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

Depth-resolved assessment of changes in concentration of chromophores using time-resolved near-infrared spectroscopy: estimation of cytochrome-c-oxidase uncertainty by Monte Carlo simulations

Time-resolved near-infrared spectroscopy (TR-NIRS) measurements can be used to recover changes in concentrations of tissue constituents ( Δ C ) by applying the moments method and the Beer-Lambert law. In this work we carried out the error propagation analysis allowing to calculate the standard deviations of uncertainty in estimation of the Δ C . Here, we show the process of choosing wavelengths for the evaluation of hemodynamic (oxy-, deoxyhemoglobin) and metabolic (cytochrome-c-oxidase (CCO)) responses within the brain tissue as measured with an in-house developed TR-NIRS multi-wavelength system, which measures at 16 consecutive wavelengths separated by 12.5 nm and placed between 650 and 950 nm. Data generated with Monte Carlo simulations on three-layered model (scalp, skull, brain) for wavelengths range from 650 to 950 nm were used to carry out the error propagation analysis for varying choices of wavelengths. For a detector with a spectrally uniform responsivity, the minimal standard deviation of the estimated changes in CCO within the brain layer, σ Δ C CCO brain  = 0.40 µM, was observed for the 16 consecutive wavelengths from 725 to 912.5 nm. For realistic a detector model, i.e. the spectral responsivity characteristic is considered, the minimum, σ Δ C CCO brain  = 0.47 µM, was observed at the 16 consecutive wavelengths from 688 to 875 nm. We introduce the method of applying the error propagation analysis to data as measured with spectral TR-NIRS systems to calculate uncertainty of recovery of tissue constituents concentrations.

Optical measures of cerebral arterial stiffness are associated with white matter signal abnormalities and cognitive performance in normal aging

Decline in fluid abilities in normal aging is associated with increased white matter lesions, measured on T1-weighted images as white matter signal abnormalities (WMSAs). WMSAs are particularly evident in hypertensive older adults, suggesting vascular involvement. However, because hypertension is assessed systemically, the specific role of cerebral arterial stiffening in WMSAs has yet to be demonstrated. In 93 cognitively normal adults (aged 18-87 years), we used a novel method to measure cerebral arterial elasticity (pulse relaxation function [PReFx]) with diffuse optical tomography (pulse-DOT) and investigated its association with WMSAs, age, and cognition. PReFx was associated with WMSAs, with older adults with low PReFx showing the greatest WMSA burden. PReFx in brain regions perfused by the middle cerebral artery showed the largest associations with WMSAs and partially mediated the relationship between age and WMSAs. Finally, WMSAs partially mediated the relationship between PReFx and fluid but not crystallized abilities scores. Taken together, these findings suggest that loss of cerebral arterial elasticity is associated with cerebral white matter lesions and age-related cognitive decline.

Mapping brain function during naturalistic viewing using high-density diffuse optical tomography

Naturalistic stimuli, such as movies, more closely recapitulate "real life" sensory processing and behavioral demands relative to paradigms that rely on highly distilled and repetitive stimulus presentations. The rich complexity inherent in naturalistic stimuli demands an imaging system capable of measuring spatially distributed brain responses, and analysis tools optimized for unmixing responses to concurrently presented features. In this work, the combination of passive movie viewing with high-density diffuse optical tomography (HD-DOT) is developed as a platform for naturalistic brain mapping. We imaged healthy young adults during free viewing of a feature film using HD-DOT and observed reproducible, synchronized cortical responses across a majority of the field-of-view, most prominently in hierarchical cortical areas related to visual and auditory processing, both within and between individuals. In order to more precisely interpret broad patterns of cortical synchronization, we extracted visual and auditory features from the movie stimulus and mapped the cortical responses to the features. The results demonstrate the sensitivity of HD-DOT to evoked responses during naturalistic viewing, and that feature-based decomposition strategies enable functional mapping of naturalistic stimulus processing, including human-generated speech.

Hyper-spectral Recovery of Cerebral and Extra-Cerebral Tissue Properties Using Continuous Wave Near-Infrared Spectroscopic Data

Near-infrared spectroscopy (NIRS) is widely used as a non-invasive method to monitor the hemodynamics of biological tissue. A common approach of NIRS relies on continuous wave (CW) methodology, i.e. utilizing intensity-only measurements, and, in general, assumes homogeneity in the optical properties of the biological tissue. However, in monitoring cerebral hemodynamics within humans, this assumption is not valid due to complex layered structure of the head. The NIRS signal that contains information about cerebral blood hemoglobin levels is also contaminated with extra-cerebral tissue hemodynamics, and any recovery method based on such a priori homogenous approximation would lead to erroneous results. In this work, utilization of hyper-spectral intensity only measurements (i.e., CW) at multiple distances are presented and are shown to recover two-layered tissue properties along with the thickness of top layer, using an analytical solution for a two-layered semi-infinite geometry. It is demonstrated that the recovery of tissue oxygenation index (TOI) of both layers can be achieved with an error of 4.4%, with the recovered tissue thickness of 4% error. When the data is measured on a complex tissue such as the human head, it is shown that the semi-infinite recovery model can lead to uncertain results, whereas, when using an appropriate model accounting for the tissue-boundary structure, the tissue oxygenation levels are recovered with an error of 4.2%, and the extra-cerebral tissue thickness with an error of 11.8%. The algorithm is finally used together with human subject data, demonstrating robustness in application and repeatability in the recovered parameters that adhere well to expected published parameters.

The Optical Effective Attenuation Coefficient as an Informative Measure of Brain Health in Aging

Aging is accompanied by widespread changes in brain tissue. Here, we hypothesized that head tissue opacity to near-infrared light provides information about the health status of the brain’s cortical mantle. In diffusive media such as the head, opacity is quantified through the Effective Attenuation Coefficient (EAC), which is proportional to the geometric mean of the absorption and reduced scattering coefficients. EAC is estimated by the slope of the relationship between source–detector distance and the logarithm of the amount of light reaching the detector (optical density). We obtained EAC maps across the head in 47 adults (age range 18–75 years), using a high-density dual-wavelength optical system. We correlated regional and global EAC measures with demographic, neuropsychological, structural and functional brain data. Results indicated that EAC values averaged across wavelengths were strongly associated with age-related changes in cortical thickness, as well as functional and neuropsychological measures. This is likely because the EAC largely depends on the thickness of the sub-arachnoid cerebrospinal fluid layer, which increases with cortical atrophy. In addition, differences in EAC values between wavelengths were correlated with tissue oxygenation and cardiorespiratory fitness, indicating that information about cortical health can be derived non-invasively by quantifying the EAC.

Investigation into repetitive concussion in sport (RECOS): study protocol of a prospective, exploratory, observational cohort study

INTRODUCTION

Sport-related concussion management remains a diagnostic dilemma to clinicians in all strata of care, coaching staff and players alike. The lack of objective diagnostic and prognostic biomarkers and over-reliance on subjective clinical assessments carries a significant health risk of undiagnosed concussive episodes and early return to play before full recovery increasing the risk of sustaining additional concussion, and leading to long-term sequelae and/or unfavourable outcome.

