Diffuse optical tomography with physiological and spatiala prioriconstraints

Fluorescence molecular tomography for quantum yield and lifetime

Fluorescence molecular tomography (FMT) is a promising modality for noninvasive imaging of internal fluorescence agents in biological tissues, especially in small animal models, with applications in diagnosis, therapy, and drug design. In this paper, we present a fluorescent reconstruction algorithm that combines time-resolved fluorescence imaging data with photon-counting microcomputed tomography (PCMCT) images to estimate the quantum yield and lifetime of fluorescent markers in a mouse model. By incorporating PCMCT images, a permissible region of interest of fluorescence yield and lifetime can be roughly estimated as prior knowledge, reducing the number of unknown variables in the inverse problem and improving the image reconstruction stability. Our numerical experiments demonstrate the accuracy and stability of the proposed reconstruction method in the presence of data noise, achieving a reconstruction error of 0.02 ns for the fluorescence lifetime and an average relative error of 18% for quantum yield reconstruction.

Indocyanine Green-Camptothecin Co-Loaded Perfluorocarbon Double-Layer Nanocomposite: A Versatile Nanotheranostics for Photochemotherapy and FDOT Diagnosis of Breast Cancer

Breast cancer remains the most frequently diagnosed cancer and is the leading cause of neoplastic disease burden for females worldwide, suggesting that effective therapeutic and/or diagnostic strategies are still urgently needed. In this study, a type of indocyanine green (ICG) and camptothecin (CPT) co-loaded perfluorocarbon double-layer nanocomposite named ICPNC was developed for detection and photochemotherapy of breast cancer. The ICPNCs were designed to be surface modifiable for on-demand cell targeting and can serve as contrast agents for fluorescence diffuse optical tomography (FDOT). Upon near infrared (NIR) irradiation, the ICPNCs can generate a significantly increased production of singlet oxygen compared to free ICG, and offer a comparable cytotoxicity with reduced chemo-drug dosage. Based on the results of animal study, we further demonstrated that the ICPNCs ([ICG]/[CPT] = 40-/7.5-μM) in association with 1-min NIR irradiation (808 nm, 6 W/cm²) can provide an exceptional anticancer effect to the MDA-MB-231 tumor-bearing mice whereby the tumor size was significantly reduced by 80% with neither organ damage nor systemic toxicity after a 21-day treatment. Given a number of aforementioned merits, we anticipate that the developed ICPNC is a versatile theranostic nanoagent which is highly promising to be used in the clinic.

PV-MBLL algorithm for extraction of absolute tissue oxygenation information by diffuse optical spectroscopy

BACKGROUND AND OBJECTIVE

Tissue blood oxygenation contains critical information for biomedical studies and healthcare. The primary approach to extract the absolute value of tissue blood oxygenation (e.g., oxygen saturation) is spatial-resolved algorithm for near-infrared diffuse optical spectroscopy with continues-wave (CW) light, which require acquisition of the optical signals from multiple pairs of sources and detectors (S-D). This study reports the first attempt for absolute oxygenation measurement with single S-D pair of optical signals.

METHODS

A novel algorithm, namely, phantom-validation modified Beer-Lambert law (PV-MBLL), was created to fully utilize the optical signals from single S-D pair. This algorithm is combined with two-step phantom measurement to extract the absolute value of tissue oxygenation in CW system. The proposed PV-MBLL algorithm was compared with the conventional spatial-resolved algorithm on both step-varied liquid phantom and human experiment of cuff occlusion on arms. The one-way ANOVA analysis was performed to investigate the difference between the two algorithms.

RESULTS

By using the PV-MBLL algorithm, the reconstructed tissue absorption coefficient is highly accurate (not larger than 5.35% in error) over a wide range (0.02-0.20 cm^-1). By contrast, the spatial-resolved algorithm leads to much larger errors (up to 37.57% in error). Moreover, the responses of oxygen saturation to cuff occlusion differ significantly (p < 0.005) with the two algorithms.

CONCLUSIONS

The proposed PV-MBLL algorithm has promising potential for accurate acquisition of oxygenation information. Additionally, the single S-D pair greatly reduces the size of optical probe and instrument cost, thus it is highly appropriate for the tissues with small size and large curvature.

Hybrid time-domain and continuous-wave diffuse optical tomography instrument with concurrent, clinical magnetic resonance imaging for breast cancer imaging

Diffuse optical tomography has demonstrated significant potential for clinical utility in the diagnosis and prognosis of breast cancer, and its use in combination with other structural imaging modalities improves lesion localization and the quantification of functional tissue properties. Here, we introduce a hybrid diffuse optical imaging system that operates concurrently with magnetic resonance imaging (MRI) in the imaging suite, utilizing commercially available MR surface coils. The instrument acquires both continuous-wave and time-domain diffuse optical data in the parallel-plate geometry, permitting both absolute assignment of tissue optical properties and three-dimensional tomography; moreover, the instrument is designed to incorporate diffuse correlation spectroscopic measurements for probing tissue blood flow. The instrument is described in detail here. Image reconstructions of a tissue phantom are presented as an initial indicator of the system's ability to accurately reconstruct optical properties and the concrete benefits of the spatial constraints provided by concurrent MRI. Last, we briefly discuss how various data combinations that the instrument could facilitate, including tissue perfusion, can enable more comprehensive assessment of lesion physiology.

Impact of errors in experimental parameters on reconstructed breast images using diffuse optical tomography

Near-infrared diffuse optical tomography (NIR-DOT) is an emerging technology that offers hemoglobin based, functional imaging tumor biomarkers for breast cancer management. The most promising clinical translation opportunities are in the differential diagnosis of malignant vs. benign lesions, and in early response assessment and guidance for neoadjuvant chemotherapy. Accurate quantification of the tissue oxy- and deoxy-hemoglobin concentration across the field of view, as well as repeatability during longitudinal imaging in the context of therapy guidance, are essential for the successful translation of NIR-DOT to clinical practice. The ill-posed and ill-condition nature of the DOT inverse problem makes this technique particularly susceptible to model errors that may occur, for example, when the experimental conditions do not fully match the assumptions built into the image reconstruction process. To evaluate the susceptibility of DOT images to experimental errors that might be encountered in practice for a parallel-plate NIR-DOT system, we simulated 7 different types of errors, each with a range of magnitudes. We generated simulated data by using digital breast phantoms derived from five actual mammograms of healthy female volunteers, to which we added a 1-cm tumor. After applying each of the experimental error types and magnitudes to the simulated measurements, we reconstructed optical images with and without structural prior guidance and assessed the overall error in the total hemoglobin concentrations (HbT) and in the HbT contrast between the lesion and surrounding area vs. the best-case scenarios. It is found that slight in-plane probe misalignment and plate rotation did not result in large quantification errors. However, any out-of-plane probe tilting could result in significant deterioration in lesion contrast. Among the error types investigated in this work, optical images were the least likely to be impacted by breast shape inaccuracies but suffered the largest deterioration due to cross-talk between signal channels. However, errors in optical images could be effectively controlled when experimental parameters were properly estimated during data acquisition and accounted for in the image processing procedure. Finally, optical images recovered using structural priors were, in general, less susceptible to experimental errors; however, lesion contrasts were more sensitive to errors when tumor locations were used as a priori info. Findings in this simulation study can provide guidelines for system design and operation in optical breast imaging studies.

