigh-density probe arrays and show that highly focal activations would be missed by classical next-nearest neighbor NIRS approach, but also by DOT, when using a sparse probe array. Distinct activation patterns for both fingers correlated well with the expected neuroanatomy in five of eight subjects. Additionally we show that activation for different fingers is projected to different tissue depths in the DOT image. Comparison to the fMRI data yielded similar activation foci in seven out of ten finger representations in these five subjects when comparing the lateral localization of DOT and fMRI results.

Implicit and explicit prior information in near-infrared spectral imaging: accuracy, quantification and diagnostic value

Near-infrared spectroscopy (NIRS) of tissue provides quantification of absorbers, scattering and luminescent agents in bulk tissue through the use of measurement data and assumptions. Prior knowledge can be critical about things such as (i) the tissue shape and/or structure, (ii) spectral constituents, (iii) limits on parameters, (iv) demographic or biomarker data, and (v) biophysical models of the temporal signal shapes. A general framework of NIRS imaging with prior information is presented, showing that prior information datasets could be incorporated at any step in the NIRS process, with the general workflow being: (i) data acquisition, (ii) pre-processing, (iii) forward model, (iv) inversion/reconstruction, (v) post-processing, and (vi) interpretation/diagnosis. Most of the development in NIRS has used ad hoc or empirical implementations of prior information such as pre-measured absorber or fluorophore spectra, or tissue shapes as estimated by additional imaging tools. A comprehensive analysis would examine what prior information maximizes the accuracy in recovery and value for medical diagnosis, when implemented at separate stages of the NIRS sequence. Individual applications of prior information can show increases in accuracy or improved ability to estimate biochemical features of tissue, while other approaches may not. Most beneficial inclusion of prior information has been in the inversion/reconstruction process, because it solves the mathematical intractability. However, it is not clear that this is always the most beneficial stage.

Towards the next generation of near-infrared spectroscopy

Although near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, it has also been developing into a useful tool for neuroimaging studies (functional NIRS). Over the past 30 years, technology has developed and NIRS has found a wide range of applications. However, the accuracy and reliability of NIRS have not yet been widely accepted, mainly because of the difficulties in selective and quantitative detection of signals arising in cerebral tissue, which subject the use of NIRS to a number of practical restrictions. This review summarizes the strengths and advantages of NIRS over other neuroimaging modalities and demonstrates specific examples. The issues of selective quantitative measurement of cerebral haemoglobin during brain activation are also discussed, together with the problems of applying the methods of functional magnetic resonance imaging data analysis to NIRS data analysis. Finally, near-infrared optical tomography--the next generation of NIRS--is described as a potential technique to overcome the limitations of NIRS.

Biomedical tissue phantoms with controlled geometric and optical properties for Raman spectroscopy and tomography

To support the translation of Raman spectroscopy into clinical applications, synthetic models are needed to accurately test, optimize and validate prototype fiber optic instrumentation. Synthetic models (also called tissue phantoms) are widely used for developing and testing optical instrumentation for diffuse reflectance, fluorescence, and Raman spectroscopies. While existing tissue phantoms accurately model tissue optical scattering and absorption, they do not typically model the anatomic shapes and chemical composition of tissue. Because Raman spectroscopy is sensitive to molecular composition, Raman tissue phantoms should also approximate the bulk tissue composition. We describe the fabrication and characterization of tissue phantoms for Raman tomography and spectroscopy. These phantoms have controlled chemical and optical properties, and also multilayer morphologies which approximate the appropriate anatomic shapes. Tissue phantoms were fabricated to support on-going Raman studies by simulating the human wrist and rat leg. Surface meshes (triangle patch models) were generated from computed tomography (CT) images of a human arm and rat leg. Rapid prototyping was used to print mold templates with complex geometric patterns. Plastic casting techniques used for movie special effects were adapted to fabricate molds from the rapid prototypes, and finally to cast multilayer gelatin tissue phantoms. The gelatin base was enriched with additives to model the approximate chemistry and optical properties of individual tissue layers. Additional studies were performed to determine optimal casting conditions, phantom stability, layer delamination and chemical diffusion between layers. Recovery of diffuse reflectance and Raman spectra in tissue phantoms varied with probe placement. These phantoms enable optimization of probe placement for human or rat studies. These multilayer tissue phantoms with complex geometries are shown to be stable, with minimal layer delamination and chemical diffusion.