OBJECTIVE

To identify a set of parameters (neuroimaging with neurophysiological, biological and neuropsychological tests) that may support pitch-side and outpatient clinical decision-making in order to objectively diagnose concussion, determine the severity of injury, guide a safe return to play and identify the potential predictors of the long-term sequelae of concussion.

METHODS AND ANALYSIS

An exploratory, observational, prospective, cohort study recruiting between 2017 and 2020. The participants will have a baseline preseason screening (brain imaging, neuropsychological assessments, serum, urine and saliva sampling). If a screened player later suffers a concussion and/or multiple concussions then he/she will be assessed again with the same protocol within 72 hours, and their baseline data will be used as internal control as well as normative data. Inferential statistical analysis will be performed to determine correlations between biological, imaging techniques and neuropsychological assessments.

ETHICS AND DISSEMINATION

This study was approved by the East of England-Essex Research Ethics Committee on 22 September 2017-REC 17/EE/0275; IRAS 216703. The results of this study will be presented at national and international conferences and submitted for publication in peer reviewed journals.

TRIAL REGISTRATION NUMBER

ISRCTN16974791; Pre-results.

High-density functional diffuse optical tomography based on frequency-domain measurements improves image quality and spatial resolution

Measurements of dynamic near-infrared (NIR) light attenuation across the human head together with model-based image reconstruction algorithms allow the recovery of three-dimensional spatial brain activation maps. Previous studies using high-density diffuse optical tomography (HD-DOT) systems have reported improved image quality over sparse arrays. These HD-DOT systems incorporated multidistance overlapping continuous wave measurements that only recover differential intensity attenuation. We investigate the potential improvement in reconstructed image quality due to the additional incorporation of phase shift measurements, which reflect the time-of-flight of the measured NIR light, within the tomographic reconstruction from high-density measurements. To evaluate image reconstruction with and without the additional phase information, we simulated point spread functions across a whole-scalp field of view in 24 subject-specific anatomical models using an experimentally derived noise model. The addition of phase information improves the image quality by reducing localization error by up to 59% and effective resolution by up to 21% as compared to using the intensity attenuation measurements alone. Furthermore, we demonstrate that the phase data enable images to be resolved at deeper brain regions where intensity data fail, which is further supported by utilizing experimental data from a single subject measurement during a retinotopic experiment.

Dynamic Activation Patterns of the Motor Brain Revealed by Diffuse Optical Tomography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019;2019:6028-6031. [PMID: 31947220 DOI: 10.1109/embc.2019.8857370]

Diffuse optical tomography (DOT), a subset of functional near-infrared spectroscopy (fNIRS), is a noninvasive functional imaging modality for studying the human brain in normal and diseased conditions. It measures changes in concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) in the blood vasculature of the brain. In contrast to functional magnetic resonance imaging (fMRI), the gold standard in human brain imaging, DOT offers the advantage of higher temporal resolution, portability, lower cost, multiple contrasts and usability for persons who cannot otherwise utilize MRI-based imaging modalities, including bedridden patients and infants, etc. The goal of the present study was to evaluate performance of a DOT method in studying dynamic patterns of brain activations involving motor control. CW-fNIRS data were acquired in four sessions from a healthy male participant when he performed a motor task in a block-design experiment. Results from experimental data showed pronounced activity in the primary motor cortex (M1), contralateral to the clenching hand. It was further observed that the M1 activity was consistent over four sessions. Furthermore, temporal dynamics of motor activity at each session further revealed well-sequenced activation patterns among M1, premotor cortex (PMC), and supplementary motor area (SMA). Timed ipsilateral motor activity suppression was also observed several seconds after the onset of contralateral M1 activity. More importantly, these temporal dynamics were similarly observed in all four sessions. These preliminary results suggest that the DOT method has the sensitivity, reliability, and spatio-temporal resolutions to study activities originated from the motor cortices. A full-scope evaluation and validation in more participants on the motor system can establish it as a promising neuroimaging tool to study, such as, infants at the risk of cerebral palsy or elders with Parkinson's due to its portability and usability in clinical environments.

Differential pathlength factor in continuous wave functional near-infrared spectroscopy: reducing hemoglobin's cross talk in high-density recordings

Functional near-infrared spectroscopy (fNIRS) estimates the functional oscillations of oxyhemoglobin and deoxyhemoglobin in the cortex through scalp-located multiwavelength recordings. Hemoglobin oscillations are inferred through temporal changes in continuous-wave (CW) light attenuation. However, because of the diffusive multilayered head tissue structures, the photon path is longer than the source-detector separation, complicating hemoglobin evaluation. This aspect is incorporated in the modified Beer-Lambert law where the source-detector distance is multiplied by the differential pathlength factor (DPF). Since DPF estimation requires photons' time-of-flight information, DPF is assumed a priori in CW-fNIRS. Importantly, errors in the DPF spectrum induce hemoglobin cross talk, which is detrimental for fNIRS. We propose to estimate subject-specific DPF spectral dependence relying on multidistance high-density measurements. The procedure estimates the effective attenuation coefficient (EAC), which is proportional to the geometric mean of absorption and reduced scattering. Since DPF depends on the scattering-to-absorption ratio, EAC limits the spectral dependence assumption to scattering. This approach was compared to a standard frequency-domain multidistance procedure. A good association between the two methods ( r 2 = 0.69 ) was obtained. This approach could estimate low-resolution maps of the DPF spectral dependence through large field of view, high-density systems, reducing hemoglobin cross talk, and increasing fNIRS sensitivity and specificity to brain activity without instrumentation modification.

Three-dimensional frequency-domain optical anisotropy imaging of biological tissues with near-infrared light

PURPOSE

Near-infrared optical imaging aims to reconstruct the absorption μ a and scattering μ s coefficients in order to detect tumors at early stage. However, the reconstructions have only been limited to μ a and μ s due to theoretical and computational limitations. The authors propose an efficient method of the reconstruction, in three-dimensional geometries, of the anisotropy factor g of the Henyey-Greenstein phase function as a new optical imaging biomarker.

METHODS

The light propagation in biological tissues is accurately modeled by the radiative transfer equation (RTE) in the frequency-domain. The reconstruction algorithm is based on a gradient-based updating scheme. The adjoint method is used to efficiently compute the gradient of the objective function which represents the discrepancy between simulated and measured boundary data. A parallel implementation is carried out to reduce the computational time.

RESULTS

We show that by illuminating only one surface of a tissue-like phantom, the algorithm is able to accurately reconstruct optical values and different shapes (spherical and cylindrical) that characterize small tumor-like inclusions. Numerical simulations show the robustness of the algorithm to reconstruct the anisotropy factor with different contrast levels, inclusion depths, initial guesses, heterogeneous background, noise levels, and two-layered medium. The crosstalk problem when reconstructing simultaneously μ s and g has been reported and achieved with a reasonable quality.