Diffuse optical tomography for breast cancer imaging guided by computed tomography: A feasibility study

Diffuse optical tomography (DOT) has attracted attentions in the last two decades due to its intrinsic sensitivity in imaging chromophores of tissues such as hemoglobin, water, and lipid. However, DOT has not been clinically accepted yet due to its low spatial resolution caused by strong optical scattering in tissues. Structural guidance provided by an anatomical imaging modality enhances the DOT imaging substantially. Here, we propose a computed tomography (CT) guided multispectral DOT imaging system for breast cancer imaging. To validate its feasibility, we have built a prototype DOT imaging system which consists of a laser at the wavelength of 650 nm and an electron multiplying charge coupled device (EMCCD) camera. We have validated the CT guided DOT reconstruction algorithms with numerical simulations and phantom experiments, in which different imaging setup parameters, such as projection number of measurements and width of measurement patch, have been investigated. Our results indicate that an air-cooling EMCCD camera is good enough for the transmission mode DOT imaging. We have also found that measurements at six angular projections are sufficient for DOT to reconstruct the optical targets with 2 and 4 times absorption contrast when the CT guidance is applied. Finally, we have described our future research plan on integration of a multispectral DOT imaging system into a breast CT scanner.

Combined Diffuse Optical Tomography (DOT) and MRI System for Cancer Imaging in Small Animals

Recently, there has been a great amount of interest in developing multi-modality imaging techniques for oncologic research and clinical studies with the aim of obtaining complementary information and, thus, improving the detection and characterization of tumors. In this present work, the details of a combined MR-diffuse optical imaging system for dual-modality imaging of small animals are given. As a part of this effort, a multi-spectral frequency domain diffuse optical tomography system is integrated with an MRI system. Here, a network analyzer provides the rf modulation signal for the laser diodes and measures the amplitude and the phase of the detected signals. Photomultiplier tubes are utilized to measure low-level signals. The integration of this optical imaging system with the 4T MRI system is realized by incorporating a fiber adaptive interface inside the MR magnet. Coregistration is achieved by a special probe design utilizing fiducial markers. A finite element algorithm is used to solve the diffusion equation and an inverse solver based on this forward solver is implemented to calculate the absorption and scattering maps from the acquired data. The MR a priori information is used to guide the optical reconstruction algorithm. Phantom studies show that the absorption coefficient of a 7 mm inclusion in an irregular object located in 64 mm phantom is recovered with 11% error when MR a priori information is used. ENU induced tumor model is used to test the performance of the system in vivo.

Dimensionality Reduction Based Optimization Algorithm for Sparse 3-D Image Reconstruction in Diffuse Optical Tomography

Diffuse optical tomography (DOT) is a relatively low cost and portable imaging modality for reconstruction of optical properties in a highly scattering medium, such as human tissue. The inverse problem in DOT is highly ill-posed, making reconstruction of high-quality image a critical challenge. Because of the nature of sparsity in DOT, sparsity regularization has been utilized to achieve high-quality DOT reconstruction. However, conventional approaches using sparse optimization are computationally expensive and have no selection criteria to optimize the regularization parameter. In this paper, a novel algorithm, Dimensionality Reduction based Optimization for DOT (DRO-DOT), is proposed. It reduces the dimensionality of the inverse DOT problem by reducing the number of unknowns in two steps and thereby makes the overall process fast. First, it constructs a low resolution voxel basis based on the sensing-matrix properties to find an image support. Second, it reconstructs the sparse image inside this support. To compensate for the reduced sensitivity with increasing depth, depth compensation is incorporated in DRO-DOT. An efficient method to optimally select the regularization parameter is proposed for obtaining a high-quality DOT image. DRO-DOT is also able to reconstruct high-resolution images even with a limited number of optodes in a spatially limited imaging set-up.

Combining energy and Laplacian regularization to accurately retrieve the depth of brain activity of diffuse optical tomographic data

Diffuse optical tomography (DOT) provides data about brain function using surface recordings. Despite recent advancements, an unbiased method for estimating the depth of absorption changes and for providing an accurate three-dimensional (3-D) reconstruction remains elusive. DOT involves solving an ill-posed inverse problem, requiring additional criteria for finding unique solutions. The most commonly used criterion is energy minimization (energy constraint). However, as measurements are taken from only one side of the medium (the scalp) and sensitivity is greater at shallow depths, the energy constraint leads to solutions that tend to be small and superficial. To correct for this bias, we combine the energy constraint with another criterion, minimization of spatial derivatives (Laplacian constraint, also used in low resolution electromagnetic tomography, LORETA). Used in isolation, the Laplacian constraint leads to solutions that tend to be large and deep. Using simulated, phantom, and actual brain activation data, we show that combining these two criteria results in accurate (error <2 mm) absorption depth estimates, while maintaining a two-point spatial resolution of <24 mm up to a depth of 30 mm. This indicates that accurate 3-D reconstruction of brain activity up to 30 mm from the scalp can be obtained with DOT.

Characterization of structural-prior guided optical tomography using realistic breast models derived from dual-energy x-ray mammography

Multi-spectral near-infrared diffuse optical tomography (DOT) is capable of providing functional tissue assessment that can complement structural mammographic images for more comprehensive breast cancer diagnosis. To take full advantage of the readily available sub-millimeter resolution structural information in a multi-modal imaging setting, an efficient x-ray/optical joint image reconstruction model has been proposed previously to utilize anatomical information from a mammogram as a structural prior. In this work, we develop a complex digital breast phantom (available at http://openjd.sf.net/digibreast) based on direct measurements of fibroglandular tissue volume fractions using dual-energy mammographic imaging of a human breast. We also extend our prior-guided reconstruction algorithm to facilitate the recovery of breast tumors, and perform a series of simulation-based studies to systematically evaluate the impact of lesion sizes and contrasts, tissue background, mesh resolution, inaccurate priors, and regularization parameters, on the recovery of breast tumors using multi-modal DOT/x-ray measurements. Our studies reveal that the optical property estimation error can be reduced by half by utilizing structural priors; the minimum detectable tumor size can also be reduced by half when prior knowledge regarding the tumor location is provided. Moreover, our algorithm is shown to be robust to false priors on tumor location.