A three-dimensional finite element model and image reconstruction algorithm for time-domain fluorescence imaging in highly scattering media

In this work, development and evaluation of a three-dimensional (3D) finite element model (FEM) based on the diffusion approximation of time-domain (TD) near-infrared fluorescence light transport in biological tissue is presented. This model allows both excitation and fluorescence temporal point-spread function (TPSF) data to be generated for heterogeneous scattering and absorbing media of arbitrary geometry. The TD FEM is evaluated via comparisons with analytical and Monte Carlo (MC) calculations and is shown to provide a quantitative accuracy which has less than 0.72% error in intensity and less than 37 ps error for mean time. The use of the Born-Ratio normalized data is demonstrated to reduce data mismatch between MC and FEM to less than 0.22% for intensity and less than 22 ps in mean time. An image reconstruction framework, based on a 3D FEM formulation, is outlined and simulation results based on a heterogeneous mouse model with a source of fluorescence in the pancreas is presented. It is shown that using early photons (i.e. the photons detected within the first 200 ps of the TPSF) improves the spatial resolution compared to using continuous-wave signals. It is also demonstrated, as expected, that the utilization of two time gates (early and latest photons) can improve the accuracy both in terms of spatial resolution and recovered contrast.

Imaging workflow and calibration for CT-guided time-domain fluorescence tomography

In this study, several key optimization steps are outlined for a non-contact, time-correlated single photon counting small animal optical tomography system, using simultaneous collection of both fluorescence and transmittance data. The system is presented for time-domain image reconstruction in vivo, illustrating the sensitivity from single photon counting and the calibration steps needed to accurately process the data. In particular, laser time- and amplitude-referencing, detector and filter calibrations, and collection of a suitable instrument response function are all presented in the context of time-domain fluorescence tomography and a fully automated workflow is described. Preliminary phantom time-domain reconstructed images demonstrate the fidelity of the workflow for fluorescence tomography based on signal from multiple time gates.

Bioluminescence tomography using eigenvectors expansion and iterative solution for the optimized permissible source region

A reconstruction algorithm for bioluminescence tomography (BLT) has been developed. The algorithm numerically calculates the Green's function at different wavelengths using the diffusion equation and finite element method. The optical properties used in calculating the Green's function are reconstructed using diffuse optical tomography (DOT) and assuming anatomical information is provided by x-ray computed tomography or other methods. A symmetric system of equations is formed using the Green's function and the measured light fluence rate and the resulting eigenvalue problem is solved to get the eigenvectors of this symmetric system of equations. A space can be formed from the eigenvectors obtained and the reconstructed source is written as an expansion of the eigenvectors corresponding to non-zero eigenvalues. The coefficients of the expansion are found to obtain the reconstructed BL source distribution. The problem is solved iteratively by using a permissible source region that is shrunk by removing nodes with low probability to contribute to the source. Throughout this process the permissible region shrinks from the entire object to just a few nodes. The best estimate of the reconstructed source is chosen that which minimizes the difference between the calculated and measured light fluence rates. 3D simulations presented here show that the reconstructed source is in good agreement with the actual source in terms of locations, magnitudes, sizes, and total powers for both localized multiple sources and large inhomogeneous source distributions.

Toward whole-body optical imaging of rats using single-photon counting fluorescence tomography

We used single-photon counting (SPC) detection for diffuse fluorescence tomography to image nanomolar (nM) concentrations of reporter dyes through a rat. Detailed phantom data are presented to show that every centimeter increase in tissue thickness leads to 1 order of magnitude decrease in the minimum fluorophore concentration detectable for a given detector sensitivity. Specifically, here, detection of Alexa Fluor 647 dyes is shown to be achievable for concentrations as low as 1 nM (<200 fM) through more than 5 cm in tissue phantoms, which indicates that this is feasible in larger rodent models. Because it is possible to detect sub-nM fluorescent inclusions with SPC technology in rats, it follows that it is possible to localize subpicomolar fluorophore concentrations in mice, putting the concentration sensitivity limits on the same order as nuclear medicine methods.

