Source-detector Separation Research Articles

Neural network-based optimization of sub-diffuse reflectance spectroscopy for improved parameter prediction and efficient data collection.

In this study, a general and systematical investigation of sub-diffuse reflectance spectroscopy is implemented. A Gegenbauer-kernel phase function-based Monte Carlo is adopted to describe photon transport more efficiently. To improve the computational efficiency and accuracy, two neural network algorithms, namely, back propagation neural network and radial basis function neural network are utilized to predict the absorption coefficient , reduced scattering coefficient and sub-diffusive quantifier , simultaneously, at multiple source-detector separations (SDS). The predicted results show that the three parameters can be predicated accurately by selecting five SDSs or above. Based on the simulation results, a four wavelength (520, 650, 785 and 830 nm) measurement system using five SDSs is designed by adopting phase-lock-in technique. Furtherly, the trained neural-network models are utilized to extract optical properties from the phantom and in vivo experimental data. The results verify the feasibility and effectiveness of our proposed system and methods in mucosal disease diagnosis.

Noninvasive optical monitoring of pulmonary embolism: a Monte Carlo study on visible Chinese human thoracic tissues.

In recent years, the incidence rate of pulmonary embolism (PE) has increased dramatically. Currently, the correct diagnosis rate of PE in China is relatively low, and the diagnosis error rate and missed diagnosis rate were as high as about 80%. The most standard method of PE detection is pulmonary artery digital subtraction angiography (DSA), but pulmonary artery DSA is an invasive examination, and patients can have certain risks and discomfort. Noninvasive monitoring of PE remains challenging in cardiovascular medicine. We attempt to study the light propagation in human thoracic tissues and explore the possibility of near-infrared spectroscopy (NIRS) in noninvasive detection of PE. In this study, by utilizing the Monte Carlo simulation method for voxelized media and the Visible Chinese Human dataset, we quantified and visualized the photon migration in human thoracic region. The influence of the development (three levels) of PE on the light migration was observed. Results showed that around 4.6% light fluence was absorbed by the pulmonary tissue. The maximum signal sensitivity distribution reached 0.073% at the 2.8- to 3.1-cm light source-detector separation. The normalized light intensity was significantly different among different PE levels and formed a linear relationship ( , ). The study found that photons could reach the pulmonary artery tissue, the light intensity was linearly related to the degrees of embolism, PE could be quantitatively diagnosed by NIRS. Meanwhile, the optimized distance in between the light source and detector, 2.8 to 3.1cm, was recommended to be used in future potential noninvasive optical diagnosis of PE.

Goniometric Examination of Diffuse Reflectance of a Skin Phantom in the Wavelength Range from 400 to 1600 nm

Since all of noninvasive optical monitors such as near-infrared spectroscopy are transcutaneous, it is important to consider the optical properties of the skin. The purpose of the present study was to clarify the effects of incident angle and source-detector separation (SDS) on the detection of components in the dermal layer. Here, we developed a novel skin phantom consisting of epidermal and dermal layers with optical properties ranging from 400 to 1600 nm. The phantom was simulated by only water, scatters and absorbers, without agarose, silicone or other materials. The phantom showed reflectance spectra very similar to those of actual human skin by the integrating sphere measurements. Furthermore, an optical system was assembled in which the incident angle could be changed from 20º to 80º and the SDS from 0 to 6 mm independently. For the wavelength range of 400 to 900 nm, the absorption spectrum of hemoglobin in the dermal layer was investigated to assess detectability. For the wavelength range of 900 to 1600 nm, the absorption spectrum was confirmed by including glucose in the dermal layer. The absorbance was calculated from the measured diffuse reflected light intensity. The optimal incident angle and SDS for optical measurements focused on the dermal layer were estimated by the signal-to-noise ratio (SNR). In the wavelength range of 400 to 900 nm, the absorption spectrum of hemoglobin with the highest SNR was obtained at an incident angle of 70° and SDS of 4 mm. In the wavelength range of 900 to 1600 nm, the absorption spectrum of glucose with the highest SNR was obtained at an incident angle of 20° and SDS of 0 mm. These conditions are expected to be optimal for transcutaneous measurement of biomolecules within the dermis using diffuse reflected light of wavelength range from 400 to 1600 nm.

