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Cerebral blood flow (CBF) measures are used in clinical settings to diagnose conditions (e.g., vasospasms, sickle cell disease, stroke, dementia, confirmation of brain death), as well as in research, emerging as potential early biomarkers of declining brain health. The aim of this chapter is to provide an overview of approaches used to measure CBF for determining resting cerebral tissue perfusion and functional CBF responsiveness. We will highlight the strengths and weaknesses of each and illustrate the methodological differences that need to be considered when assessing brain vascular health. The imaging methods measuring CBF will cover: Doppler ultrasound (spanning transcranial Doppler (TCD), duplex ultrasound, and transcranial color Doppler (TCCD)), magnetic resonance imaging (MRI) (including arterial spin labeling (ASL), blood oxygenation level dependent (BOLD) signal measures and phase-contrast angiography), and finally near-infrared spectroscopy (NIRS).

Objective: A new method for fitting diffusion-weighted magnetic resonance imaging (DW-MRI) data composed of an unknown number of multi-exponential components is presented and evaluated. Methods: The auto-regressive discrete acquisition points transformation (ADAPT) method is an adaption of the auto-regressive moving average system, which allows for the modeling of multi-exponential data and enables the estimation of the number of exponential components without prior assumptions. ADAPT was evaluated on simulated DW-MRI data. The optimum ADAPT fit was then applied to human brain DWI data and the correlation between the ADAPT coefficients and the parameters of the commonly used bi-exponential intravoxel incoherent motion (IVIM) method were investigated. Results: The ADAPT method can correctly identify the number of components and model the exponential data. The ADAPT coefficients were found to have strong correlations with the IVIM parameters. ADAPT(1,1)-β0 correlated with IVIM-D: ρ = 0.708, P

Performance assessment and standardization are indispensable for instruments of clinical relevance in general and clinical instrumentation based on photon migration/diffuse optics in particular. In this direction, a multi-laboratory exercise was initiated with the aim of assessing and comparing their performances. 29 diffuse optical instruments belonging to 11 partner institutions of a European level Marie Curie Consortium BitMap1 were considered for this exercise. The enrolled instruments covered different approaches (continuous wave, CW; frequency domain, FD; time domain, TD and spatial frequency domain imaging, SFDI) and applications (e.g. mammography, oximetry, functional imaging, tissue spectroscopy). 10 different tests from 3 well-accepted protocols, namely, the MEDPHOT2 , the BIP3 , and the nEUROPt4 protocols were chosen for the exercise and the necessary phantoms kits were circulated across labs and institutions enrolled in the study. A brief outline of the methodology of the exercise is presented here. Mainly, the design of some of the synthetic descriptors, (single numeric values used to summarize the result of a test and facilitate comparison between instruments) for some of the tests will be discussed.. Future actions of the exercise aim at deploying these measurements onto an open data repository and investigating common analysis tools for the whole dataset.

Developing near-infrared spectroscopy (NIRS) parameter recovery techniques to more specifically resolve brain physiology from that of the overlying tissue is an important part of improving the clinical utility of the technology. The Valsalva maneuver (VM) involves forced expiration against a closed glottis causing widespread venous congestion within the context of a fall in cardiac output. Due to the specific anatomical confines and metabolic demands of the brain we believe a properly executed VM has the ability to separate haemodynamic activity of brain tissue from that of the overlying scalp as observed by NIRS, and confirmed by functional magnetic resonance imaging (fMRI). Healthy individuals performed a series of standing maximum effort VMs under separate observation by frequency domain near-infrared spectroscopy (FD-NIRS) and fMRI. Nine individuals completed the clinical protocol (6 males, age 21-40). During the VMs, brain and extracranial tissue targeted signal were significantly different (opposite direction of change) in both fMRI and NIRS (p=0.00025 and 0.00115 respectively), with robust cross correlation of parameters between modalities. Four of these individuals performed further VMs after infiltrating 2% xylocaine/1:100,000 epinephrine (vasoconstrictor) into scalp tissue beneath the probes. No significant difference in the cerebrally derived parameters was observed. The maximum effort VM has the ability to separate NIRS observable physiology of the brain from the overlying extracranial tissue. Observations made by this FD cerebral NIRS device are comparable with fMRI in this context.

Rheumatoid arthritis (RA) is an inflammatory joint disease often affecting the hands, which if untreated causes disability. Diffuse optical tomography (DOT) provides information about the underlying functional properties of biological tissue. To detect pathophysiological changes in inflamed RA joints, a good understanding of the baseline values for healthy subjects is first required. Finger joints from healthy subjects were imaged using a non-contact, multispectral, continuous wave DOT system, recovering physiological parameters of oxygen saturation, total haemoglobin, water concentration and scatter amplitude. Reconstructed values across the cohort demonstrated good consistency between finger joints from the same participant, with greater variation seen between subjects.