The utility of direct-current as compared to frequency domain measurements in spectrally-constrained diffuse optical tomography toward cancer imaging

This work investigates, by means of analytical and simulation studies, the performance of spectrally-constrained image reconstruction in Continuous-Wave or Direct-Current (DC) and Frequency Domain (FD) near-infrared optical tomography. A recent analytic approach for estimating the accuracy of target recovery and the level of background artifact for optical tomography at single wavelength, based on the analysis of parametric reconstruction uncertainty level (PRUL), is extended to spectrally-constrained optical tomography. The analytical model is implemented to rank three sets of wavelengths that had been used as spectral prior in an independent experimental study. Subsequent simulation appraises the recovery of oxygenated hemoglobin (HbO), deoxygenated hemoglobin (Hb), water (H2O), scattering amplitude (A), and scattering power (b) using DC-only, DC-excluded FD, and DC-included FD, based on the three sets of wavelengths as the spectral prior. The simulation results support the analytic ranking of the performance of the three sets of spectral priors, and generally agree with the performance outcome of DC-only versus that of DC-excluded FD and DC-included FD. Specifically, this study indicate that: 1) the rank of overall quality of chromophore recovery is Hb, H2O, and HbO from the highest to lowest; and in the scattering part the A is always better recovered than b. This outcome does suggest that the DC-only information gives rise to unique solution to the image reconstruction routine under the given spectral prior. 2) DC-information is not-redundant in FD-reconstruction, as the artifact levels of DC-included FD reconstruction are always lower than those of DC-excluded FD. 3) The artifact level as represented by the noise-to-contrast-ratio is almost always the lowest in DC-only, leading to generally better resolution of multiple targets of identical contrasts over the background than in FD. However, the FD could outperform DC in the recovery of scattering properties including both A and b when the spectral prior is less optimal, implying the benefit of phase-information in scattering recovery in the context of spectrally-constrained optical tomography.

Improvement of absorption and scattering discrimination by selection of sensitive points on temporal profile in diffuse optical tomography

We present a new method allowing the reconstruction of 3D time-domain diffuse optical tomography images, based on the time-dependent diffusion equation and an iterative algorithm (ART) using specific points on the temporal profiles. The first advantage of our method versus the full time-resolved scheme consists in considerably reducing the inverse problem resolution time. Secondly, in the presence of scattering heterogeneities, our method provides images of better quality comparatively to classical methods using full-time data or the first moments of the profiles.

Remote positioning optical breast magnetic resonance coil for slice-selection during image-guided near-infrared spectroscopy of breast cancer

The design and testing of a pneumatic optical positioning interface produced with the goal of improving fiber positioning in magnetic resonance (MR)-guided diffuse spectral imaging of breast cancer is presented. The system was created for vertical positioning of optical fibers inside the MR bore during a patient exam to target suspicious lesions with MR scans for reference and collect multiple planes of optical data. The interface includes new fiber plates for mechanical and optical coupling to the breast, and was tested in phantoms and human imaging. Reconstructions with data taken in the new interface show acceptable linearity over different absorber concentrations (residual norm = 0.067), and exhibit good contrast recovery at different imaging planes, which is consistent with previous work. An example of human breast imaging through the new interface is shown and a discussion of how it compares to other patient interfaces for breast imaging is presented. Design goals of increasing the available degrees of freedom for fiber positioning while maintaining good patient-fiber contact and comfort were accomplished. This interface allows improved volumetric imaging with interactive and accurate slice selection to quantify targeted suspicious lesions.

Acousto-optic-assisted diffuse optical tomography

We introduce and experimentally demonstrate acousto-optic-assisted diffuse optical tomography (DOT) using a holography-based acousto-optic setup. The method is based on probing a scattering medium with a localized acoustical modulation of the phase of the scattered light. The optical properties of the scattering medium are recovered with ultrasound-limited resolution by applying DOT reconstruction methods on a set of the measured intensities of light, modulated at different locations throughout the medium.

Diffuse photon remission along unique spiral paths on a cylindrical interface is modeled by photon remission along a straight line on a semi-infinite interface

We demonstrate that, for a long cylindrical applicator that interfaces concavely or convexly with a scattering-dominant medium, a unique set of spiral-shaped directions exist on the tissue-applicator interface, along which the diffuse photon remission is essentially modeled by the photon remission along a straight line on a semi-infinite interface. This interesting phenomenon, which is validated in steady state in this work by finite-element and Monte Carlo methods, may be particularly useful for simplifying deeper-tissue sensing in endoscopic imaging geometry.