Single Source-Detector Separation Approach to Calculate Tissue Oxygen Saturation Using Continuous Wave Near-Infrared Spectroscopy

Currently, common optical techniques to measure tissue oxygen saturation (StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) include time domain (TD), frequency domain (FD), and continuous wave (CW) near-infrared spectroscopy (NIRS). While TD- and FD-NIRS can provide absolute hemoglobin concentration, these systems are often complex and expensive. CW-NIRS, such as diffuse reflectance spectroscopy and spatially resolved spectroscopy (SRS), are simpler and more affordable, but they still require at least two source-detector separations. Here, we propose a single source-detector separation (SSDS) approach to measure StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> using reflected intensities from three wavelengths. The accuracy of the SSDS-based StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> measurement was verified using an optical simulation and an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-vivo</i> experiment. Simulated spatially dependent reflectance was generated using the Virtual Tissue Simulator on a 1-layer model, which has StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ranging from 0% to 100%. SSDS calculation yielded an equivalent StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> to the actual value (average error = 0.3% ± 0.5%). We then performed StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> measurements on seven healthy volunteers in the prefrontal cortex during a simulated hypercapnia test using a CW-NIRS device. This device consists of a light source and two photodetectors, which are 30 mm and 40 mm away from the light source. The cerebral oxygen saturation was calculated using both the SRS approach, which uses the reflected intensities at both separations, and the SSDS approach, which employs the reflected intensities at either 30 mm or 40 mm separation. The SRS-based StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> calculation was similar to the value calculated from the SSDS method (average difference = 5.0% ± 1.1%). This proposed method will help to advance the development of miniaturized technologies to monitor StO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> continuously.

Assessing the Sensitivity of Multi-Distance Hyperspectral NIRS to Changes in the Oxidation State of Cytochrome C Oxidase in the Brain.

Near-infrared spectroscopy (NIRS) measurements of tissue oxygen saturation (StO2) are frequently used during vascular and cardiac surgeries as a non-invasive means of assessing brain health; however, signal contamination from extracerebral tissues remains a concern. As an alternative, hyperspectral (hs)NIRS can be used to measure changes in the oxidation state of cytochrome c oxidase (ΔoxCCO), which provides greater sensitivity to the brain given its higher mitochondrial concentration versus the scalp. The purpose of this study was to evaluate the depth sensitivity of the oxCCO signal to changes occurring in the brain and extracerebral tissue components. The oxCCO assessment was conducted using multi-distance hsNIRS (source-detector separations = 1 and 3 cm), and metabolic changes were compared to changes in StO2. Ten participants were monitored using an in-house system combining hsNIRS and diffuse correlation spectroscopy (DCS). Data were acquired during carotid compression (CC) to reduce blood flow and hypercapnia to increase flow. Reducing blood flow by CC resulted in a significant decrease in oxCCO measured at rSD = 3 cm but not at 1 cm. In contrast, significant changes in StO2 were found at both distances. Hypercapnia caused significant increases in StO2 and oxCCO at rSD = 3 cm, but not at 1 cm. Extracerebral contamination resulted in elevated StO2 but not oxCCO after hypercapnia, which was significantly reduced by applying regression analysis. This study demonstrated that oxCCO was less sensitive to extracerebral signals than StO2.

Functional Time Domain Diffuse Correlation Spectroscopy.