Limited-projection-angle hybrid fluorescence molecular tomography of multiple molecules

An advantage of fluorescence methods over other imaging modalities is the ability to concurrently resolve multiple moieties using fluorochromes emitting at different spectral regions. Simultaneous imaging of spectrally separated agents is helpful in interrogating multiple functions or establishing internal controls for accurate measurements. Herein, we investigated multimoiety imaging in the context of a limited-projection-angle hybrid fluorescence molecular tomography (FMT), and x-ray computed tomography implementation and the further registration with positron emission tomography (PET) data. Multichannel FMT systems may image fluorescent probes of varying distribution patterns. Therefore, it is possible that different channels may require different use of priors and regularization parameters. We examined the performance of automatically estimating regularization factors implementing priors, using data-driven regularization specific for limited-projection-angle schemes. We were particularly interested in identifying the implementation variations between hybrid-FMT channels due to probe distribution variation. For this reason, initial validation of the data-driven algorithm on a phantom was followed by imaging different agent distributions in animals, assuming superficial and deep seated activity. We further demonstrate the benefits of combining hybrid FMT with PET to gain multiple readings on the molecular composition of disease.

Noninvasive evaluation of electrical stimulation impacts on muscle hemodynamics via integrating diffuse optical spectroscopies with muscle stimulator

Technologies currently available for the monitoring of electrical stimulation (ES) in promoting blood circulation and tissue oxygenation are limited. This study integrated a muscle stimulator with a diffuse correlation spectroscopy (DCS) flow-oximeter to noninvasively quantify muscle blood flow and oxygenation responses during ES. Ten healthy subjects were tested using the integrated system. The muscle stimulator delivered biphasic electrical current to right leg quadriceps muscle, and a custom-made DCS flow-oximeter was used for simultaneous measurements of muscle blood flow and oxygenation in both legs. To minimize motion artifact of muscle fibers during ES, a novel gating algorithm was developed for data acquisition at the time when the muscle was relaxed. ES at 2, 10, and 50 Hz were applied for 20 min on each subject in three days sequentially. Results demonstrate that the 20-min ES at all frequencies promoted muscle blood flow significantly. However, only the ES at 10 Hz resulted in significant and persistent increases in oxy-hemoglobin concentration during and post ES. This pilot study supports the application of the integrated system to quantify tissue hemodynamic improvements for the optimization of ES treatment in patients suffering from diseases caused by poor blood circulation and low tissue oxygenation (e.g., pressure ulcer).

Nonquadratic penalization improves near-infrared diffuse optical tomography

A new approach that can easily incorporate any generic penalty function into the diffuse optical tomographic image reconstruction is introduced to show the utility of nonquadratic penalty functions. The penalty functions that were used include quadratic (ℓ2), absolute (ℓ1), Cauchy, and Geman-McClure. The regularization parameter in each of these cases was obtained automatically by using the generalized cross-validation method. The reconstruction results were systematically compared with each other via utilization of quantitative metrics, such as relative error and Pearson correlation. The reconstruction results indicate that, while the quadratic penalty may be able to provide better separation between two closely spaced targets, its contrast recovery capability is limited, and the sparseness promoting penalties, such as ℓ1, Cauchy, and Geman-McClure have better utility in reconstructing high-contrast and complex-shaped targets, with the Geman-McClure penalty being the most optimal one.

Detectability of absorption and reduced scattering coefficients in frequency-domain measurements using a realistic head phantom

Detection limits of the changes in absorption and reduced scattering coefficients were investigated using a frequency-domain near-infrared system in a realistic head phantom. The results were quantified in terms of the maximum detectable depth for different activation volumes in the range of 0.8-20 microliters. The non-linear relation between the maximum detectable depth and the magnitude of changes in the absorption coefficient conform well with the Born approximation to the diffusion equation. The minimal detectable changes in the reduced scattering coefficient measured in terms of the phase signal were found to be approximately twice as large as that of the absorption coefficient using the AC signal for the same volume and at the same depth. The phase delay, which can be used to quantify the fast neuronal optical response in the human brain, showed a linear dependence on the reciprocal of the reduced scattering coefficient, as predicted by the Rytov approximation.

MAP estimation with structural priors for fluorescence molecular tomography

Fluorescence molecular tomography (FMT) is an attractive imaging tool for quantitatively and three-dimensionally resolving fluorophore distributions in small animals, but it suffers from low spatial resolution due to its inherent ill-posed nature. Structural priors obtained from a secondary modality system such as x-ray computed tomography or magnetic resonance imaging can help to improve FMT reconstruction results. However, challenge remains in how to fully take advantage of the structural priors while effectively avoid undesirable influence caused by an immoderate usage. In this paper, we propose a new method to resolve the FMT inverse problem based on maximum a posteriori (MAP) estimation with structural priors (MAP-SP) in a Bayesian framework. Instead of imposing the structural priors directly on the reconstruction results, the MAP-SP method utilizes them to constrain the unknown hyperparameters of the prior information model which is essential for the Bayesian framework. Then, a low dimensional inverse problem and an alternating optimization scheme are used to automatically calculate the unknown hyperparameters, which make the FMT reconstruction process self-adaptive. Simulation and phantom results show that the proposed MAP-SP method can effectively make use of the structural priors and leads to improvements in reconstruction quality as compared with traditional regularization methods.

Spatial and temporal hemodynamic study of human primary visual cortex using simultaneous functional MRI and diffuse optical tomography

Blood oxygenation level dependent (BOLD) functional MRI and near infrared optical tomography have been widely used to investigate hemodynamic responses to functional stimulation in the human brain. In this paper, we present a complete methodology for integrating the two imaging modalities to study the underlying physiological mechanism of the hemodynamic response in primary visual cortex. Using a specially designed MRI-compatible optical probe, optical imaging was conducted using a frequency-domain near infrared spectrometer. Three-dimensional optical image reconstruction was based on diffuse optical tomography (DOT) using a perturbative approach. The sensitivity function of the forward problem was obtained using Monte Carlo simulations. From preliminary results, the spatial activation pattern of changes in deoxyhemoglobin concentration is consistent with the BOLD signal map. The patterns of oxy- and deoxyhemoglobin changes are also very similar to one another. The temporal hemodynamic response shows an increased total hemoglobin concentration, which indicates an increased cerebral blood volume (CBV) during physiological activation.