Photon diffusion in a homogeneous medium bounded externally or internally by an infinitely long circular cylindrical applicator. II. Quantitative examinations of the steady-state theory

This is Part II of the work that examines photon diffusion in a homogenous medium enclosed by a concave circular cylindrical applicator or enclosing a convex circular cylindrical applicator. Part I of this work [J. Opt. Soc. Am. A 27, 648 (2010)] analytically examined the steady-state photon diffusion between a source and a detector for two specific cases: (1) the detector is placed only azimuthally with respect to the source, and (2) the detector is placed only longitudinally with respect to the source, in the infinitely long concave and convex applicator geometries. For the first case, it was predicted that the decay rate of photon fluence would become smaller in the concave geometry and greater in the convex geometry than that in the semi-infinite geometry for the same source-detector distance. For the second case, it was projected that the decay rate of photon fluence would be greater in the concave geometry and smaller in the convex geometry than that in the semi-infinite geometry for the same source-detector distance. This Part II of the work quantitatively examines these predictions from Part I through several approaches, including (a) the finite-element method, (b) the Monte Carlo simulation, and (c) experimental measurement. Despite that the quantitative examinations have to be conducted for finite cylinder applicators with large length-to-radius ratio to approximate the infinite-length condition modeled in Part I, the results obtained by these quantitative methods for two concave and three convex applicator dimensions validated the qualitative trend predicted by Part I and verified the quantitative accuracy of the analytic treatment of Part I in the diffusion regime of the measurement, at a given set of absorption and reduced scattering coefficients of the medium.

Optical mammography: Diffuse optical imaging of breast cancer

Existing imaging modalities for breast cancer screening, diagnosis and therapy monitoring, namely X-ray mammography and magnetic resonance imaging, have been proven to have limitations. Diffuse optical imaging is a set of non-invasive imaging modalities that use near-infrared light, which can be an alternative, if not replacement, to those existing modalities. This review covers the background knowledge, recent clinical outcome, and future outlook of this newly emerging medical imaging modality.

Improved bioluminescence and fluorescence reconstruction algorithms using diffuse optical tomography, normalized data, and optimized selection of the permissible source region

Reconstruction algorithms are presented for two-step solutions of the bioluminescence tomography (BLT) and the fluorescence tomography (FT) problems. In the first step, a continuous wave (cw) diffuse optical tomography (DOT) algorithm is used to reconstruct the tissue optical properties assuming known anatomical information provided by x-ray computed tomography or other methods. Minimization problems are formed based on L1 norm objective functions, where normalized values for the light fluence rates and the corresponding Green's functions are used. Then an iterative minimization solution shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. Throughout this process the permissible region shrinks from the entire object to just a few points. The optimum reconstructed bioluminescence and fluorescence distributions are chosen to be the results of the iteration corresponding to the permissible region where the objective function has its global minimum This provides efficient BLT and FT reconstruction algorithms without the need for a priori information about the bioluminescence sources or the fluorophore concentration. Multiple small sources and large distributed sources can be reconstructed with good accuracy for the location and the total source power for BLT and the total number of fluorophore molecules for the FT. For non-uniform distributed sources, the size and magnitude become degenerate due to the degrees of freedom available for possible solutions. However, increasing the number of data points by increasing the number of excitation sources can improve the accuracy of reconstruction for non-uniform fluorophore distributions.

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

A near-IR (NIR) tomography system with spectral-encoded sources was built to quantify the temporal contrast in human breast tissue using guidance from magnetic resonance imaging. The systems were integrated with a custom breast coil interface to provide simultaneous acquisition. The NIR signal was synchronized to simultaneous finger pulse oximeter plethysmogram, which offered a frequency reference. A 0.1 s temporal delay of the absorption pulse within adipose tissue relative to fibroglandular tissue was found, in an initial human study, showing the potential for novel contrast imaging of fast flow signals in deep tissue.