CONCLUSIONS

The proposed RTE-based reconstruction algorithm is robust to spatially retrieve and localize small tumoral inclusions. Heterogeneities in g-factor have been accurately reconstructed which makes the new algorithm a candidate of choice to image this factor as new intrinsic contrast biomarker for optical imaging.

Self-calibrating time-resolved near infrared spectroscopy

Time-resolved near infrared spectroscopy is considered to be a gold standard technique when measuring absolute values of tissue optical properties, as it provides separable and independent information about both tissue absorption and scattering. However, time-resolved instruments require an accurate characterization by measuring the instrument response function in order to decouple the contribution of the instrument itself from the measurement. In this work, a new approach to the methodology of analysing time-resolved data is presented where the influence of instrument response function is eliminated from the data and a self-calibrating analysis is proposed. The proposed methodology requires an instrument to provide at least two wavelengths and allows spectral parameters recovery (optical properties or constituents concentrations and reduced scatter amplitude and power). Phantom and in-vivo data from two different time-resolved systems are used to validate the accuracy of the proposed self-calibrating approach, demonstrating that parameters recovery compared to the conventional curve fitting approach is within 10% and benefits from introducing a spectral constraint to the reconstruction problem. It is shown that a multi-wavelength time-resolved data can be used for parameters recovery directly without prior calibration (instrument response function measurement).

High-density diffuse optical tomography for imaging human brain function

This review describes the unique opportunities and challenges for noninvasive optical mapping of human brain function. Diffuse optical methods offer safe, portable, and radiation free alternatives to traditional technologies like positron emission tomography or functional magnetic resonance imaging (fMRI). Recent developments in high-density diffuse optical tomography (HD-DOT) have demonstrated capabilities for mapping human cortical brain function over an extended field of view with image quality approaching that of fMRI. In this review, we cover fundamental principles of the diffusion of near infrared light in biological tissue. We discuss the challenges involved in the HD-DOT system design and implementation that must be overcome to acquire the signal-to-noise necessary to measure and locate brain function at the depth of the cortex. We discuss strategies for validation of the sensitivity, specificity, and reliability of HD-DOT acquired maps of cortical brain function. We then provide a brief overview of some clinical applications of HD-DOT. Though diffuse optical measurements of neurophysiology have existed for several decades, tremendous opportunity remains to advance optical imaging of brain function to address a crucial niche in basic and clinical neuroscience: that of bedside and minimally constrained high fidelity imaging of brain function.

Clinical Brain Monitoring with Time Domain NIRS: A Review and Future Perspectives

Near-infrared spectroscopy (NIRS) is an optical technique that can measure brain tissue oxygenation and haemodynamics in real-time and at the patient bedside allowing medical doctors to access important physiological information. However, despite this, the use of NIRS in a clinical environment is hindered due to limitations, such as poor reproducibility, lack of depth sensitivity and poor brain-specificity. Time domain NIRS (or TD-NIRS) can resolve these issues and offer detailed information of the optical properties of the tissue, allowing better physiological information to be retrieved. This is achieved at the cost of increased instrument complexity, operation complexity and price. In this review, we focus on brain monitoring clinical applications of TD-NIRS. A total of 52 publications were identified, spanning the fields of neonatal imaging, stroke assessment, traumatic brain injury (TBI) assessment, brain death assessment, psychiatry, peroperative care, neuronal disorders assessment and communication with patient with locked-in syndrome. In all the publications, the advantages of the TD-NIRS measurement to (1) extract absolute values of haemoglobin concentration and tissue oxygen saturation, (2) assess the reduced scattering coefficient, and (3) separate between extra-cerebral and cerebral tissues, are highlighted; and emphasize the utility of TD-NIRS in a clinical context. In the last sections of this review, we explore the recent developments of TD-NIRS, in terms of instrumentation and methodologies that might impact and broaden its use in the hospital.

Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation

OBJECTIVE

Fluorescence molecular tomography (FMT) can provide valuable molecular information by mapping the bio-distribution of fluorescent reporter molecules in the intact organism. Various prototype FMT systems have been introduced during the past decade. However, none of them has evolved as a standard tool for routine biomedical research. The goal of this paper is to develop a software package that can automate the complete FMT reconstruction procedure.

METHODS

We present smart toolkit for fluorescence tomography (STIFT), a comprehensive platform comprising three major protocols: 1) virtual FMT, i.e., forward modeling and reconstruction of simulated data; 2) control of actual FMT data acquisition; and 3) reconstruction of experimental FMT data.

RESULTS

Both simulation and phantom experiments have shown robust reconstruction results for homogeneous and heterogeneous tissue-mimicking phantoms containing fluorescent inclusions.

CONCLUSION

STIFT can be used for optimization of FMT experiments, in particular for optimizing illumination patterns.

SIGNIFICANCE

This paper facilitates FMT experiments by bridging the gaps between simulation, actual experiments, and data reconstruction.

Sensitivity Uniformity Ratio as a New Index to Optimize the Scanning Geometry for Fluorescent Molecular Tomography

Background:

Molecular fluorescence imaging is widely used as a noninvasive method to study the cellular and molecular mechanisms. In the optical imaging system, the sensitivity is the change of the intensity received by the detector for the changed optical characteristics (fluorescence) in each sample point. Sensitivity could be considered as a function of imaging geometry. A favor imaging system has a uniform and high-sensitivity coefficient for each point of the sample. In this study, a new parameter was proposed which the optimal angle between the source and detector could be determined based on this parameter.

Methods:

For evaluation of the new method, a two-dimensional mesh with a radius of 20 mm and 5133 nodes was built. In each reconstruction, 0.5-mm fluorescence heterogeneity with a contrast-to-purpose ratio of fluorescence yield of 10 was randomly added at different points of the sample. The source and the detector were simulated in different geometric conditions. The calculations were performed using the NIRFAST and MATLAB software. The relationship between mean squared error (MSE) and sensitivity uniformity ratio (SUR) was evaluated using the correlation coefficient. Finally, based on the new index, an optimal geometrical strategy was introduced.

Results:

There was a negative correlation coefficient (R = −0.78) with the inverse relationship between the SUR and MSE indices. The reconstructed images showed that the better image quality achieved using the optimal geometry for all scanning depths. For the conventional geometry, there is an artifact in the opposite side of the inhomogeneity at the shallow depths, which has been eliminated in the reconstructed images achieved using the optimal geometry.

Conclusion:

The SUR is a powerful computational tool which could be used to determine the optimal angles between the source and detector for each scanning depth.