Time-domain diffuse correlation spectroscopy (TD-DCS) offers a novel approach to high-spatial resolution functional brain imaging based on the direct quantification of cerebral blood flow (CBF) changes in response to neural activity. However, the signal-to-noise ratio (SNR) offered by previous TD-DCS instruments remains a challenge to achieving the high temporal resolution needed to resolve perfusion changes during functional measurements. Here we present a next-generation optimized functional TD-DCS system that combines a custom 1,064 nm pulse-shaped, quasi transform-limited, amplified laser source with a high-resolution time-tagging system and superconducting nanowire single-photon detectors (SNSPDs). System characterization and optimization was conducted on homogenous and two-layer intralipid phantoms before performing functional CBF measurements in six human subjects. By acquiring CBF signals at over 5 Hz for a late gate start time of the temporal point spread function (TPSF) at 15 mm source-detector separation, we demonstrate for the first time the measurement of blood flow responses to breath-holding and functional tasks using TD-DCS.

A Multilayer Monte Carlo Analysis of Optical Interactions in Reflectance Neck Photoplethysmography.

This paper presents a multilayer Monte Carlo model of a healthy human neck to investigate the light-tissue interaction during different perfusion states within its dermal layer. Whilst there is great interest in advancing wearable technologies for medical applications, and non-invasive techniques like photoplethysmography (PPG) have been studied in detail, research has focused on more conventional body regions like the finger, wrist, and ear. Alternatively, the neck could offer access to additional physiological parameters which other body regions are unsuitable for. The aim of this work was to investigate the effects of several factors that would influence the optimum design of a reflectance PPG sensor for the neck. These included the source-detector separation on the optical path, penetration depth, and light detection efficiency. The results were generated from a static multilayer model in a reflectance mode geometry at two wavelengths, 660 nm and 880 nm, containing different blood volume fractions with a fixed oxygen saturation. Simulations indicated that both wavelengths penetrated similar depths, where optimal source-detector separation should not exceed 3 mm or 2.4 mm, for red and infrared respectively. Within this range, light interrogates the dermal-fat boundary corresponding to the last neck tissue layer positively contributing to a neck PPG acquisition.

Age-related changes in diffuse optical tomography sensitivity profiles from childhood to adulthood.

.Significance: Diffuse optical tomography (DOT) uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the brain location that generates the hemodynamic signal require accurate descriptions of the DOT sensitivity to the underlying cortex. DOT sensitivity profiles are different in infants compared with adults. However, the descriptions of DOT sensitivity profiles from early childhood to adulthood are lacking despite the continuous head and brain development.Aim: We aim to investigate age-related differences in DOT sensitivity profiles in individuals aged from 2 to 34 years with narrow age ranges of 0.5 or 1 year.Approach: We implemented existing photon migration simulation methods and computed source–detector channel DOT sensitivity using age-appropriate, realistic head models.Results: DOT sensitivity profiles change systematically as a function of source–detector separation distance for all age groups. Children displayed distinctive DOT sensitivity profiles compared to older individuals, and the differences were enhanced at larger separation distances.Conclusions: The findings have important implications for the design of source–detector placement and image reconstruction. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone DOT data. Using age-inappropriate head models will have more negative impacts on estimation accuracy in younger children.

Influence of source-detector separation on diffuse correlation spectroscopy measurements of cerebral blood flow with a multilayered analytical model.

.Significance: Diffuse correlation spectroscopy (DCS) is an emerging noninvasive optical technology for bedside monitoring of cerebral blood flow. However, extracerebral hemodynamics can significantly influence DCS estimations of cerebral perfusion. Advanced analytical models can be used to remove the contribution of extracerebral hemodynamics; however, these models are highly sensitive to measurement noise. There is a need for an empirical determination of the optimal source–detector separation(s) (SDS) that improves the accuracy and reduces sensitivity to noise in the estimation of cerebral blood flow with these models.Aim: To determine the influence of SDS on solution uniqueness, measurement accuracy, and sensitivity to inaccuracies in model parameters when using the three-layer model to estimate cerebral blood flow with DCS.Approach: We performed a series of in silico simulations on samples spanning a wide range of physiologically-relevant layer optical properties, thicknesses, and flow. Data were simulated at SDS ranging from 0.5 to 3.0 cm using the three-layer solution to the correlation diffusion equation (with and without noise added) and using three-layer slab Monte Carlo simulations. We quantified the influence of SDS on uniqueness, accuracy, and sensitivity to inaccuracies in model parameters using the three-layer inverse model.Results: Two SDS are required to ensure a unique solution of cerebral blood flow index (CBFi). Combinations of 0.5/1.0/1.5 and 2.5 cm provide the optimal choice for balancing the depth penetration with signal-to-noise ratio to minimize the error in CBFi across a wide range of samples with varying optical properties, thicknesses, and dynamics.Conclusions: These results suggest that the choice of SDS is critical for minimizing the estimated error of cerebral blood flow when using the three-layer model to analyze DCS data.