Mono- and multimodal registration of optical breast images

Optical breast imaging offers the possibility of noninvasive, low cost, and high sensitivity imaging of breast cancers. Poor spatial resolution and a lack of anatomical landmarks in optical images of the breast make interpretation difficult and motivate registration and fusion of these data with subsequent optical images and other breast imaging modalities. Methods used for registration and fusion of optical breast images are reviewed. Imaging concerns relevant to the registration problem are first highlighted, followed by a focus on both monomodal and multimodal registration of optical breast imaging. Where relevant, methods pertaining to other imaging modalities or imaged anatomies are presented. The multimodal registration discussion concerns digital x-ray mammography, ultrasound, magnetic resonance imaging, and positron emission tomography.

FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography

The development of hybrid optical tomography methods to improve imaging performance has been suggested over a decade ago and has been experimentally demonstrated in animals and humans. Here we examined in vivo performance of a camera-based hybrid fluorescence molecular tomography (FMT) system for 360° imaging combined with X-ray computed tomography (XCT). Offering an accurately co-registered, information-rich hybrid data set, FMT-XCT has new imaging possibilities compared to stand-alone FMT and XCT. We applied FMT-XCT to a subcutaneous 4T1 tumor mouse model, an Aga2 osteogenesis imperfecta model and a Kras lung cancer mouse model, using XCT information during FMT inversion. We validated in vivo imaging results against post-mortem planar fluorescence images of cryoslices and histology data. Besides offering concurrent anatomical and functional information, FMT-XCT resulted in the most accurate FMT performance to date. These findings indicate that addition of FMT optics into the XCT gantry may be a potent upgrade for small-animal XCT systems.

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.

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.

Diffuse optical monitoring of repeated cerebral ischemia in mice

Occlusions of bilateral common carotid arteries (bi-CCA) in mice are popular models for the investigation of transient forebrain ischemia. Currently available technologies for assessing cerebral blood flow (CBF) and oxygenation in ischemic mice have limitations. This study tests a novel near-infrared diffuse correlation spectroscopy (DCS) flow-oximeter for monitoring both CBF and cerebral oxygenation in mice undergoing repeated transient forebrain ischemia. Concurrent flow measurements in a mouse brain were first conducted for validation purposes; DCS measurement was found highly correlated with laser Doppler measurement (R2 = 0.94) and less susceptible to motion artifacts. With unique designs in experimental protocols and fiber-optic probes, we have demonstrated high sensitivities of DCS flow-oximeter in detecting the regional heterogeneity of CBF responses in different hemispheres and global changes of both CBF and cerebral oxygenation across two hemispheres in mice undergoing repeated 2-minute bi-CCA occlusions over 5 days. More than 75% CBF reductions were found during bi-CCA occlusions in mice, which may be considered as a threshold to determine a successful bi-CCA occlusion. With the progress of repeated 2-minute bi-CCA occlusions over days, a longitudinal decline in the magnitudes of CBF reduction was observed, indicating the brain adaptation to cerebral ischemia through the repeated preconditioning.

High-resolution reconstruction of fluorescent inclusions in mouse thorax using anatomically guided sampling and parallel Monte Carlo computing

We present a method for high-resolution reconstruction of fluorescent images of the mouse thorax. It features an anatomically guided sampling method to retrospectively eliminate problematic data and a parallel Monte Carlo software package to compute the Jacobian matrix for the inverse problem. The proposed method was capable of resolving microliter-sized femtomole amount of quantum dot inclusions closely located in the middle of the mouse thorax. The reconstruction was verified against co-registered micro-CT data. Using the proposed method, the new system achieved significantly higher resolution and sensitivity compared to our previous system consisting of the same hardware. This method can be applied to any system utilizing similar imaging principles to improve imaging performance.

MR water quantitative priors improves the accuracy of optical breast imaging

Magnetic resonance (MR) guided optical breast imaging is a promising modality to improve the specificity of breast imaging, because it provides high-resolution quantitative maps of total hemoglobin, oxygen saturation, water content, and optical scattering. These properties have been shown to distinguish malignant from benign lesions. However, the optical detection hardware required for deep tissue imaging has poor spectral sensitivity which limits accurate water quantification; this reduces the accuracy of hemoglobin quantification. We present a methodology to improve optical quantification by utilizing the ability of Dixon MR imaging to quantitatively estimate water and fat; this technique effectively reduces optical crosstalk between water and oxyhemoglobin. The techniques described in this paper reduce hemoglobin quantification error by as much as 38%, as shown in a numerical phantom, and an experimental phantom. Error is reduced by as much 20% when imperfect MR water quantification is given. These techniques may also increase contrast between diseased and normal tissue, as shown in breast tissue in vivo. It is also shown that using these techniques may permit fewer wavelengths to be used with similar quantitative accuracy, enabling higher temporal resolution. In addition, it is shown that these techniques can improve the ability of MRI to quantify water in the presence of bias in the Dixon water/fat separation.

Evaluation of the simplified spherical harmonics approximation in bioluminescence tomography through heterogeneous mouse models

In vivo bioluminescence imaging (BLI) has played a more and more important role in biomedical research of small animals. Bioluminescence tomography (BLT) further translates the BLI optical information into three-dimensional bioluminescent source distribution, which could greatly facilitate applications in related studies. Although the diffusion approximation (DA) is one of the most widely-used forward models, higher-order approximations are still needed for in vivo small animal imaging. In this work, as a relatively accurate and higher-order approximation theory, the performance of the simplified spherical harmonics approximation (SPN) in BLT is evaluated detailedly in heterogeneous small animals. In the numerical validations, the SPN based results demonstrate better imaging quality compared with diffusion approximation heterogeneously under various source locations over wide optical domain. Although the evaluation for the effects of the optical property mismatch indicates the sensitivity of SPN is similar with DA model in the source localization, it may offer improved performance with much less artifacts. In what follows, heterogeneous experimental BLT reconstructions using in vivo mouse further evaluate the capability of the higher-order method for practical biomedical applications.