The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live and necrotic/apoptotic cells have been defined using in vitro methods. The delineation of different cellular states using spectroscopic methods is difficult due to the complex nature of these biological processes. Sophisticated, objective classification methods will therefore be important for such differentiation. In this study, spectral data from healthy/traumatised cell samples using hyperspectral imaging between 2500–3500 nm were collected using a portable prototype device. Machine learning algorithms, in the form of clustering, have been performed on a variety of pre-processing data types including ‘raw’ unprocessed, smoothed resampling, background subtracted and spectral derivative. The resulting clusters were utilised as a diagnostic tool for the assessment of cellular health and quantified using both sensitivity and specificity to compare the different analysis methods. The raw data exhibited differences for one of the three different trauma types applied, although unable to accurately cluster all the traumatised samples due to signal contamination from the chemical insult. The background subtracted and smoothed data sets reduced the accuracy further, due to the apparent removal of key spectral features which exhibit cellular health. However, the spectral derivative data-types significantly improved the accuracy of clustering compared to other data types, with both sensitivity and specificity for the background subtracted data set being >94% highlighting its utility to account for unknown signal contamination while maintaining important cellular spectral features.

Objective This study aimed to investigate the reliability of intravoxel incoherent motion (IVIM) model derived parameters D and f and their dependence on b value distributions with a rapid three b value acquisition protocol. Materials and methods Diffusion models for brain, kidney, and liver were assessed for bias, error, and reproducibility for the estimated IVIM parameters using b values 0 and 1000, and a b value between 200 and 900, at signal-to-noise ratios (SNR) 40, 55, and 80. Relative errors were used to estimate optimal b value distributions for each tissue scenario. Sixteen volunteers underwent brain DW-MRI, for which bias and coefficient of variation were determined in the grey matter. Results Bias had a large influence in the estimation of D and f for the low-perfused brain model, particularly at lower b values, with the same trends being confirmed by in vivo imaging. Significant differences were demonstrated in vivo for estimation of D (P = 0.029) and f (P

Within 72 hours of stroke onset, High-Density Diffuse Optical Tomography can detect disruptions in functional connectivity patterns that significantly differ from healthy subjects (p

Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n = 5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxel-to-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subject-specific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4 +/− 1 mm, significantly less than the average distance between cortical gyri. This specificity demonstrates that HD-DOT has sufficient image quality to be useful as a surrogate for fMRI.

Purpose: Bioluminescenceimaging is a research tool for studying gene expression levels in small animal models of human disease. Bioluminescence light, however, is strongly scattered in biological tissue and no direct image of the light-emitting reporter probe’s location can be obtained. Therefore, the authors have developed a linear image reconstruction method for bioluminescencetomography (BLT) that recovers the three-dimensional spatial bioluminescent source distribution in small animals. Methods: The proposed reconstruction method uses third-order simplified spherical harmonics ( SP 3 ) solutions to the equation of radiative transfer for modeling the bioluminescence light propagation in optically nonuniform tissue. The SP 3 equations and boundary conditions are solved with a finite-difference (FD) technique on a regular grid. The curved geometry of the animal surface was taken into account with a blocking-off region method for regular grids. Coregistered computed tomography(CT) and magnetic resonance (MR)images provide information regarding the geometry of the skin surface and internal organs. The inverse source problem is defined as an algebraic system of linear equations for the unknown source distribution and is iteratively solved given multiview and multispectral boundary measurements. The average tissue absorption parameters, which are used for the image reconstruction process, were calculated with an evolution strategy (ES) from in vivo measurements using an implanted pointlike source of known location and spectrum. Moreover, anatomical information regarding the location of the internal organs and other tissue structures within the animal’s body are provided by coregistered MRimages. Results: First, the authors recovered the wavelength-dependent absorption coefficients (average error of 14%) with the ES under ideal conditions by using a numerical mouse model. Next, they reconstructed the average absorption coefficient of a small animal by using an artificial implanted light source and the validated ES. Last, they conducted twoin vivo animal experiments and recovered the spatial location of the implanted light source and the spatial distribution of a bioluminescent reporter system located in the kidneys. The source reconstruction results were coregistered to CT and MRimages. They further found that accurate bioluminescenceimage reconstructions could be obtained when segmenting a voidlike cyst with low-scattering and absorption parameters, whereas inaccurate image reconstructions were obtained when assuming a uniform optical parameter distribution instead. The image reconstructions were completed within 23 min on a 3 GHz Intel processor. Conclusions: The authors demonstrated onin vivo examples that the combination of anatomical coregistration, accurate optical tissueproperties, multispectral acquisition, and a blocking-off FD- SP 3 solution of the radiative transfer model significantly improves the accuracy of the BLT reconstructions.