Oral and Subcutaneous Administration of a Near-Infrared Fluorescent Molecular Imaging Agent Detects Inflammation in a Mouse Model of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease that causes irreversible damage to the joints. However, effective drugs exist that can stop disease progression, leading to intense interest in early detection and treatment monitoring to improve patient outcomes. Imaging approaches have the potential for early detection, but current methods lack sensitivity and/or are time-consuming and expensive. We examined potential routes for self-administration of molecular imaging agents in the form of subcutaneous and oral delivery of an integrin binding near-infrared (NIR) fluorescent imaging agent in an animal model of RA with the long-term goal of increasing safety and patient compliance for screening. NIR imaging has relatively low cost, uses non-ionizing radiation, and provides minimally invasive spatial and molecular information. This proof-of-principle study shows significant uptake of an IRDye800CW agent in inflamed joints of a collagen antibody induced arthritis (CAIA) mouse model compared to healthy joints, irrespective of the method of administration. The imaging results were extrapolated to clinical depths in silico using a 3D COMSOL model of NIR fluorescence imaging in a human hand to examine imaging feasability. With target to background concentration ratios greater than 5.5, which are achieved in the mouse model, these probes have the potential to identify arthritic joints following oral delivery at clinically relevant depths.

Assessment of cerebrovascular development and intraventricular hemorrhages in preterm infants with optical measures of the brain arterial pulse wave

Preterm infants (born at 24-34 weeks of gestational age) suffer from a high incidence of neurological complications. Cerebrovascular lesions (intraventricular hemorrhages, IVH, and ischemic injury) due to the immaturity of the vascular system and its inability to adapt to the extra-uterine environment are the major causes of adverse neurological outcomes. We investigated the feasibility of assessing cerebrovascular status in preterm infants using a novel non-invasive optical procedure, pulse-DOT, usable within the incubator. Pulse-DOT, validated in adults, provides estimates of cerebral arterial status based on optical measurements of the pulse wave. These measurements are taken with a high-density optode montage and provide accurate spatial and temporal information. We found that two pulse parameters (pulse relaxation function, PReFx, and pulse rise time, PRT) in the investigated frontotemporal region, correlated with infant's age at recording, indexing cerebrovascular development. Moreover, PRT differentiated infants with and without concurrent IVH (sensitivity = 100%, specificity = 70%). These values are at least as high as those of the resistivity index obtained with transcranial Doppler of the middle cerebral artery, the current clinical method of choice for investigating arterial elasticity in preterm infants. This makes pulse-DOT a promising tool for investigating cerebrovascular risk factors and related pathologies in preterm infants.

Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction

As photoacoustic (PA) imaging makes its way into the clinic, the accuracy of PA-based metrics becomes increasingly important. To address this need, a method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed and validated to accurately estimate oxygen saturation (SO₂) in tissue. With data from a Vevo LAZR system, performance of our LFC approach was assessed in ex vivo blood targets (37.6%-99.6% SO₂) and in vivo rat arteries. Estimation error of absolute SO₂ and change in SO₂ reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while the accuracy of the LFC method was correlated with the number of wavelengths acquired. This paper demonstrates the need for an SNR-regularized LFC to accurately quantify SO₂ with PA imaging.

Noninvasive imaging of dual-agent uptake in glioma and normal tissue using MRI-coupled fluorescence tomography

As the role of immuno-oncological therapeutics expands, the capacity to noninvasively quantify molecular targets and drug-target engagement is increasingly critical to drug development efforts and treatment monitoring. Previously, we showed that MRI-coupled dual-agent fluorescence tomography (FMT) is capable of estimating the concentration of epidermal growth factor receptor (EGFR) in orthotopic glioma models noninvasively. This approach uses the dynamic information of two fluorescent agents (a targeted agent and untargeted isotype) to estimate tumor receptor concentration in vivo. This approach generally relies on the two tracers having similar kinetics in normal tissues, which may not always be the case. Herein, we describe an additional channel added to the MRI-FMT system which measures the uptake of both agents in the normal muscle, data which can be used to compensate for differing kinetic behavior.

Spectral correction for handheld optoacoustic imaging by means of near-infrared optical tomography in reflection mode

In vivo imaging of tissue/vasculature oxygen saturation levels is of prime interest in many clinical applications. To this end, the feasibility of combining two distinct and complementary imaging modalities is investigated: optoacoustics (OA) and near-infrared optical tomography (NIROT), both operating noninvasively in reflection mode. Experiments were conducted on two optically heterogeneous phantoms mimicking tissue before and after the occurrence of a perturbation. OA imaging was used to resolve submillimetric vessel-like optical absorbers at depths up to 25 mm, but with a spectral distortion in the OA signals. NIROT measurements were utilized to image perturbations in the background and to estimate the light fluence inside the phantoms at the wavelength pair (760 nm, 830 nm). This enabled the spectral correction of the vessel-like absorbers' OA signals: the error in the ratio of the absorption coefficient at 830 nm to that at 760 nm was reduced from 60%-150% to 10%-20%. The results suggest that oxygen saturation (SO ₂ ) levels in arteries can be determined with <10% error and furthermore, that relative changes in vessels' SO ₂ can be monitored with even better accuracy. The outcome relies on a proper identification of the OA signals emanating from the studied vessels.

Computer simulation analysis of source-detector position for percutaneously measured O2 -gas signal in a three-dimensional preterm infant lung

Further improvements in the clinical care of our most vulnerable patients-preterm infants-are needed. Novel diagnostic and surveillance tools facilitate such advances. The GASMAS technique has shown potential to become a tool to, noninvasively, monitor gas in the lungs of preterm infants, by placing a laser source and a detector on the chest wall skin. It is believed that this technology will become a valuable clinical diagnostic tool for monitoring the lung function of these patients. Today, the technology is, for this application, in an early stage and further investigations are needed. In the present study, a three-dimensional computer model of the thorax of an infant is constructed, from a set of CT images. Light transport simulations are performed to provide information about the position dependence of the laser- and detector probe on the thorax of the infant. The result of the simulations, based on the study method and the specified model used in this work, indicates that measurement geometries in front and on the side of the lung are favorable in order to obtain a good gas absorption signal.

Development of a multi-channel NIRS-USG hybrid imaging system for detecting prostate cancer and improving the accuracy of imaging-based diagnosis: a phantom study

Purpose

This study aimed to develop a multi-channel near-infrared spectroscopy (NIRS) and ultrasonography (USG) fusion imaging system for imaging prostate cancer and to verify its diagnostic capability by applying the hybrid imaging system to a prostate cancer phantom.

Methods

A multi-channel NIRS system using the near-infrared 785-nm wavelength with 12 channels and four detectors was developed. After arranging the optical fibers around a USG transducer, we performed NIRS imaging and grayscale USG imaging simultaneously. Fusion imaging was obtained by processing incoming signals and the spatial reconstruction of NIRS, which corresponded with grayscale USG acquired at the same time. The NIRS-USG hybrid system was applied to a silicone-based optical phantom of the prostate gland containing prostate cancer to verify its diagnostic capability qualitatively.

Results

The NIRS-USG hybrid imaging system for prostate cancer imaging simultaneously provided anatomical and optical information with 2-dimensional registration. The hybrid imaging system showed more NIR attenuation over the prostate cancer model than over the model of normal prostate tissue. Its diagnostic capability to discriminate a focal area mimicking the optical properties of prostate cancer from the surrounding background mimicking the optical properties of normal prostate tissue was verified by applying the hybrid system to a silicone-based optical phantom of prostate cancer.