Quantifying Earth's radiogenic heat budget

Earth's internal heat drives its dynamic engine, causing mantle convection, plate tectonics, and the geodynamo. These renewing and protective processes, which make Earth habitable, are fueled by primordial and radiogenic heat. For the past two decades, particle physicists have measured the flux of geoneutrinos, electron antineutrinos emitted during β− decay. These ghost-like particles provide a direct measure of the amount of heat producing elements (HPE: Th & U) in the Earth and in turn define the planet's absolute concentration of the refractory elements. The geoneutrino flux has contributions from the lithosphere and mantle. Detector sensitivity follows a 1/r2 (source detector separation distance) dependence. Accordingly, an accurate geologic model of the Near-Field Lithosphere (NFL, closest 500 km) surrounding each experiment is required to define the mantle's contribution. Because of its proximity to the detector and enrichment in HPEs, the local lithosphere contributes ∼50% of the signal and has the greatest effect on interpreting the mantle's signal.We re-analyzed the upper crustal compositional model used by Agostini et al. (2020) for the Borexino experiment. We documented the geology of the western Near-Field region as rich in potassic volcanism, including some centers within 50 km of the detector. In contrast, the Agostini study did not include these lithologies and used only a HPE-poor, carbonate-rich, model for upper crustal rocks in the surrounding ∼150 km of the Borexino experiment. Consequently, we report 3× higher U content for the local upper crust, which produces a 200% decrease in Earth's radiogenic heat budget, when compared to their study. Results from the KamLAND and Borexino geoneutrino experiments are at odds with one another and predict mantle compositional heterogeneity that is untenable. Combined analyses of the KamLAND and Borexino experiments using our revised local models strongly favor an Earth with ∼20 TW present-day total radiogenic power. The next generation of geoneutrino detectors (SNO+, counting; and JUNO, under construction) will better constrain the HPE budget of the Earth.

Evaluation of the robustness of cerebral oximetry to variations in skin pigmentation using a tissue-simulating phantom.

Clinical studies have demonstrated that epidermal pigmentation level can affect cerebral oximetry measurements. To evaluate the robustness of these devices, we have developed a phantom-based test method that includes an epidermis-simulating layer with several melanin concentrations and a 3D-printed cerebrovascular module. Measurements were performed with neonatal, pediatric and adult sensors from two commercial oximeters, where neonatal probes had shorter source-detector separation distances. Referenced blood oxygenation levels ranged from 30 to 90%. Cerebral oximeter outputs exhibited a consistent decrease in saturation level with simulated melanin content; this effect was greatest at low saturation levels, producing a change of up to 15%. Dependence on pigmentation was strongest in a neonatal sensor, possibly due to its high reflectivity. Overall, our findings indicate that a modular channel-array phantom approach can provide a practical tool for assessing the impact of skin pigmentation on cerebral oximeter performance and that modifications to algorithms and/or instrumentation may be needed to mitigate pigmentation bias.

Development of a Monte Carlo-wave model to simulate time domain diffuse correlation spectroscopy measurements from first principles.