The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution.

Three-dimensional (3D) diffuse optical tomography is known to be a nonlinear, ill-posed and sometimes under-determined problem, where regularization is added to the minimization to allow convergence to a unique solution. In this work, a generalized least-squares (GLS) minimization method was implemented, which employs weight matrices for both data-model misfit and optical properties to include their variances and covariances, using a computationally efficient scheme. This allows inversion of a matrix that is of a dimension dictated by the number of measurements, instead of by the number of imaging parameters. This increases the computation speed up to four times per iteration in most of the under-determined 3D imaging problems. An analytic derivation, using the Sherman-Morrison-Woodbury identity, is shown for this efficient alternative form and it is proven to be equivalent, not only analytically, but also numerically. Equivalent alternative forms for other minimization methods, like Levenberg-Marquardt (LM) and Tikhonov, are also derived. Three-dimensional reconstruction results indicate that the poor recovery of quantitatively accurate values in 3D optical images can also be a characteristic of the reconstruction algorithm, along with the target size. Interestingly, usage of GLS reconstruction methods reduces error in the periphery of the image, as expected, and improves by 20% the ability to quantify local interior regions in terms of the recovered optical contrast, as compared to LM methods. Characterization of detector photo-multiplier tubes noise has enabled the use of the GLS method for reconstructing experimental data and showed a promise for better quantification of target in 3D optical imaging. Use of these new alternative forms becomes effective when the ratio of the number of imaging property parameters exceeds the number of measurements by a factor greater than 2.

Functional brain imaging has become an important neuroimaging technique for the study of brain organization and development. Compared to other imaging techniques, diffuse optical tomography (DOT) is a portable and low-cost technique that can be applied to infants and hospitalized patients using an atlas-based light model. For DOT imaging, the accuracy of the forward model has a direct effect on the resulting recovered brain function within a field of view and so the accuracy of the spatially normalized atlas-based forward models must be evaluated. Herein, the accuracy of atlas-based DOT is evaluated on models that are spatially normalized via a number of different rigid registration methods on 24 subjects. A multileveled approach is developed to evaluate the correlation of the geometrical and sensitivity accuracies across the full field of view as well as within specific functional subregions. Results demonstrate that different registration methods are optimal for recovery of different sets of functional brain regions. However, the “nearest point to point” registration method, based on the EEG 19 landmark system, is shown to be the most appropriate registration method for image quality throughout the field of view of the high-density cap that covers the whole of the optically accessible cortex.

Diffuse optical tomography (DOT) for brain imaging has the potential to be an alternative human brain mapping technique when MRI imaging is not applicable. It recovers tissue chromophore concentrations of brain tissue through measures of light transmission to monitor for example the resting-state brain dynamics. This imaging technique relies on simulation of the light propagation which can be generated based on a subject-specific model. There has been some study on using rigid atlas models as alternatives for model based DOT when subject-specific anatomical data is not available; but there is still a lack of detailed analysis between geometrical accuracy and internal light propagation in tissue for atlas-based DOT. This work is focused on High-Density DOT (HD-DOT) of the whole cortex based on atlas models from 11 different rigid registration algorithms across 24 subjects, and the results are evaluated in 19 areas of the human head. The correlation between geometrical surface error and internal light propagation errors is strong in most area but varies in different regions from R 2 = 0.74 in the region around top of the head to R 2 = 0.98 in the region around the temples. In the 11 registration methods, basic-4-landmark registration with 4.2mm average surface error and 50% average internal light propagation errors is shown to be the least accurate registration method whereas full-head landmark with non-iterative point to point with 1.7mm average surface error and 32% average internal light propagation error is shown to be the most accurate registration method for atlas-based DOT.

Magnetic resonance (MR)-guided near-infrared spectral tomography was developed and used to image adipose and fibroglandular breast tissue of 11 normal female subjects, recruited under an institutional review board-approved protocol. Images of hemoglobin, oxygen saturation, water fraction, and subcellular scattering were reconstructed and show that fibroglandular fractions of both blood and water are higher than in adipose tissue. Variation in adipose and fibroglandular tissue composition between individuals was not significantly different across the scattered and dense breast categories. Combined MR and near-infrared tomography provides fundamental molecular information about these tissue types with resolution governed by MR T1 images.