Conclusion

This study successfully demonstrated that the NIRS-USG hybrid system may serve as a new imaging method for improving the diagnostic accuracy of prostate cancer, with potential utility for future clinical applications.

A Single Simulation Platform for Hybrid Photoacoustic and RF-Acoustic Computed Tomography

In recent years, multimodal thermoacoustic imaging has demonstrated superior imaging quality compared to other emerging modalities. It provides functional and molecular information, arising due to electromagnetic absorption contrast, at ultrasonic resolution using inexpensive and non-ionizing imaging methods. The development of optical- as well as radio frequency (RF)-induced thermoacoustic imaging systems would benefit from reliable numerical simulations. To date, most numerical models use a combination of different software in order to model the hybrid thermoacoustic phenomenon. Here, we demonstrate the use of a single open source finite element software platform (ONELAB) for photo- and RF-acoustic computed tomography. The solutions of the optical diffusion equation, frequency domain Maxwell’s equations, and time-domain wave equation are used to solve the optical, electromagnetic, and acoustic propagation problems, respectively, in ONELAB. The results on a test homogeneous phantom and an approximate breast phantom confirm that ONELAB is a very effective software for both photo- and RF-acoustic simulations, and invaluable for developing new reconstruction algorithms and hardware systems.

Multispectral Near-Infrared Optical Tomography for Cancer Hypoxia Study in Mice

Oxygenation of a tumor is one of the most important predictive factors: hypoxia is associated with aggressive tumors and substantially lower survival rate. Despite this high relevance of tumor oxygenation, there is currently no bedside technique available to measure it in clinical routine care. The aim of this work is to determine the oxygenation of tissue in mice by a continuous wave multispectral near-infrared optical tomograph (mNIROT). Tomographic reconstructions were processed by a massively modified NIRFAST software. We quantitatively measured the tissue oxygen saturation of the tumors in 4 BALB/c nude, female mice with human colon carcinoma cancer cells DLD-1 KRAS^wt injected subcutaneously. The study revealed changes of oxygenation in tumors on the long-term.

A New Method Based on Virtual Fluence Detectors and Software Toolbox for Handheld Spectral Optoacoustic Tomography

A minimal setup for optoacoustic (OA) imaging requires an ultrasound probe and a pulsed laser. Such a system is capable of imaging small blood vessels and is sensitive to variations in their oxygen saturation. However, absolute oxygenation values cannot be obtained without a proper correction for the varying light fluence resulting from the optical attenuation in the surrounding tissue. Other techniques, such as near-infrared optical tomography (NIROT) can be employed to assist OA imaging for fluence compensation. In this paper, we propose using blood vessels as virtual fluence detectors (VD), which serve as light detectors for NIROT image reconstructions. By avoiding the use of real photon detectors, a simpler system could be implemented in a hand-held device comparable in size with conventional ultrasound probes. Even for a low number of VDs it provides increased informational value which, in combination with a large number of light sources, results in precise reconstructions. We define a tomographic inverse problem based on ratios of OA signals measured at several wavelengths where optical properties of VDs, tumor and normal tissue can be reconstructed simultaneously. The use of ratio data effectively removes light source skin coupling errors for the case of emission in a single point, which is required for clinical applications. We have defined the mathematical structure of an inverse problem where chromophore concentrations for normal, tumor and embedded VDs are obtained simultaneously from this ratio data. To test the performance of our approach we show an image reconstruction on a virtual phantom with an embedded tumor in the vicinity of eight blood vessels. We conclude that this limited number of VDs, located in areas of maximum sensitivity result in high quality reconstructions. For the simplest case of a single blood vessel located in a homogeneous tissue, we present a graphical user interface based toolbox for conducting virtual experiments. The toolbox can be used to assist in the design and optimization of suitable hardware for different applications, among which imaging tumor oxygenation and ischemic lesions in the brain of preterm infants are of great clinical value.

Solving 3-D PDEs by Tensor B-Spline Methodology: A High Performance Approach Applied to Optical Diffusion Tomography

Solutions of 3-D elliptic PDEs form the basis of many mathematical models in medicine and engineering. Solving elliptic PDEs numerically in 3-D with fine discretization and high precision is challenging for several reasons, including the cost of 3-D meshing, the massive increase in operation count, and memory consumption when a high-order basis is used, and the need to overcome the "curse of dimensionality." This paper describes how these challenges can be either overcome or relaxed by a Tensor B-spline methodology with the following key properties: 1) the tensor structure of the variational formulation leads to regularity, separability, and sparsity, 2) a method for integration over the complex domain boundaries eliminates meshing, and 3) the formulation induces high-performance and memory-efficient computational algorithms. The methodology was evaluated by application to the forward problem of Optical Diffusion Tomography (ODT), comparing it with the solver from a state-of-the-art Finite-Element Method (FEM)-based ODT reconstruction framework. We found that the Tensor B-spline methodology allows one to solve the 3-D elliptic PDEs accurately and efficiently. It does not require 3-D meshing even on complex and non-convex boundary geometries. The Tensor B-spline approach outperforms and is more accurate than the FEM when the order of the basis function is > 1, requiring fewer operations and lower memory consumption. Thus, the Tensor B-spline methodology is feasible and attractive for solving large elliptic 3-D PDEs encountered in real-world problems.

Bioluminescence tomography with structural information estimated via statistical mouse atlas registration

Due to an ill-posed and underestimated characteristic of bioluminescence tomography (BLT) reconstruction, a priori anatomical information obtained from computed tomography (CT) or magnetic resonance imaging (MRI), is usually incorporated to improve the reconstruction accuracy. The organs need to be segmented, which is time-consuming and challenging, especially for the low-contrast CT images. In this paper, we present a BLT reconstruction method based on a statistical mouse atlas to improve the efficiency of heterogeneous model generation and the accuracy of target localization. The low-contrast CT image of the mouse was first registered to the statistical mouse atlas model with the constraints of mouse surface and high-contrast organs (bone and lung). Then the other organs, such as the liver and kidney, were determined automatically through the statistical mouse atlas model. The estimated organs were then discretized into tetrahedral meshes for BLT reconstruction. The linearized Bregman method was used to solve the sparse inverse problem of BLT by minimizing the regularization function (L1 norm plus L2 norm with smooth factor). Both numerical simulations and in vivo experiments were conducted, and the results demonstrate that even though the localization of the estimated organs may not be exactly accurate, the proposed method is feasible to reconstruct the bioluminescent source effectively and accurately with the estimated organs. This method would greatly benefit the bioluminescent light source localization for hybrid BLT/CT systems.

Exploiting neurovascular coupling: a Bayesian sequential Monte Carlo approach applied to simulated EEG fNIRS data

OBJECTIVE

Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown.

APPROACH

Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF).

MAIN RESULTS

We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements.

SIGNIFICANCE

The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.