Comparing implementations of magnetic-resonance-guided fluorescence molecular tomography for diagnostic classification of brain tumors

Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT scanner. All data were spectrally unmixed to extract the dye fluorescence from the tissue autofluorescence. Methods to combine the two data sets were compared using student's t-tests and receiver operating characteristic analysis. Bulk fluorescence measurements that made up the optical imaging data set were also considered in the comparison. While most techniques were able to distinguish EGFR(+) tumors from EGFR(-) tumors and control animals, with area-under-the-curve values=1, only a handful were able to distinguish EGFR(-) tumors from controls. Bulk fluorescence spectroscopy techniques performed as well as most imaging techniques, suggesting that complex imaging algorithms may be unnecessary to diagnose EGFR status in these tissue volumes.

Development of an optical imaging platform for functional imaging of small animals using wide-field excitation

The design and characterization of a time-resolved functional imager using a wide-field excitation scheme for small animal imaging is described. The optimal operation parameters are established based on phantom studies. The performance of the platform for functional imaging and the simultaneous 3D reconstruction of absorption and scattering coefficients is investigated in vitro.

Image-guided optical spectroscopy in diagnosis of osteoarthritis: a clinical study

This goal of this study was to clinically evaluate the potential of a novel hybrid imaging techniques, called x-ray guided multispectral diffuse optical tomography, for identifying physiological parameters of joint tissues that can be used to distinguish between osteoarthritic and healthy joints in the hand. Between 2006 and 2009, the distal interphalangeal (DIP) finger joints from 40 subjects including 22 osteoarthritis patients and 18 healthy controls were examined clinically and scanned by the hybrid imaging platform that integrated a C-arm based x-ray tomosynthetic system with a mutlispectral diffuse optical imaging system. Based on the reconstructed results from the 40 subjects, it was observed that oxygen saturation and water content were two statistically most significant physiological discriminators for differentiation of the healthy joints from the osteoarthritic ones.

Imaging performance of a hybrid x-ray computed tomography-fluorescence molecular tomography system using priors

PURPOSE

The performance is studied of two newly introduced and previously suggested methods that incorporate priors into inversion schemes associated with data from a recently developed hybrid x-ray computed tomography and fluorescence molecular tomography system, the latter based on CCD camera photon detection. The unique data set studied attains accurately registered data of high spatially sampled photon fields propagating through tissue along 360 degrees projections.

METHODS

Approaches that incorporate structural prior information were included in the inverse problem by adding a penalty term to the minimization function utilized for image reconstructions. Results were compared as to their performance with simulated and experimental data from a lung inflammation animal model and against the inversions achieved when not using priors.

RESULTS

The importance of using priors over stand-alone inversions is also showcased with high spatial sampling simulated and experimental data. The approach of optimal performance in resolving fluorescent biodistribution in small animals is also discussed.

CONCLUSIONS

Inclusion of prior information from x-ray CT data in the reconstruction of the fluorescence biodistribution leads to improved agreement between the reconstruction and validation images for both simulated and experimental data.

Fast optical imaging of human brain function

Great advancements in brain imaging during the last few decades have opened a large number of new possibilities for neuroscientists. The most dominant methodologies (electrophysiological and magnetic resonance-based methods) emphasize temporal and spatial information, respectively. However, theorizing about brain function has recently emphasized the importance of rapid (within 100 ms or so) interactions between different elements of complex neuronal networks. Fast optical imaging, and in particular the event-related optical signal (EROS, a technology that has emerged over the last 15 years) may provide descriptions of localized (to sub-cm level) brain activity with a temporal resolution of less than 100 ms. The main limitations of EROS are its limited penetration, which allows us to image cortical structures not deeper than 3 cm from the surface of the head, and its low signal-to-noise ratio. Advantages include the fact that EROS is compatible with most other imaging methods, including electrophysiological, magnetic resonance, and trans-cranial magnetic stimulation techniques, with which can be recorded concurrently. In this paper we present a summary of the research that has been conducted so far on fast optical imaging, including evidence for the possibility of recording neuronal signals with this method, the properties of the signals, and various examples of applications to the study of human cognitive neuroscience. Extant issues, controversies, and possible future developments are also discussed.

Hybrid system for simultaneous fluorescence and x-ray computed tomography

A hybrid imaging system for simultaneous fluorescence tomography and X-ray computed tomography (XCT) of small animals has been developed and presented. The system capitalizes on the imaging power of a 360 ( degrees )-projection free-space fluorescence tomography system, implemented within a microcomputed tomography scanner. Image acquisition is based on techniques that automatically adjust a series of imaging parameters to offer a high dynamic range dataset. Image segmentation further allows the incorporation of structural priors in the optical reconstruction problem to improve the imaging performance. The functional system characteristics are showcased, and images from a brain imaging study are shown, which are reconstructed using XCT-derived priors into the optical forward problem.

Data specific spatially varying regularization for multimodal fluorescence molecular tomography

Fluorescence molecular tomography (FMT) allows in vivo localization and quantification of fluorescence biodistributions in whole animals. The ill-posed nature of the tomographic reconstruction problem, however, limits the attainable resolution. Improvements in resolution and overall imaging performance can be achieved by forming image priors from geometric information obtained by a secondary anatomical or functional high-resolution imaging modality such as X-ray computed tomography or magnetic resonance imaging. A particular challenge in using image priors is to avoid the use of assumptions that may bias the solution and reduced the accuracy of the inverse problem. This is particularly relevant in FMT inversions where there is not an evident link between secondary geometric information and the underlying fluorescence biodistribution. We present here a new, two step approach to incorporating structural priors into the FMT inverse problem. By using the anatomic information to define a low dimensional inverse problem, we obtain a solution which we then use to determine the parameters defining a spatially varying regularization matrix for the full resolution problem. The regularization term is thus customized for each data set and is guided by the data rather than depending only on user defined a priori assumptions. Results are presented for both simulated and experimental data sets, and show significant improvements in image quality as compared to traditional regularization techniques.