Multi-wavelength Near-Infrared (NIR) Tomography was utilized in this study to non-invasively quantify physiological parameters of breast tumors using direct spectral reconstruction. Frequency domain NIR measurements were incorporated with a new spectrally constrained direct chromophore and scattering image reconstruction algorithm, which was validated in simulations and experimental phantoms. Images of total hemoglobin, oxygen saturation, water, and scatter parameters were obtained with higher accuracy than previously reported. Using this spectral approach, in vivo NIR images are presented and interpreted through a series of case studies (n=6 subjects) having differing abnormalities. The corresponding mammograms and ultrasound images are also evaluated. Three of six cases were malignant (infiltrating ductal carcinomas) and showed higher hemoglobin (34–86% increase), a reduction in oxygen saturation, an increase in water content as well as scatter changes relative to surrounding normal tissue. Three of six cases were benign, two of which were diagnosed with fibrocystic disease and showed a dominant contrast in water, consistent with fluid filled cysts. Scatter amplitude was the main source of contrast in the volunteer with the benign condition fibrosis, which typically contains denser collagen tissue. The changes monitored correspond to physiological changes associated with angiogenesis, hypoxia and cell proliferation anticipated in cancers. These changes represent potential diagnostic indicators, which can be assessed to characterize breast tumors.

The design and implementation of a multispectral, frequency-domain near infrared tomography system is outlined, which operates in a MRI magnet for utilization of MR-guided image reconstruction of tissue optical properties. Using long silica optical fiber bundles, measurements of light transmission through up to 12 cm of female breast tissue can be acquired simultaneously with MRI scans. The NIR system utilizes six optical wavelengths from 660 to 850 nm using intensity modulated diode lasers nominally working at 100 MHz. Photomultiplier tube detector gain levels are electronically controlled on a time scale of 200 ms, thereby allowing rapid switching of the source to locations around the tissue. There are no moving parts in the detection channels and for each source position, 15 PMTs operating in parallel allow sensitivity down to 0.5 pW/cm2 at the tissue surface. Images of breast tissue optical absorption and reduced scattering coefficients are obtained using a Newton-type reconstruction algorithm to solv...

Near-infrared (NIR) tomography is a technique used to measure light propagation through tissue and generate images of internal optical property distributions from boundary measurements. Most popular applications have concentrated on female breast imaging, neonatal and adult head imaging, as well as muscle and small animal studies. In most instances a highly scattering medium with a homogeneous refractive index is assumed throughout the imaging domain. Using these assumptions, it is possible to simplify the model to the diffusion approximation. However, biological tissue contains regions of varying optical absorption and scatter, as well as varying refractive index. In this work, we introduce an internal boundary constraint in the finite element method approach to modelling light propagation through tissue that accounts for regions of different refractive indices. We have compared the results to data from a Monte Carlo simulation and show that for a simple two-layered slab model of varying refractive index, the phase of the measured reflectance data is significantly altered by the variation in internal refractive index, whereas the amplitude data are affected only slightly.

A combined magnetic resonance and near-infrared (MRI-NIR) imaging modality can potentially yield high resolution maps of optical properties from noninvasive simultaneous measurement. The main disadvantage of near-infrared (NIR) tomography lies in the low spatial resolution resulting from the highly scattering nature of tissue for these wavelengths. MRI has achieved high resolution, but suffers from low specificity. In this study, NIR image reconstruction algorithms that incorporate a priori structural information provided by MRI are investigated in an attempt to optimize recovery of a simulated optical property distribution. The effect of high levels of tissue heterogeneity are evaluated to determine the limitations of incorporating prior information into a realistic set of patient breast images. We assume absorption coefficient (/spl mu//sub a/) variations near /spl plusmn/40%, and transport scattering coefficient (/spl mu//sub s//sup //) variations near /spl plusmn/20%, in a coronal breast MRI geometry. Changes in tissue pathology due to tumor growth can be observed with NIR tompgraphy, and so the goal here is to determine how best to quantify these tumor-based contrast regions within the presence of high tissue heterogeneity. By applying knowledge of tissue's layered structure in reconstruction through various constraints in the iterative algorithm, quantitative recovery of the tumor optical properties improves from 69% to 74%, and localization improves as well. However, only when the true heterogeneity of the tissue distribution was included was accurate quantification of the tumor region possible. Using a good initial guess of /spl mu//sub a/ and /spl mu//sub s//sup //, derived from the regional structure of the model, quantification of the region reaches 99% of the true value, and spatial resolution retains a similar value to the original MRI image.

Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

The image reconstruction problem encountered in diffuse optical tomographic imaging is ill-posed in nature, necessitating the usage of regularization to result in stable solutions. This regularization also results in loss of resolution in the reconstructed images. A frame work, that is attributed by model-resolution, to improve the reconstructed image characteristics using the basis pursuit deconvolution method is proposed here. The proposed method performs this deconvolution as an additional step in the image reconstruction scheme. It is shown, both in numerical and experimental gelatin phantom cases, that the proposed method yields better recovery of the target shapes compared to traditional method, without the loss of quantitativeness of the results.