Weighting function effects in a direct regularization method for image-guided near-infrared spectral tomography of breast cancer

Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast by 10%, the contrast to noise ratio by 20% and the full width half maximum (FWHM) by 30%. The results from phantoms and human images show that a linear inverse distance weighting function appears optimal, and that incorporation of this function can generally improve the recovered total hemoglobin contrast of the tumor to the normal surrounding tissue by more than 15% in human cases.

Comparison of source localization techniques in diffuse optical tomography for fNIRS application using a realistic head model

Functional near-infrared spectroscopy (fNIRS) is a non-invasive imaging technique that elicits growing interest for research and clinical applications. In the last decade, efforts have been made to develop a mathematical framework in order to image the effective sources of hemoglobin variations in brain tissues. Different approaches can be used to impose additional information or constraints when reconstructing the cerebral images of an ill-posed problem. The goal of this study is to compare the performance and limitations of several source localization techniques in the context of fNIRS tomography using individual anatomical magnetic resonance imaging (MRI) to model light propagation. The forward problem is solved using a Monte Carlo simulation of light propagation in the tissues. The inverse problem has been linearized using the Rytov approximation. Then, Tikhonov regularization applied to least squares, truncated singular value decomposition, back-projection, L1-norm regularization, minimum norm estimates, low resolution electromagnetic tomography and Bayesian model averaging techniques are compared using a receiver operating characteristic analysis, blurring and localization error measures. Using realistic simulations (n = 450) and data acquired from a human participant, this study depicts how these source localization techniques behave in a human head fNIRS tomography. When compared to other methods, Bayesian model averaging is proposed as a promising method in DOT and shows great potential to improve specificity, accuracy, as well as to reduce blurring and localization error even in presence of noise and deep sources. Classical reconstruction methods, such as regularized least squares, offer better sensitivity but higher blurring; while more novel L1-based method provides sparse solutions with small blurring and high specificity but lower sensitivity. The application of these methods is also demonstrated experimentally using visual fNIRS experiment with adult participant.

Plasmonic Optical Imaging of Gold Nanorods Localization in Small Animals

Gold nanoparticles (GNP) have been intensively investigated for applications in cancer imaging and therapy. Most imaging studies focused on microscopic imaging. Their potential as optical imaging probes for whole body small animal imaging has rarely been explored. Taking advantage of their surface plasmon resonance (SPR) properties, we aim to develop a noninvasive diffuse optical imaging method to map the distribution of a special type of GNP, gold nanorods (GNR), in small animals. We developed an integrated dual-modality imaging system capable of both x-ray computed tomography (XCT) and diffuse optical tomography (DOT). XCT provides the animal anatomy and contour required for DOT; DOT maps the distribution of GNR in the animal. This SPR enhanced optical imaging (SPROI) technique was investigated using simulation, phantom and mouse experiments. The distribution of GNR at various concentrations (0.1-100 nM, or 3.5 ug/g-3.5 mg/g) was successfully reconstructed from centimeter-scaled volumes. SPROI detected GNR at 18 μg/g concentration in the mouse breast tumor, and is 3 orders more sensitive than x-ray imaging. This study demonstrated the high sensitivity of SPROI in mapping GNR distributions in small animals. It does not require additional imaging tags other than GNR themselves. SPROI can be used to detect tumors targeted by GNR via passive targeting based on enhanced permeability and retention or via active targeting using biologically conjugated ligands.

Direct Regularization From Co-Registered Contrast MRI Improves Image Quality of MRI-Guided Near-Infrared Spectral Tomography of Breast Lesions

An approach using direct regularization from co-registered dynamic contrast enhanced magnetic reson- ance images was used to reconstruct near-infrared spectral tomography patient images, which does not need image segmentation. 20 patients with mammography/ultrasound confirmed breast abnormalities were involved in this paper, and the resulting images indicated that tumor total hemoglobin concentration contrast differentiated malignant from benign cases (p-value = 0.021). The approach prod- uced reconstructed images, which significantly reduced surface artifacts near the source-detector locations (p-value = 4.16e-6).

Nth-order linear algorithm for diffuse correlation tomography

The current approaches to imaging the tissue blood flow index (BFI) from diffuse correlation tomography (DCT) data are either an analytical solution or a finite element method, both of which are unable to simultaneously account for the tissue heterogeneity and fully utilize the DCT data. In this study, a new imaging concept for DCT, namely NL-DCT, was created by us in which the medical images are combined with light Monte Carlo simulation to provide geometrical and heterogeneous information in tissue. Moreover, the DCT data at multiple delay time are fully utilized via iterative linear regression. The unique merit of NL-DCT in utilizing the medical images as prior information, when combined with a split Bregman algorithm for total variation minimization (Bregman-TV), was validated on a realistic human head model. Computer simulation outcomes demonstrate the accuracy and robustness of NL-DCT in localizing and separating the flow anomalies as well as the capability to preserve edges of anomalies.

Fast localization method of an anomaly in tissue based on differential optical density

The position of the source-detector (S-D) relative to an anomaly has an important influence on the detection effect in non-invasive near-infrared spectroscopy-based methods. In this study, a single-source multi-detector structure was designed in order to realize the rapid localization of anomalies within tissue. This method uses finite element analysis of the optical density distribution for different horizontal positions, depths and diameters of anomalies. The difference in optical density between the detectors was then calculated. The simulation results show that the horizontal position of the anomaly in the tissue can be quickly located according to the differential optical density difference curves formed by the multiple detectors. The Gaussian fitting feature of these curves shows strong correlation with the horizontal positions, depths and diameters of the anomaly. Through the differential optical density difference curves, rapid localization within the region of interest can be achieved. This method provides an important reference for sources and detectors location for tumor detection, brain function optical imaging and other fields using near infrared spectroscopy, and improves its detection accuracy.

The NIRS Brain AnalyzIR Toolbox

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650-900 nm) to measure changes in cerebral blood volume and oxygenation. Over the last several decades, this technique has been utilized in a growing number of functional and resting-state brain studies. The lower operation cost, portability, and versatility of this method make it an alternative to methods such as functional magnetic resonance imaging for studies in pediatric and special populations and for studies without the confining limitations of a supine and motionless acquisition setup. However, the analysis of fNIRS data poses several challenges stemming from the unique physics of the technique, the unique statistical properties of data, and the growing diversity of non-traditional experimental designs being utilized in studies due to the flexibility of this technology. For these reasons, specific analysis methods for this technology must be developed. In this paper, we introduce the NIRS Brain AnalyzIR toolbox as an open-source Matlab-based analysis package for fNIRS data management, pre-processing, and first- and second-level (i.e., single subject and group-level) statistical analysis. Here, we describe the basic architectural format of this toolbox, which is based on the object-oriented programming paradigm. We also detail the algorithms for several of the major components of the toolbox including statistical analysis, probe registration, image reconstruction, and region-of-interest based statistics.