.Significance: Diffuse correlation spectroscopy (DCS) is an optical technique that measures blood flow non-invasively and continuously. The time-domain (TD) variant of DCS, namely, TD-DCS has demonstrated a potential to improve brain depth sensitivity and to distinguish superficial from deeper blood flow by utilizing pulsed laser sources and a gating strategy to select photons with different pathlengths within the scattering tissue using a single source–detector separation. A quantitative tool to predict the performance of TD-DCS that can be compared with traditional continuous wave DCS (CW-DCS) currently does not exist but is crucial to provide guidance for the continued development and application of these DCS systems.Aims: We aim to establish a model to simulate TD-DCS measurements from first principles, which enables analysis of the impact of measurement noise that can be utilized to quantify the performance for any particular TD-DCS system and measurement geometry.Approach: We have integrated the Monte Carlo simulation describing photon scattering in biological tissue with the wave model that calculates the speckle intensity fluctuations due to tissue dynamics to simulate TD-DCS measurements from first principles.Results: Our model is capable of simulating photon counts received at the detector as a function of time for both CW-DCS and TD-DCS measurements. The effects of the laser coherence, instrument response function, detector gate delay, gate width, intrinsic noise arising from speckle statistics, and shot noise are incorporated in the model. We have demonstrated the ability of our model to simulate TD-DCS measurements under different conditions, and the use of our model to compare the performance of TD-DCS and CW-DCS under a few typical measurement conditions.Conclusion: We have established a Monte Carlo-Wave model that is capable of simulating CW-DCS and TD-DCS measurements from first principles. In our exploration of the parameter space, we could not find realistic measurement conditions under which TD-DCS outperformed CW-DCS. However, the parameter space for the optimization of the contrast to noise ratio of TD-DCS is large and complex, so our results do not imply that TD-DCS cannot indeed outperform CW-DCS under different conditions. We made our code available publicly for others in the field to find use cases favorable to TD-DCS. TD-DCS also provides a promising way to measure deep brain tissue dynamics using a short source–detector separation, which will benefit the development of technologies including high density DCS systems and image reconstruction using a limited number of source–detector pairs.

Reconstruction of optical coefficients in turbid media using time-resolved reflectance and calibration-free instrument response functions.

Measurements of time-resolved reflectance from a homogenous turbid medium can be employed to retrieve the absolute values of its optical transport coefficients. However, the uncertainty in the temporal shift of the experimentally determined instrument response function (IRF) with respect to the real system response can lead to errors in optical property reconstructions. Instrument noise and measurement of the IRF in a reflectance geometry can exacerbate these errors. Here, we examine three reconstruction approaches that avoid requiring direct measurements of photon launch times. They work by (a) fitting relative shapes of the reflectance profile with a pre-determined constraint on the scattering coefficient, (b) calibrating launch-time differences via a reference sample, and (c) freely fitting for the launch-time difference within the inverse problem. Analysis methods that can place a tight bound on the scattering coefficient can produce errors within 5-15% for both absorption and scattering at source-detector separations of 10 and 15 mm. Including the time-shift in the fitting procedure also recovered optical coefficients to under 20% but showed large crosstalk between extracted scattering and absorption coefficients. We find that the uncertainty in the temporal shift greatly impacts the reconstructed reduced scattering coefficient compared to absorption.

Probing depth in diffuse reflectance spectroscopy of biotissues: a Monte Carlo study