A random-effects model for group-level analysis of diffuse optical brain imaging

Diffuse optical imaging is a non-invasive technique for measuring changes in blood oxygenation in the brain. This technique is based on the temporally and spatially resolved recording of optical absorption in tissue within the near-infrared range of light. Optical imaging can be used to study functional brain activity similar to functional MRI. However, group level comparisons of brain activity from diffuse optical data are difficult due to registration of optical sensors between subjects. In addition, optical signals are sensitive to inter-subject differences in cranial anatomy and the specific arrangement of optical sensors relative to the underlying functional region. These factors can give rise to partial volume errors and loss of sensitivity and therefore must be accounted for in combining data from multiple subjects. In this work, we describe an image reconstruction approach using a parametric Bayesian model that simultaneously reconstructs group-level images of brain activity in the context of a random-effects analysis. Using this model, we demonstrate that localization accuracy and the statistical effects size of group-level reconstructions can be improved when compared to individualized reconstructions. In this model, we use the Restricted Maximum Likelihood (ReML) method to optimize a Bayesian random-effects model.

Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units

Diffuse optical tomographic image reconstruction uses advanced numerical models that are computationally costly to be implemented in the real time. The graphics processing units (GPUs) offer desktop massive parallelization that can accelerate these computations. An open-source GPU-accelerated linear algebra library package is used to compute the most intensive matrix-matrix calculations and matrix decompositions that are used in solving the system of linear equations. These open-source functions were integrated into the existing frequency-domain diffuse optical image reconstruction algorithms to evaluate the acceleration capability of the GPUs (NVIDIA Tesla C 1060) with increasing reconstruction problem sizes. These studies indicate that single precision computations are sufficient for diffuse optical tomographic image reconstruction. The acceleration per iteration can be up to 40, using GPUs compared to traditional CPUs in case of three-dimensional reconstruction, where the reconstruction problem is more underdetermined, making the GPUs more attractive in the clinical settings. The current limitation of these GPUs in the available onboard memory (4 GB) that restricts the reconstruction of a large set of optical parameters, more than 13,377.

Algorithms for bioluminescence tomography incorporating anatomical information and reconstruction of tissue optical properties

Reconstruction algorithms are presented for a two-step solution of the bioluminescence tomography (BLT) problem. In the first step, a priori anatomical information provided by x-ray computed tomography or by other methods is used to solve the continuous wave (cw) diffuse optical tomography (DOT) problem. A Taylor series expansion approximates the light fluence rate dependence on the optical properties of each region where first and second order direct derivatives of the light fluence rate with respect to scattering and absorption coefficients are obtained and used for the reconstruction. In the second step, the reconstructed optical properties at different wavelengths are used to calculate the Green's function of the system. Then an iterative minimization solution based on the L1 norm shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. This provides an efficient BLT reconstruction algorithm with the ability to determine relative source magnitudes and positions in the presence of noise.

Perturbation theory for the diffusion equation by use of the moments of the generalized temporal point-spread function. III. Frequency-domain and time-domain results

We study the performance of a previously proposed perturbation theory for the diffusion equation in frequency and time domains as they are known in the field of near infrared spectroscopy and diffuse optical tomography. We have derived approximate formulas for calculating higher order self- and mixed path length moments, up to the fourth order, which can be used in general diffusive media regardless of geometry and initial distribution of the optical properties, for studying the effect of absorbing defects. The method of Padé approximants is used to extend the validity of the theory to a wider range of absorption contrasts between defects and background. By using Monte Carlo simulations, we have tested these formulas in the semi-infinite and slab geometries for the cases of single and multiple absorbing defects having sizes of interest (d=4-10 mm, where d is the diameter of the defect). In frequency domain, the discrepancy between the two methods of calculation (Padé approximants and Monte Carlo simulations) was within 10% for absorption contrasts Deltamu(a)<or=0.2 mm(-1) for alternating current data, and usually to within 1 degrees for Deltamu(a)<or=0.1 mm(-1) for phase data. In time domain, the average discrepancy in the temporal range of interest (a few nanoseconds) was 2%-3% for Deltamu(a)<or=0.06 mm(-1). The proposed method is an effective fast forward problem solver: all the time-domain results presented in this work were obtained with a computational time of less than about 15 s with a Pentium IV 1.66 GHz personal computer.