Dynamic contrast-enhanced diffuse optical tomography (DCE-DOT): experimental validation with a dynamic phantom

Dynamic contrast-enhanced diffuse optical tomography (DCE-DOT) can provide spatially resolved enhancement kinetics of an optical contrast agent. We undertook a systematic phantom study to evaluate the effects of the geometrical parameters such as the depth and size of the inclusion as well as the optical parameters of the background on the recovered enhancement kinetics of the most commonly used optical contrast agent, indocyanine green (ICG). For this purpose a computer-controlled dynamic phantom was constructed. An ICG-intralipid-water mixture was circulated through the inclusions while the DCE-DOT measurements were acquired with a temporal resolution of 16 s. The same dynamic study was repeated using inclusions of different sizes located at different depths. In addition to this, the effect of non-scattering regions was investigated by placing a second inclusion filled with water in the background. The phantom studies confirmed that although the peak enhancement varied substantially for each case, the recovered injection and dilution rates obtained from the percentage enhancement maps agreed within 15% independent of not only the depth and the size of the inclusion but also the presence of a non-scattering region in the background. Although no internal structural information was used in these phantom studies, it may be necessary to use it for small objects buried deep in tissue. However, the different contrast mechanisms of optical and other imaging modalities as well as imperfect co-registration between both modalities may lead to potential errors in the structural a priori. Therefore, the effect of erroneous selection of structural priors was investigated as the final step. Again, the injection and dilution rates obtained from the percentage enhancement maps were also immune to the systematic errors introduced by erroneous selection of the structural priors, e.g. choosing the diameter of the inclusion 20% smaller increased the peak enhancement 60% but changed the injection and dilution rates only less than 10%.

Time-gated perturbation Monte Carlo for whole body functional imaging in small animals

This paper explores a time-resolved functional imaging method based on Monte Carlo model for whole-body functional imaging of small animals. To improve the spatial resolution and quantitative accuracy of the functional map, a Bayesian hierarchical method with a high resolution spatial prior is applied to guide the optical reconstructions. Simulated data using the proposed approach are employed on an anatomically accurate mouse model where the optical properties range and volume limitations of the diffusion equation model exist. We investigate the performances of using time-gated data type and spatial priors to quantitatively image the functional parameters of multiple organs. Accurate reconstructions of the two main functional parameters of the blood volume and the relative oxygenation are demonstrated by using our method. Moreover, nonlinear optode settings guided by anatomical prior is proved to be critical to imaging small organs such as the heart.

Topographic localization of brain activation in diffuse optical imaging using spherical wavelets

Diffuse optical imaging is a non-invasive technique that uses near-infrared light to measure changes in brain activity through an array of sensors placed on the surface of the head. Compared to functional MRI, optical imaging has the advantage of being portable while offering the ability to record functional changes in both oxy- and deoxy-hemoglobin within the brain at a high temporal resolution. However, the reconstruction of accurate spatial images of brain activity from optical measurements represents an ill-posed and underdetermined problem that requires regularization. These reconstructions benefit from incorporating prior information about the underlying spatial structure and function of the brain. In this work, we describe a novel image reconstruction approach which uses surface-based wavelets derived from structural MRI to incorporate high-resolution anatomical and structural prior information about the brain. This surface-based approach is used to approximate brain activation patterns through the reconstruction and presentation of topographical (two-dimensional) maps of brain activation directly onto the folded surface of the cortex. The set of wavelet coefficients is directly estimated by a truncated singular-value decomposition based pseudo-inversion of the wavelet projection of the optical forward model. We use a reconstruction metric based on Shannon entropy which quantifies the sparse loading of the wavelet coefficients and is used to determine the optimal truncation and regularization of this inverse model. In this work, examples of the performance of this model are illustrated for several cases of numerical simulation and experimental data with comparison to functional magnetic resonance imaging.

3D shape based reconstruction of experimental data in Diffuse Optical Tomography

Diffuse optical tomography (DOT) aims at recovering three-dimensional images of absorption and scattering parameters inside diffusive body based on small number of transmission measurements at the boundary of the body. This image reconstruction problem is known to be an ill-posed inverse problem, which requires use of prior information for successful reconstruction. We present a shape based method for DOT, where we assume a priori that the unknown body consist of disjoint subdomains with different optical properties. We utilize spherical harmonics expansion to parameterize the reconstruction problem with respect to the subdomain boundaries, and introduce a finite element (FEM) based algorithm that uses a novel 3D mesh subdivision technique to describe the mapping from spherical harmonics coefficients to the 3D absorption and scattering distributions inside a unstructured volumetric FEM mesh. We evaluate the shape based method by reconstructing experimental DOT data, from a cylindrical phantom with one inclusion with high absorption and one with high scattering. The reconstruction was monitored, and we found a 87% reduction in the Hausdorff measure between targets and reconstructed inclusions, 96% success in recovering the location of the centers of the inclusions and 87% success in average in the recovery for the volumes.

Early-photon fluorescence tomography: spatial resolution improvements and noise stability considerations

In vivo tissue imaging using near-infrared light suffers from low spatial resolution and poor contrast recovery because of highly scattered photon transport. For diffuse optical tomography (DOT) and fluorescence molecular tomography (FMT), the resolution is limited to about 5-10% of the diameter of the tissue being imaged, which puts it in the range of performance seen in nuclear medicine. This paper introduces the mathematical formalism explaining why the resolution of FMT can be significantly improved when using instruments acquiring fast time-domain optical signals. This is achieved through singular-value analysis of the time-gated inverse problem based on weakly diffused photons. Simulations relevant to mouse imaging are presented showing that, in stark contrast to steady-state imaging, early time-gated intensities (within 200 ps or 400 ps) can in principle be used to resolve small fluorescent targets (radii from 1.5 to 2.5 mm) separated by less than 1.5 mm.

Quantitative fluorescence tomography with functional and structural a priori information

We demonstrate the necessity of functional and structural a priori information for quantitative fluorescence tomography (FT) with phantom studies. Here the functional a priori information is defined as the optical properties of the heterogeneous background that can be measured by a diffuse optical tomography (DOT) system. A CCD-based noncontact hybrid FT/DOT system that could take measurements at multiple views was built. Multimodality phantoms with multiple compartments were constructed and used in the experiments to mimic a heterogeneous optical background. A 3.6 mm diameter object deeply embedded in a heterogeneous optical background could be localized without any a priori information, but the recovered fluorophore concentration only reached one tenth of the true concentration. On the other hand, the true fluorophore concentration could be recovered when both functional and structural a priori information is utilized to guide and constrain the FT reconstruction algorithm.