Realistic head models are used to assess the information content in regions of the brain relevant to monitoring traumatic brain injury patients with commercial NIRS probes, highlighting system variability and the need for better standardization.

We present integrative advances in high-density diffuse optical tomography imaging arrays, large field-of-view instrumentation, and anatomical head modeling. The system was tested by imaging four language tasks and multiple resting-state networks.

We present an overview of time-resolved optical tomography together with the hardware and software methods that we have developed for a clinical instrument that implements this modality. The hardware is based on a multichannel photon-counting technique that records the histograms of photons time-of-flight through highly scattering and attenuating media. The software is based on a finite element model that is iteratively updated in order to minimize the difference between measured and modeled data. We have presented a first experimental reconstruction of a three-dimensional (3D) distribution of variable absorption and scattering coefficient, together with an ideal simulation of the same case. (C) 2000 John Wiley & Sons, Inc.

Practical imaging constraints restrict the number of wavelengths that can be measured in a single Biolumines- cence Tomography imaging session, but it is unclear which set of measurement wavelengths is optimal, in the sense of providing the most information about the bioluminescent source. Mutual Information was used to integrate knowledge of the type of bioluminescent source likely to be present, the optical properties of tissue and physics of light propagation, and the noise characteristics of the imaging system, in order to quantify the information contained in measurements at different sets of wavelengths. The approach was applied to a two-dimensional simulation of Bioluminescence Tomography imaging of a mouse, and the results indicate that different wavelengths and sets of wavelengths contain different amounts of information. When imaging at a single wavelength, 580nm was found to be optimal, and when imaging at two wavelengths, 570nm and 580nm were found to be optimal. Examination of the dispersion of the posterior distributions for single wavelengths suggests that information regarding the location of the centre of the bioluminescence distribution is relatively independent of wavelength, whilst information regarding the width of the bioluminescence distribution is relatively wavelength specific.

Knowledge of the surface geometry of an imaging subject is important in many applications. This information can be obtained via a number of different techniques, including time of flight imaging, photogrammetry, and fringe projection profilometry. Existing systems may have restrictions on instrument geometry, require expensive optics, or require moving parts in order to image the full surface of the subject. An inexpensive generalised fringe projection profilometry system is proposed that can account for arbitrarily placed components and use mirrors to expand the field of view. It simultaneously acquires multiple views of an imaging subject, producing a cloud of points that lie on its surface, which can then be processed to form a three dimensional model. A prototype of this system was integrated into an existing Diffuse Optical Tomography and Bioluminescence Tomography small animal imaging system and used to image objects including a mouse-shaped plastic phantom, a mouse cadaver, and a coin. A surface mesh generated from surface capture data of the mouse-shaped plastic phantom was compared with ideal surface points provided by the phantom manufacturer, and 50% of points were found to lie within 0.1mm of the surface mesh, 82% of points were found to lie within 0.2mm of the surface mesh, and 96% of points were found to lie within 0.4mm of the surface mesh.

The guest editors introduce a feature issue containing papers based on research presented at the BIOMED 2016 Congress, held in Fort Lauderdale, FL, 24–28 April, 2016.

Background A reliable portable non-invasive monitor for use in brain injury is needed, so near infrared spectroscopy (NIRS) has potential. Historical inconsistencies in NIRS have prevented its use, often attributed to the contamination of signal from extracranial tissue. We aimed to validate the brain signal from frequency domain NIRS (advanced NIRS technique), comparing its abilities with functional MRI (fMRI) to isolate physiological activity in the brain from those of extracranial tissue. Methods In a prospective healthy volunteer study, nine individuals (six male, three female, age range 21–40 years) performed supine Valsalva manoeuvres (adequacy monitored via finger photoplethysmography and capnography). The Valsalva manoeuvre provided a suitable model for cerebral ischaemia and rises in intracranial pressure. During the manoeuvre, a portable frequency domain NIRS device was targeted separately at the brain and at extracranial tissue, and fMRI (blood oxygen load dependent sequence) was taken from regions corresponding to both fields of NIRS acquisition. Area under the curve analysis of the change in variables during the Valsalva manoeuvre was analysed by the Wilcoxon rank sum method with multiple pairwise comparisons between the brain and extracranial tissue signals for both NIRS and fMRI. Findings We observed similar responses in both brain and extracranial tissue: in all volunteers, oxygenation in brain tissue during the Valsalva manoeuvre decreased (mean −7·2% NIRS [SD 4·7], −3·4% fMRI [SD 1·46]) and oxygenation from the extracranial acquired data increased (mean +6·1% NIRS [SD 2·72], +4·4% fMRI [SD 3·45]), matching physiological predictions. These brain and extracranial signals were significantly different in both fMRI and NIRS (p=0·00025 and 0·00115, respectively). Interpretation Our findings confirm that frequency domain NIRS can detect specific changes within the brain tissue during the Valsalva manoeuvre independent of physiological features of extracranial tissue and reflects changes observed by fMRI. Therefore, the frank changes in the brain observed by frequency domain NIRS are brain specific, demonstrating the potential for this method to be used within the context of brain injury. Funding National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre.