Maps of in vivo oxygen pressure with submillimetre resolution and nanomolar sensitivity enabled by Cherenkov-excited luminescence scanned imaging

Low signal-to-noise ratios and limited imaging depths restrict the ability of optical-imaging modalities to detect and accurately quantify molecular emissions from tissue. Here, by using a scanning external X-ray beam from a clinical linear accelerator to induce Cherenkov excitation of luminescence in tissue, we demonstrate in vivo mapping of the oxygenation of tumours at depths of several millimetres, with submillimetre resolution and nanomolar sensitivity. This was achieved by scanning thin sheets of the X-ray beam orthogonally to the emission-detection plane, and by detecting the signal via a time-gated CCD camera synchronized to the radiation pulse. We also show with experiments using phantoms and with simulations that the performance of Cherenkov-excited luminescence scanned imaging (CELSI) is limited by beam size, scan geometry, probe concentration, radiation dose and tissue depth. CELSI might provide the highest sensitivity and resolution in the optical imaging of molecular tracers in vivo.

L1-norm based nonlinear reconstruction improves quantitative accuracy of spectral diffuse optical tomography

Spectrally constrained diffuse optical tomography (SCDOT) is known to improve reconstruction in diffuse optical imaging; constraining the reconstruction by coupling the optical properties across multiple wavelengths suppresses artefacts in the resulting reconstructed images. In other work, L1-norm regularization has been shown to improve certain types of image reconstruction problems as its sparsity-promoting properties render it robust against noise and enable the preservation of edges in images, but because the L1-norm is non-differentiable, it is not always simple to implement. In this work, we show how to incorporate L1 regularization into SCDOT. Three popular algorithms for L1 regularization are assessed for application in SCDOT: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM), and fast iterative shrinkage-thresholding algorithm (FISTA). We introduce an objective procedure for determining the regularization parameter in these algorithms and compare their performance in simulated experiments, and in real data acquired from a tissue phantom. Our results show that L1 regularization consistently outperforms Tikhonov regularization in this application, particularly in the presence of noise.

Ultrasound-mediation of self-illuminating reporters improves imaging resolution in optically scattering media

In vivo imaging of self-illuminating bio-and chemiluminescent reporters is used to observe the physiology of small animals. However, strong light scattering by biological tissues results in poor spatial resolution of the optical imaging, which also degrades the quantitative accuracy. To overcome this challenging problem, focused ultrasound is used to modulate the light from the reporter at the ultrasound frequency. This produces an ultrasound switchable light 'beacon' that reduces the influence of light scattering in order to improve spatial resolution. The experimental results demonstrate that apart from light modulation at the ultrasound frequency (AC signal at 3.5 MHz), ultrasound also increases the DC intensity of the reporters. This is shown to be due to a temperature rise caused by insonification that was minimized to be within acceptable mammalian tissue safety thresholds by adjusting the duty cycle of the ultrasound. Line scans of bio-and chemiluminescent objects embedded within a scattering medium were obtained using ultrasound modulated (AC) and ultrasound enhanced (DC) signals. Lateral resolution is improved by a factor of 12 and 7 respectively, as compared to conventional CCD imaging. Two chemiluminescent sources separated by ~10 mm at ~20 mm deep inside a 50 mm thick chicken breast have been successfully resolved with an average signal-to-noise ratio of approximately 8-10 dB.

Bayesian sparse-based reconstruction in bioluminescence tomography improves localization accuracy and reduces computational time

Bioluminescence tomography (BLT) provides fundamental insight into biological processes in vivo. To fully realize its potential, it is important to develop image reconstruction algorithms that accurately visualize and quantify the bioluminescence signals taking advantage of limited boundary measurements. In this study, a new 2-step reconstruction method for BLT is developed by taking advantage of the sparse a priori information of the light emission using multispectral measurements. The first step infers a wavelength-dependent prior by using all multi-wavelength measurements. The second step reconstructs the source distribution based on this developed prior. Simulation, phantom and in vivo results were performed to assess and compare the accuracy and the computational efficiency of this algorithm with conventional sparsity-promoting BLT reconstruction algorithms, and results indicate that the position errors are reduced from a few millimeters down to submillimeter, and reconstruction time is reduced by 3 orders of magnitude in most cases, to just under a few seconds. The recovery of single objects and multiple (2 and 3) small objects is simulated, and the recovery of images of a mouse phantom and an experimental animal with an existing luminescent source in the abdomen is demonstrated. Matlab code is available at https://github.com/jinchaofeng/code/tree/master.

Multispectral, non-contact diffuse optical tomography of healthy human finger joints

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.

ESTRO ACROP: Technology for precision small animal radiotherapy research: Optimal use and challenges

Many radiotherapy research centers have recently installed novel research platforms enabling the investigation of the radiation response of tumors and normal tissues in small animal models, possibly in combination with other treatment modalities. Many more research institutes are expected to follow in the coming years. These novel platforms are capable of mimicking human radiotherapy more closely than older technology. To facilitate the optimal use of these novel integrated precision irradiators and various small animal imaging devices, and to maximize the impact of the associated research, the ESTRO committee on coordinating guidelines ACROP (Advisory Committee in Radiation Oncology Practice) has commissioned a report to review the state of the art of the technology used in this new field of research, and to issue recommendations. This report discusses the combination of precision irradiation systems, small animal imaging (CT, MRI, PET, SPECT, bioluminescence) systems, image registration, treatment planning, and data processing. It also provides guidelines for reporting on studies.

Incorporation of an ultrasound and model guided permissible region improves quantitative source recovery in bioluminescence tomography

Bioluminescence imaging has shown great potential for studying and monitoring disease progression in small animal pre-clinical imaging. However, absolute bioluminescence source recovery through tomographic multi-wavelength measurements is often hindered through the lack of quantitative accuracy and suffers from both poor localisation and quantitative recovery. In this work a method to incorporate a permissible region strategy through not only a priori location (permissible region) but also based on a model of light propagation and hence light sensitivity is developed and tested using both simulations and experimental data. Reconstructions on two different numerical models (a simple slab, and the digital version of a heterogeneous mouse) show an improvement of localisation and recovery of intensity (around 25% for the slab model and around 10% for the digital mouse model). This strategy is also used with experimental data from a phantom gel, which demonstrated an improved recovered tomographic image.

Development and Validation of a Sensor Prototype for Near-Infrared Imaging of the Newborn Brain

Imaging brain oxygenation is crucial for preventing brain lesions in preterm infants. Our aim is to build and validate a near-infrared optical tomography (NIROT) sensor for the head of neonates. This sensor, combined with an optoacoustic device, will enable quantitative monitoring of the structural and functional information of the brain. Since the head of preterm infants is small and fragile great care must be taken to produce a comfortable and compact device in which a sufficient number of light sources and detectors can be implemented. Here we demonstrate our first prototype. Heterogeneous silicone phantoms were produced to validate the prototype's data acquisition, data processing, and image reconstruction. Reconstructed optical properties agree well with the target values. The mechanical performance of the new NIROT sensor prototype confirms its suitability for the clinical application.