Development of a noncontact 3-D fluorescence tomography system for small animal in vivo imaging

Fluorescence imaging is an important tool for tracking molecular-targeting probes in preclinical studies. It offers high sensitivity, but nonetheless low spatial resolution compared to other leading imaging methods such CT and MRI. We demonstrate our methodological development in small animal in vivo whole-body imaging using fluorescence tomography. We have implemented a noncontact fluid-free fluorescence diffuse optical tomography system that uses a raster-scanned continuous-wave diode laser as the light source and an intensified CCD camera as the photodetector. The specimen is positioned on a motorized rotation stage. Laser scanning, data acquisition, and stage rotation are controlled via LabVIEW applications. The forward problem in the heterogeneous medium is based on a normalized Born method, and the sensitivity function is determined using a Monte Carlo method. The inverse problem (image reconstruction) is performed using a regularized iterative algorithm, in which the cost function is defined as a weighted sum of the L-2 norms of the solution image, the residual error, and the image gradient. The relative weights are adjusted by two independent regularization parameters. Our initial tests of this imaging system were performed with an imaging phantom that consists of a translucent plastic cylinder filled with tissue-simulating liquid and two thin-wall glass tubes containing indocyanine green. The reconstruction is compared to the output of a finite element method-based software package NIRFAST and has produced promising results.

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

Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect the tissue composition. In this paper, the implementation and display of fully 3D MR image-guided NIRS is outlined and demonstrated using in vivo data from three healthy women and a volunteer undergoing neoadjuvant chemotherapy. Additionally, a display feature presented here scales the transparency of the optical images to the sensitivity of the measurements, providing a logical way to incorporate partial volume sets of optical images onto the MR volume. These concepts are demonstrated with 3D data sets using Volview software online.

Direct estimation of evoked hemoglobin changes by multimodality fusion imaging

In the last two decades, both diffuse optical tomography (DOT) and blood oxygen level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) methods have been developed as noninvasive tools for imaging evoked cerebral hemodynamic changes in studies of brain activity. Although these two technologies measure functional contrast from similar physiological sources, i.e., changes in hemoglobin levels, these two modalities are based on distinct physical and biophysical principles leading to both limitations and strengths to each method. In this work, we describe a unified linear model to combine the complimentary spatial, temporal, and spectroscopic resolutions of concurrently measured optical tomography and fMRI signals. Using numerical simulations, we demonstrate that concurrent optical and BOLD measurements can be used to create cross-calibrated estimates of absolute micromolar deoxyhemoglobin changes. We apply this new analysis tool to experimental data acquired simultaneously with both DOT and BOLD imaging during a motor task, demonstrate the ability to more robustly estimate hemoglobin changes in comparison to DOT alone, and show how this approach can provide cross-calibrated estimates of hemoglobin changes. Using this multimodal method, we estimate the calibration of the 3 tesla BOLD signal to be -0.55%+/-0.40% signal change per micromolar change of deoxyhemoglobin.

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

Near-infrared (NIR) region-based spectroscopy is examined for accuracy with spectral recovery using frequency domain data at a discrete number of wavelengths, as compared to that with broadband continuous wave data. Data with more wavelengths in the frequency domain always produce superior quantitative spectroscopy results with reduced noise and error in the chromophore concentrations. Performance of the algorithm in the situation of doing region-guided spectroscopy within the MRI is also considered, and the issue of false positive prior regions being identified is examined to see the effect of added wavelengths. The results indicate that broadband frequency domain data are required for maximal accuracy. A broadband frequency domain experimental system was used to validate the predictions, using a mode-locked Ti:sapphire laser for the source between 690- and 850-nm wavelengths. The 80-MHz pulsed signal is heterodyned with photomultiplier tube detection, to lower frequency for data acquisition. Tissue-phantom experiments with known hemoglobin absorption and tissue-like scatter values are used to validate the system, using measurements every 10 nm. More wavelengths clearly provide superior quantification of total hemoglobin values. The system and algorithms developed here should provide an optimal way to quantify regions with the goal of image-guided breast tissue spectroscopy within the MRI.

Magnetic resonance-coupled fluorescence tomography scanner for molecular imaging of tissue

A multichannel spectrally resolved optical tomography system to image molecular targets in small animals from within a clinical MRI is described. Long source/detector fibers operate in contact mode and couple light from the tissue surface in the magnet bore to 16 spectrometers, each containing two optical gratings optimized for the near infrared wavelength range. High sensitivity, cooled charge coupled devices connected to each spectrograph provide detection of the spectrally resolved signal, with exposure times that are automated for acquisition at each fiber. The design allows spectral fitting of the remission light, thereby separating the fluorescence signal from the nonspecific background, which improves the accuracy and sensitivity when imaging low fluorophore concentrations. Images of fluorescence yield are recovered using a nonlinear reconstruction approach based on the diffusion approximation of photon propagation in tissue. The tissue morphology derived from the MR images serves as an imaging template to guide the optical reconstruction algorithm. Sensitivity studies show that recovered values of indocyanine green fluorescence yield are linear to concentrations of 1 nM in a 70 mm diameter homogeneous phantom, and detection is feasible to near 10 pM. Phantom data also demonstrate imaging capabilities of imperfect fluorophore uptake in tissue volumes of clinically relevant sizes. A unique rodent MR coil provides optical fiber access for simultaneous optical and MR data acquisition of small animals. A pilot murine study using an orthotopic glioma tumor model demonstrates optical-MRI imaging of an epidermal growth factor receptor targeted fluorescent probe in vivo.

A simulation study of the variability of indocyanine green kinetics and using structural a priori information in dynamic contrast enhanced diffuse optical tomography (DCE-DOT)

We investigated (1) the variability of indocyanine green kinetics (ICG) between different cases in the existence of random noise, changing the size of the imaging region, the location and the size of the inclusion, (2) the use of structural a priori information to reduce the variability. We performed two-dimensional simulation studies for this purpose. In the simulations, we used a two-compartmental model to describe the ICG transport and obtained pharmacokinetic parameters. The transfer constant and the rate constant showed a wide variation, i.e. 60% and 95%, respectively, when random Gaussian noise with a standard deviation of 1% in amplitude and 0.4 degrees in phase was added to data. Moreover, recovered peak ICG concentration and time to reach the peak concentration was different within different cases. When structural a priori information was used in the reconstructions, the variations in the transfer and the rate constant were reduced to 29%, 15%, respectively. As a result, although the recovered peak concentration was still case dependent, the variability of the shape of the kinetic curve was reduced.