An automated, multi-view, spectral bioluminescence tomography system that utilises structured-light-based surface capture techniques along with a model-based approach to image reconstruction is presented.

Image-quality of high-density diffuse optical tomography is evaluated against fMRI using functional maps of visual cortex as a benchmark. Co-registered subject-specific light models have an average localization error of 4.4 +/- 1 mm.

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.

This work examines the robustness of spectral prior to continuous-wave based, with respect to frequency domain based, image reconstruction for unique recovering of chromophores and scattering property distributions. An analytical model for parametric uncertainty in recovering optical property is derived, which afterwards is implemented for optimized selection of wavelengths and quality estimation of the image. Simulation results agree with the theoretical predictions in the following aspects: 1) the proposed analytical model is capable of selecting the optimal set of wavelengths for CW-based spectral reconstruction; 2) with sufficient number of wavelengths, DC-only reconstruction can resolve the concentrations of several important chromophores and scattering parameters, with the accuracy and background artifact level equivalent to those by DC-excluded or DC-included frequency-domain reconstructions; and 3) including DC in frequency-domain reconstruction generally improves reconstruction outcome as compared to when neglecting DC.

In MRI-guided diffuse optical tomography of the human brain function, three-dimensional anatomical head model consisting of up to five segmented tissue types can be specified. With disregard to misclassification between different tissues, uncertainty in the optical properties of each tissue type becomes the dominant cause of systematic error in image reconstruction. In this study we present a quantitative evaluation of image resolution dependence due to such uncertainty. Our results show that given a head model which provides a realistic description of its tissue optical property distribution, high-density diffuse optical tomography with cortically constrained image reconstruction are capable of detecting focal activation up to 21.81 mm below the human scalp at an imaging quality better than or equal to 1.0 cm in localization error and 1.0 cm 3 in FVHM with a tolerance of uncertainty in tissue optical properties between +15% and -20%.

The use of higher order approximations to the Radiative transport equation, through simplified spherical harmonics expansion (SP(N)) in optical tomography are presented. It is shown that, although the anisotropy factor can be modeled in the forward problem, its sensitivity to the measured boundary data is limited to superficial regions and more importantly, due to uniqueness of the inverse problem it cannot be determined using frequency domain data. Image reconstruction through the use of higher ordered models is presented. It is demonstrated that at higher orders (for example SP7) the image reconstruction becomes highly under-determined due to the large increase in the number of unknowns which cannot be adequately recovered. However, reconstruction of diffuse parameters, namely optical absorption and reduced scatter have shown to be more accurate where only the sensitivity matrix used in the inverse problem is based on SP(N) method and image reconstruction is limited to these two diffuse parameters.

The use of higher order approximations to the Radiative transport equation, through simplified spherical harmonics expansion (SPN) in optical tomography are presented. At higher orders, the image reconstruction becomes highly under-determined due to the large increase in the number of unknowns which cannot be adequately recovered. However, reconstruction of diffuse parameters, namely optical absorption and reduced scatter have shown to be more accurate where only the sensitivity matrix used in the inverse problem is based on SPN method and image reconstruction is limited to these two diffuse parameters.

A prototype small animal imaging system was created for coupling fluorescence tomography (FT) with x-ray microcomputed tomography (microCT). The FT system has the potential to provide synergistic information content resultant from using microCT images as prior spatial information and then allows overlay of the FT image onto the original microCT image. The FT system was designed to use single photon counting to provide maximal sensitivity measurements in a noncontact geometry. Five parallel detector locations are used, each allowing simultaneous sampling of the fluorescence and transmitted excitation signals through the tissue. The calibration and linearity range performance of the system are outlined in a series of basic performance tests and phantom studies. The ability to image protoporphyrin IX in mouse phantoms was assessed and the system is ready for in vivo use to study biological production of this endogenous marker of tumors. This multimodality imaging system will have a wide range of applications in preclinical cancer research ranging from studies of the tumor microenvironment and treatment efficacy for emerging cancer therapeutics.