Diffuse Optics for Tissue Monitoring and Tomography

This review describes the diffusion model for light transport in tissues and the medical applications of diffuse light. Diffuse optics is particularly useful for measurement of tissue hemodynamics, wherein quantitative assessment of oxy- and deoxy-hemoglobin concentrations and blood flow are desired. The theoretical basis for near-infrared or diffuse optical spectroscopy (NIRS or DOS, respectively) is developed, and the basic elements of diffuse optical tomography (DOT) are outlined. We also discuss diffuse correlation spectroscopy (DCS), a technique whereby temporal correlation functions of diffusing light are transported through tissue and are used to measure blood flow. Essential instrumentation is described, and representative brain and breast functional imaging and monitoring results illustrate the workings of these new tissue diagnostics.

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

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

Application of spectral derivative data in visible and near-infrared spectroscopy

The use of the spectral derivative method in visible and near-infrared optical spectroscopy is presented, whereby instead of using discrete measurements around several wavelengths, the difference between nearest neighbouring spectral measurements is utilized. The proposed technique is shown to be insensitive to the unknown tissue and fibre contact coupling coefficients providing substantially increased accuracy as compared to more conventional techniques. The self-calibrating nature of the spectral derivative techniques increases its robustness for both clinical and industrial applications, as is demonstrated based on simulated results as well as experimental data.

Multibeam fluorescence diffuse optical tomography using upconverting nanoparticles

Fluorescence diffuse optical tomography (FDOT) is a biomedical imaging modality that can be used for localization and quantification of fluorescent molecules inside turbid media. In this ill-posed problem, the reconstruction quality is directly determined by the amount and quality of the information obtained from the boundary measurements. Regularly, more information can be obtained by increasing the number of excitation positions in an FDOT system. However, the maximum number of excitation positions is limited by the finite size of the excitation beam. In the present work, we demonstrate a method in FDOT to exploit the unique nonlinear power dependence of upconverting nanoparticles to further increase the amount of information in a raster-scanning setup by including excitation with two beams simultaneously. We show that the additional information can be used to obtain more accurate reconstructions.

System development for high frequency ultrasound-guided fluorescence quantification of skin layers

A high frequency ultrasound-coupled fluorescence tomography system, primarily designed for imaging of protoporphyrin IX production in skin tumors in vivo, is demonstrated for the first time. The design couples fiber-based spectral sampling of the protoporphyrin IX fluorescence emission with high frequency ultrasound imaging, allowing thin-layer fluorescence intensities to be quantified. The system measurements are obtained by serial illumination of four linear source locations, with parallel detection at each of five interspersed detection locations, providing 20 overlapping measures of subsurface fluorescence from both superficial and deep locations in the ultrasound field. Tissue layers are defined from the segmented ultrasound images and diffusion theory used to estimate the fluorescence in these layers. The system calibration is presented with simulation and phantom validation of the system in multilayer regions. Pilot in-vivo data are also presented, showing recovery of subcutaneous tumor tissue values of protoporphyrin IX in a subcutaneous U251 tumor, which has less fluorescence than the skin.

Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography

PURPOSE

A computationally efficient algorithm (linear iterative type) based on singular value decomposition (SVD) of the Jacobian has been developed that can be used in rapid dynamic near-infrared (NIR) diffuse optical tomography.

METHODS

Numerical and experimental studies have been conducted to prove the computational efficacy of this SVD-based algorithm over conventional optical image reconstruction algorithms.

RESULTS

These studies indicate that the performance of linear iterative algorithms in terms of contrast recovery (quantitation of optical images) is better compared to nonlinear iterative (conventional) algorithms, provided the initial guess is close to the actual solution. The nonlinear algorithms can provide better quality images compared to the linear iterative type algorithms. Moreover, the analytical and numerical equivalence of the SVD-based algorithm to linear iterative algorithms was also established as a part of this work. It is also demonstrated that the SVD-based image reconstruction typically requires O(NN2) operations per iteration, as contrasted with linear and nonlinear iterative methods that, respectively, require O(NN3) and O(NN6) operations, with "NN" being the number of unknown parameters in the optical image reconstruction procedure.

CONCLUSIONS

This SVD-based computationally efficient algorithm can make the integration of image reconstruction procedure with the data acquisition feasible, in turn making the rapid dynamic NIR tomography viable in the clinic to continuously monitor hemodynamic changes in the tissue pathophysiology.