Quantitative second harmonic generation imaging and modeling of the optical clearing mechanism in striated muscle and tendon

We have investigated the mechanisms and capabilities of optical clearing in conjunction with second harmonic generation (SHG) imaging in tendon and striated muscle. Our approach combines three-dimensional (3-D) SHG imaging of the axial attenuation and directional response with Monte Carlo simulation (based on measured bulk optical properties) of the creation intensity and propagation through the tissues. Through these experiments and simulations, we show that reduction of the primary filter following glycerol treatment dominates the axial attenuation response in both muscle and tendon. However, these disparate tissue types are shown to clear through different mechanisms of the glycerol-tissue interaction. In the acellular tendon, glycerol application reduces scattering by both index matching as well as increasing the interfibril separation. This results in an overall enhancement of the 3-D SHG intensity, where good agreement is found between experiment and simulation. Through analysis of the axial response as a function of glycerol concentration in striated muscle, we conclude that the mechanism in this tissue arises from matching of the refractive index of the cytoplasm of the muscle cells with that of the surrounding higher-index collagenous perimysium. We further show that the proportional decrease in the scattering coefficient mu(s) with increasing glycerol fraction can be well-approximated by Mie theory.

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

Multimodality NIR spectroscopy systems offer the possibility of region-based vascular and molecular characterization of tissue in vivo. However, computationally efficient 3D image reconstruction algorithms specific to these image-guided systems currently do not exist. Image reconstruction is often based on finite-element methods (FEMs), which require volume discretization. Here, a boundary element method (BEM) is presented using only surface discretization to recover the optical properties in an image-guided setting. The reconstruction of optical properties using BEM was evaluated in a domain containing a 30 mm inclusion embedded in two layer media with different noise levels and initial estimates. For 5% noise in measurements, and background starting values for reconstruction, the optical properties were recovered to within a mean error of 6.8%. When compared with FEM for this case, BEM showed a 28% improvement in computational time. BEM was also applied to experimental data collected from a gelatin phantom with a 25 mm inclusion and could recover the true absorption to within 6% of expected values using less time for computation compared with FEM. When applied to a patient-specific breast mesh generated using MRI, with a 2 cm ductal carcinoma, BEM showed successful recovery of optical properties with less than 5% error in absorption and 1% error in scattering, using measurements with 1% noise. With simpler and faster meshing schemes required for surface grids as compared with volume grids, BEM offers a powerful and potentially more feasible alternative for high-resolution 3D image-guided NIR spectroscopy.

Fluorescence diffuse optical tomography with functional and anatomicala prioriinformation: feasibility study

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 investigate the performance of a frequency-domain FT system for small inclusions that are embedded in a heterogeneous background. The results demonstrate that functional and structural a priori information is crucial to be able to recover both parameters with high accuracy. The functional a priori information is defined by the absorption and scattering maps at both excitation and emission wavelengths. Similarly, the boundaries of the small inclusion and different regions in the background are utilized as the structural a priori information. Without a priori information, the fluorophore concentration of a 5 mm inclusion in a 40 mm medium is recovered with 50% error, while the lifetime cannot be recovered at all. On the other hand, when both functional and structural information are available, the true lifetime can be recovered and the fluorophore concentration can be estimated only with 5% error. This study shows that a hybrid system that can acquire diffuse optical absorption tomography (DOT), FT and anatomical images in the same setting is essential to be able to recover the fluorophore concentration and lifetime accurately in vivo.

Weight-matrix structured regularization provides optimal generalized least-squares estimate in diffuse optical tomography

Diffuse optical tomography (DOT) involves estimation of tissue optical properties using noninvasive boundary measurements. The image reconstruction procedure is a nonlinear, ill-posed, and ill-determined problem, so overcoming these difficulties requires regularization of the solution. While the methods developed for solving the DOT image reconstruction procedure have a long history, there is less direct evidence on the optimal regularization methods, or exploring a common theoretical framework for techniques which uses least-squares (LS) minimization. A generalized least-squares (GLS) method is discussed here, which takes into account the variances and covariances among the individual data points and optical properties in the image into a structured weight matrix. It is shown that most of the least-squares techniques applied in DOT can be considered as special cases of this more generalized LS approach. The performance of three minimization techniques using the same implementation scheme is compared using test problems with increasing noise level and increasing complexity within the imaging field. Techniques that use spatial-prior information as constraints can be also incorporated into the GLS formalism. It is also illustrated that inclusion of spatial priors reduces the image error by at least a factor of 2. The improvement of GLS minimization is even more apparent when the noise level in the data is high (as high as 10%), indicating that the benefits of this approach are important for reconstruction of data in a routine setting where the data variance can be known based upon the signal to noise properties of the instruments.

Quantitative spatial comparison of diffuse optical imaging with blood oxygen level-dependent and arterial spin labeling-based functional magnetic resonance imaging

Akin to functional magnetic resonance imaging (fMRI), diffuse optical imaging (DOI) is a noninvasive method for measuring localized changes in hemoglobin levels within the brain. When combined with fMRI methods, multimodality approaches could offer an integrated perspective on the biophysics, anatomy, and physiology underlying each of the imaging modalities. Vital to the correct interpretation of such studies, control experiments to test the consistency of both modalities must be performed. Here, we compare DOI with blood oxygen level-dependent (BOLD) and arterial spin labeling fMRI-based methods in order to explore the spatial agreement of the response amplitudes recorded by these two methods. Rather than creating optical images by regularized, tomographic reconstructions, we project the fMRI image into optical measurement space using the optical forward problem. We report statistically better spatial correlation between the fMRI-BOLD response and the optically measured deoxyhemoglobin (R=0.71, p=1x10(-7)) than between the BOLD and oxyhemoglobin or total hemoglobin measures (R=0.38, p=0.04|0.37, p=0.05, respectively). Similarly, we find that the correlation between the ASL measured blood flow and optically measured total and oxyhemoglobin is stronger (R=0.73, p=5x10(-6) and R=0.71, p=9x10(-6), respectively) than the flow to deoxyhemoglobin spatial correlation (R=0.26, p=0.10).

An integrated measurement system for simultaneous functional magnetic resonance imaging and diffuse optical tomography in human brain mapping

An integrated measurement system is described for performing simultaneous functional magnetic resonance imaging (fMRI) and diffuse optical tomography (DOT) for human brain mapping experiments. The components of this system consist of an MRI-compatible multi-overlapping-channel optical probe, methods for co-registration of optical and fMRI measurements, and DOT reconstruction algorithms with structural and physiological constraints derived from the MRI data. The optical probe is fully MRI-compatible in the sense that it produces negligible MR image distortion and does not require any modification to the MRI scanner or data acquisition protocol. The probe can be attached to any part of the head without posing any limitation on optical data acquisition. Co-registration of images from fMRI and optical measurements was achieved by localizing the positions of the optical fibers using MRI markers. Human studies show successful implementation of the entire system.