The development of diffuse optical tomography (DOT) instrumentation for neuroimaging of humans is challenging due to the large size and the geometry of the head and the desire to distinguish signals at different depths. One approach to this problem is to use dense imaging arrays that incorporate measurements at different source–detector distances. We previously developed a high-density DOT system that is able to obtain retinotopic measurements in agreement with functional magnetic resonance imaging and positron emission tomography. Further extension of high-density DOT neuroimaging necessitates a thorough study of the measurement and imaging sensitivity that incorporates the complex geometry of the head—including the head curvature and layered tissue structure. We present numerical simulations using a finite element model of the adult head to study the sensitivity of the measured signal as a function of the imaging array and data sampling strategy. Specifically, we quantify the imaging sensitivity available within the brain (including depths beyond superficial cortical gyri) as a function of increasing the maximum source–detector separation included in the data. Through the use of depth related sensitivity analysis, it is shown that for a rectangular grid [with 1.3 cm first nearest neighbor (NN) spacing], second NN measurements are sufficient to record absorption changes along the surface of the brain’s cortical gyri (brain tissue depth 15 mm).

Spectrally-resolved BioLuminescence optical Tomography (BLT) aims to reconstruct tomographic images of Luciferase activity within a volume using spectrally resolved emission data from internal bioluminescence sources. Uniqueness as associated with non-spectrally resolved intensity-based BioLuminescence Tomography is an established drawback and it is also demonstrated that without the use of a non-negative constraint inverse algorithm the solution is inaccurate. Reconstructed images of bioluminescence are presented showing that the location of the internal bioluminescence source can be obtained with 0.5 mm accuracy. The concept of the reciprocity approach for image reconstruction is outlined providing a dramatic improvement in computational time without loss to image accuracy.

Multi-spectral Near Infrared tomographic imaging has the potential to provide information about patho-physiological function of soft tissue. However, the specific choice of wavelengths used is crucial for the accurate separation of such parameters. It will be demonstrated that the conventionally believed choice of large set of wavelengths can be detrimental in accurate recovery of tissue specific functions. The method of determining a set of optimized bands of wavelengths will be presented and are tested using simulations and experimental data. It will be shown that the optimization method achieves images as accurate as using the full spectrum, but improves crosstalk between parameters. Additionally, a Jacobian normalization technique is presented which takes into account the varying magnitude of different optical parameters within image reconstruction, creating a more uniform update within a spectral image reconstruction model.

An approach of hierarchically implementing the spatial prior information in trans-rectal optical tomography is introduced. Trans-rectal optical imaging of the prostate deals with photon propagation through the rectum wall, the peri-prostate tissue and the prostate. Reconstructing a lesion in the prostate is challenging due to the structural complexity as well as the optical heterogeneity. Incorporating spatial "hard" a priori information available from complementary imaging modalities such as trans-rectal ultrasound could in principle improve the accuracy of trans-rectal optical tomography reconstruction. However, the reconstruction is potentially subject to the local-minimum sensitivity if the values of all regional optical properties are to be initialized simultaneously. We propose a hierarchical spatial prior approach for trans-rectal optical tomography reconstruction. Instead of assigning the initial values to all sub-regions at once, a region is initially assumed homogenous, and the reconstructed optical properties are used as the initial guess for the region as a background when a sub-region is included in the next step. This approach translates to a 3-step iteration routine whereby the first step reconstructs the entire imaging volume as a single region, the second step uses these results as the initial guess of peri-prostate tissue to reconstruct the prostate and the rectum wall, and the third step assigns the updated results as the initial values of 3 existing regions to reconstruct a lesion inside the prostate. This approach, validated by simulation and applied to experimental measurements, is more reliable in global convergence, robust in imaging of single or multiple targets, and accurate for the recovering of optical properties.

Tissue phantoms simulating the human breast were used to demonstrate the imaging capabilities of an MRI-coupled fluorescence molecular tomography (FMT) imaging system. Specifically, phantoms with low tumor-to-normal drug contrast and complex internal structure were imaged with the MR-coupled FMT system. Images of indocyanine green (ICG) fluorescence yield were recovered using a diffusion model-based approach capable of estimating the distribution of fluorescence activity in a tissue volume from tissue-boundary measurements of transmitted light. Tissue structural information, which can be determined from standard T1 and T2 MR images, was used to guide the recovery of fluorescence activity. The study revealed that this spatial guidance is critical for recovering images of fluorescence yield in tissue with low tumor-to-normal drug contrast.

A three dimensional (3D) photon transport model has been developed based on the frequency domain simplified spherical harmonics approximation (SPN) to the Radiative Transport Equation. Based on preliminary Monte Carlo studies, it is shown that for problems exhibiting strong absorption, the solutions using the 7th order SPN model (N = 7) are significantly more accurate than those from a standard Diffusion (SP1) based solver. This advance is of particular interest in the field of bioluminescent imaging where the peak emission of light emitting molecular markers are closer to the visible range (500 - 650 nm) corresponding to strong absorption due to hemoglobin.