Time-resolved near infrared light propagation using frequency domain superposition

Time-resolved temporal point spread function (TPSF) measurement of near infrared spectroscopic (NIRS) data allows the estimation of absorption and reduced scattering properties of biological tissues. Such analysis requires an iterative calculation of the theoretical TPSF curve using mathematical and computational models of the domain being imaged which are computationally complex and expensive. In this work, an efficient methodology for representing the TPSF data using a superposition of cosines calculated in frequency domain is presented. The proposed method is outlined and tested on finite element realistic models of the human neck and head. Using an adult head model containing ~140k nodes, the TPSF calculation at each node for one source is accelerated from 3.11 s to 1.29 s within an error limit of ± 5% related to the time domain calculation method.

Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU

Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25  s/excitation source.

Effect of Shot Noise on Simultaneous Sensing in Frequency Division Multiplexed Diffuse Optical Tomographic Imaging Process

Diffuse optical tomography (DOT) has been studied for use in the detection of breast cancer, cerebral oxygenation, and cognitive brain signals. As optical imaging studies have increased significantly, acquiring imaging data in real time has become increasingly important. We have developed frequency-division multiplexing (FDM) DOT systems to analyze their performance with respect to acquisition time and imaging quality, in comparison with the conventional time-division multiplexing (TDM) DOT. A large tomographic area of a cylindrical phantom 60 mm in diameter could be successfully reconstructed using both TDM DOT and FDM DOT systems. In our experiment with 6 source-detector (S-D) pairs, the TDM DOT and FDM DOT systems required 6.18 and 1 s, respectively, to obtain a single tomographic data set. While the absorption coefficient of the reconstruction image was underestimated in the case of the FDM DOT, we experimentally confirmed that the abnormal region can be clearly distinguished from the background phantom using both methods.

Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

A multimodal micro-computed tomography (CT) and multi-spectral structured light imaging (SLI) system is introduced and systematically analyzed to test its feasibility to aid in margin delineation during breast conserving surgery (BCS). Phantom analysis of the micro-CT yielded a signal-to-noise ratio of 34, a contrast of 1.64, and a minimum detectable resolution of 240 μm for a 1.2 min scan. The SLI system, spanning wavelengths 490 nm to 800 nm and spatial frequencies up to 1.37 [Formula: see text], was evaluated with aqueous tissue simulating phantoms having variations in particle size distribution, scatter density, and blood volume fraction. The reduced scattering coefficient, [Formula: see text] and phase function parameter, γ, were accurately recovered over all wavelengths independent of blood volume fractions from 0% to 4%, assuming a flat sample geometry perpendicular to the imaging plane. The resolution of the optical system was tested with a step phantom, from which the modulation transfer function was calculated yielding a maximum resolution of 3.78 cycles per mm. The three dimensional spatial co-registration between the CT and optical imaging space was tested and shown to be accurate within 0.7 mm. A freshly resected breast specimen, with lobular carcinoma, fibrocystic disease, and adipose, was imaged with the system. The micro-CT provided visualization of the tumor mass and its spiculations, and SLI yielded superficial quantification of light scattering parameters for the malignant and benign tissue types. These results appear to be the first demonstration of SLI combined with standard medical tomography for imaging excised tumor specimens. While further investigations are needed to determine and test the spectral, spatial, and CT features required to classify tissue, this study demonstrates the ability of multimodal CT/SLI to quantify, visualize, and spatially navigate breast tumor specimens, which could potentially aid in the assessment of tumor margin status during BCS.

Addition of T2-guided optical tomography improves noncontrast breast magnetic resonance imaging diagnosis

Background

While dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is recognized as the most sensitive examination for breast cancer detection, it has a substantial false positive rate and gadolinium (Gd) contrast agents are not universally well tolerated. As a result, alternatives to diagnosing breast cancer based on endogenous contrast are of growing interest. In this study, endogenous near-infrared spectral tomography (NIRST) guided by T2 MRI was evaluated to explore whether the combined imaging modality, which does not require contrast injection or involve ionizing radiation, can achieve acceptable diagnostic performance.

Methods

Twenty-four subjects—16 with pathologically confirmed malignancy and 8 with benign abnormalities—were simultaneously imaged with MRI and NIRST prior to definitive pathological diagnosis. MRIs were evaluated independently by three breast radiologists blinded to the pathological results. Optical image reconstructions were constrained by grayscale values in the T2 MRI. MRI and NIRST images were used, alone and in combination, to estimate the diagnostic performance of the data. Outcomes were compared to DCE results.

Results

Sensitivity, specificity, accuracy, and area under the curve (AUC) of noncontrast MRI when combined with T2-guided NIRST were 94%, 100%, 96%, and 0.95, respectively, whereas these values were 94%, 63%, 88%, and 0.81 for DCE MRI alone, and 88%, 88%, 88%, and 0.94 when DCE-guided NIRST was added.

Conclusion

In this study, the overall accuracy of imaging diagnosis improved to 96% when T2-guided NIRST was added to noncontrast MRI alone, relative to 88% for DCE MRI, suggesting that similar or better diagnostic accuracy can be achieved without requiring a contrast agent.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0902-x) contains supplementary material, which is available to authorized users.

Fluorescent Affibody Molecule Administered In Vivo at a Microdose Level Labels EGFR Expressing Glioma Tumor Regions

Purpose

Fluorescence guidance in surgical oncology provides the potential to realize enhanced molecular tumor contrast with dedicated targeted tracers, potentially with a microdose injection level. For most glioma tumors, the blood brain barrier is compromised allowing some exogenous drug/molecule delivery and accumulation for imaging. The aberrant overexpression and/or activation of epidermal growth factor receptor (EGFR) is associated with many types of cancers, including glioblastoma, and so the use of a near-infrared (NIR) fluorescent molecule targeted to the EGFR receptor provides the potential for improving tumor contrast during surgery. Fluorescently labeled affibody molecule (ABY-029) has high EGFR affinity and high potential specificity with reasonably fast plasma clearance. In this study, ABY-29 was evaluated in glioma versus normal brain uptake from intravenous injection at a range of doses, down to a microdose injection level.

Procedure

Nude rats were inoculated with the U251 human glioma cell line in the brain. Tumors were allowed to grow for 3–4 weeks. ABY-029 fluorescence ex vivo imaging of brain slices was acquired at different time points (1–48 h) and varying injection doses from 25 to 122 μg/kg (from human protein microdose equivalent to five times microdose levels).

Results

The tumor was most clearly visualized at 1-h post-injection with 8- to 16-fold average contrast relative to normal brain. However, the tumor still could be identified after 48 h. In all cases, the ABY-029 fluorescence appeared to localize preferentially in EGFR-positive regions. Increasing the injected dose from a microdose level to five times, a microdose level increased the signal by 10-fold, and the contrast was from 8 to 16, showing that there was value in doses slightly higher than the microdose restriction. Normal tissue uptake was found to be affected by the tumor size, indicating that edema was a likely factor affecting the expected tumor to normal tissue contrast.

Conclusion

These results suggest that the NIR-labeled affibody molecules provide an excellent potential to increase surgical visualization of EGFR-positive tumor regions.