The development of diffuse optical tomography (DOT) methods for neuroimaging of humans is challenging due to the geometry and light level constraints. A high density imaging array system has been developed and used to demonstrate the possibility of true tomographic reconstruction of cortical activity within the adult subjects which are consistent with studies using functional MRI and positron-emission tomography. This work demonstrates the benefits of using high density imaging array by investigating depth related information available from the increased number of tomographic measurements. Through the use of depth related sensitivity analysis, it is shown that the use of 4th and 5th nearest neighbor (NN) measurements, the sensitivity of the data to absorption related changes within the brain are improved dramatically, as compared to 1st, 2nd or 3rd NN measurements. Additionally, it is shown that by the use of 5th NN measurements, it is possible to recover changes at depths of up to 20 mm within the brain, which is an improvement over the use of 4th NN.

Tomographic imaging of a glioma tumor with endogenous fluorescence is demonstrated using a noncontact single-photon counting fan-beam acquisition system interfaced with microCT imaging. The fluorescence from protoporphyrin IX (PpIX) was found to be detectable, and allowed imaging of the tumor from within the cranium, even though the tumor presence was not visible in the microCT image. The combination of single-photon counting detection and normalized fluorescence to transmission detection at each channel allowed robust imaging of the signal. This demonstrated use of endogenous fluorescence stimulation from aminolevulinic acid (ALA) and provides the first in vivo demonstration of deep tissue tomographic imaging with protoporphyrin IX.

We investigate the feasibility of trans-rectal optical tomography of the prostate using an endo-rectal near-infrared (NIR) applicator that is to be integrated with a trans-rectal ultrasound (TRUS) probe. Integration with TRUS ensures accurate endo-rectal positioning of the NIR applicator and the utility of using TRUS spatial prior information to guide NIR image reconstruction. The prostate NIR image reconstruction is challenging even with the use of spatial prior owing to the anatomic complexity of the imaging domain. A hierarchical reconstruction algorithm is developed that implements cascaded initial-guesses for nested domains. This hierarchical image reconstruction method is then applied to evaluating a number of NIR applicator designs for integration with a sagittal TRUS transducer. A NIR applicator configuration feasible for instrumentation development is proposed that contains one linear array of optodes on each lateral side of the sagittal TRUS transducer. The performance of this NIR applicator is characterized for the recovery of single tumor mimicking lesion as well as dual targets in the prostate. The results suggest a strong feasibility of transrectal prostate imaging by use of the endo-rectal NIR/US probe.

Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for non-invasive functional imaging of tissue, specifically for the detection and characterization of breast cancer or other soft tissue lesions. Much work has been carried out for accurate modeling and image reconstruction from clinical data. NIRFAST, a modeling and image reconstruction package has been developed, which is capable of single wavelength and multi-wavelength optical or functional imaging from measured data. The theory behind the modeling techniques as well as the image reconstruction algorithms is presented here, and 2D and 3D examples are presented to demonstrate its capabilities. The results show that 3D modeling can be combined with measured data from multiple wavelengths to reconstruct chromophore concentrations within the tissue. Additionally it is possible to recover scattering spectra, resulting from the dominant Mie-type scatter present in tissue. Overall, this paper gives a comprehensive over view of the modeling techniques used in diffuse optical tomographic imaging, in the context of NIRFAST software package.

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.

Following several years of development the construction of a multichannel time-resolved imaging device for medical optical tomography has been completed. Images are reconstructed from time-resolved measurements by use of a scheme that employs a finite-element diffusion-based forward model and an iterative reconstruction solver. Prior to testing on clinical subjects the fully automated instrument and the reconstruction software are evaluated with tissue-equivalent phantoms. We describe our first attempt to generate multiple-slice images of a phantom without uniform properties along the axial direction, while still using a computationally fast two-dimensional reconstruction algorithm. The image quality is improved by the employment of an approximate correction method that uses scaling factors derived from the ratios of finite-element forward simulations in two and three spatial dimensions. The 32-channel system was employed to generate maps of the internal scattering and the absorption properties at 14 different transverse planes across the phantom. The images clearly reveal the locations of small inhomogeneous regions embedded within the phantom. These results were obtained by use of purely temporal data and without resource to reference measurements.

Near infrared spectroscopy with diffuse light has been used within magnetic resonance imaging for several years now. The calibration of these hybrid systems requires sophisticated phantoms which have both NIR and MR characteristics, and allow validation of all the resolution, contrast, geometry and anthropomorphic characteristics of the systems and their applications. This paper reviews the range of uses of phantoms in MR and tomography imaging, and discusses key areas of development in NIR phantoms, and then some gelatin based phantoms which have been used in the hybrid system application of breast cancer imaging.

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