Diffuse reflectance spectroscopy (DRS) is an optical imaging modality based on extraction of tissue structural and functional information from back-reflectance spectra. In this paper we analyze the spectral dependence of DRS probing depth for different source-detector separations (SDSs) in the range of 1.5–7.0 mm by means of Monte Carlo simulations. The simulated spectra are employed to analyze the effect of the selected spectral range on the accuracy of oxygen saturation (StO2) reconstruction for different parameters of skin. It is shown that the probing depth varies in the range of 1–4 mm depending on SDS and tissue parameters, and in the hemoglobin absorption band for particular medium configuration it demonstrates a 2-fold decrease as compared to the neighboring spectral ranges. Comparison of different spectral ranges for StO2 reconstruction from the measured spectra at different SDSs demonstrated that the range of 480–600 nm and the full range of 480–900 nm benefit over near infrared (NIR) range (700–900 nm) in the reconstruction accuracy. The 480–600 nm range provides the best reconstruction accuracy for low blood volume content, while the full range of 480–900 nm provides better accuracy for larger blood volume content. The comprehensive study of the spectral dependency of probing depth in DSR for SDSs in the range of 1.5–7.0 mm based on MC simulations for multi-layered skin model depending on skin layers properties and numerical aperture combined with analysis of StO2 reconstruction accuracy was conducted for the first time to our knowledge.

Development of a miniaturized and modular probe for fNIRS instrument.

Functional near-infrared spectroscopy (fNIRS) is a non-invasive and promising method for continuously monitoring hemodynamic and metabolic changes in tissues. However, the existing fNIRS equipment uses optical fiber, which is bulky, expensive, and time-consuming. We present a miniaturized, modular, novel silicon photomultiplier (SiPM) detector and develop a fNIRS instrument aimed at investigating the cerebral hemodynamic response for patients with epilepsy. Light emitting probe is a circle with a diameter of 5mm. Independent and modular light source and detector are more flexible in placement. The system can be expanded to high-density measurement with 16 light sources, 16 detectors, and 52 channels. The sampling rate of each channel is 25Hz. Instrument performance was evaluated using brain tissue phantom and in vivo experiments. High signal-to-noise ratio (60dB) in source detector separation (SDS) of 30mm, good stability (0.1%), noise equivalent power (0.89 pW), and system drift (0.56%) were achieved in the phantom experiment. Forearm blood-flow occlusion experiments were performed on the forearm of three healthy volunteers to demonstrate the ability to track rapid hemodynamic changes. Breath holding experiments on the forehead of healthy volunteers demonstrated the system can well detect brain function activity. The computer software was developed to display the original light signal intensity and the concentration changes of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (HbR) in real time. This system paves the way for our further diagnosis of epilepsy.

Evaluation of fNIRS signal components elicited by cognitive and hypercapnic stimuli

Functional near infrared spectroscopy (fNIRS) measurements are confounded by signal components originating from multiple physiological causes, whose activities may vary temporally and spatially (across tissue layers, and regions of the cortex). Furthermore, the stimuli can induce evoked effects, which may lead to over or underestimation of the actual effect of interest. Here, we conducted a temporal, spectral, and spatial analysis of fNIRS signals collected during cognitive and hypercapnic stimuli to characterize effects of functional versus systemic responses. We utilized wavelet analysis to discriminate physiological causes and employed long and short source-detector separation (SDS) channels to differentiate tissue layers. Multi-channel measures were analyzed further to distinguish hemispheric differences. The results highlight cardiac, respiratory, myogenic, and very low frequency (VLF) activities within fNIRS signals. Regardless of stimuli, activity within the VLF band had the largest contribution to the overall signal. The systemic activities dominated the measurements from the short SDS channels during cognitive stimulus, but not hypercapnic stimulus. Importantly, results indicate that characteristics of fNIRS signals vary with type of the stimuli administered as cognitive stimulus elicited variable responses between hemispheres in VLF band and task-evoked temporal effect in VLF, myogenic and respiratory bands, while hypercapnic stimulus induced a global response across both hemispheres.

A novel spatially resolved interactance spectroscopy system to estimate degree of red coloration in red-fleshed apple

Reliable information about degree of red coloration in fruit flesh is essential for grading and sorting of red-fleshed apples. We propose a spatially resolved interactance spectroscopy approach as a new rapid and non-destructive technique to estimate degree of red coloration in the flesh of a red-fleshed apple cultivar ‘Kurenainoyume’. A novel measurement system was developed to obtain spatially resolved interactance spectra (190–1070 nm) for apple fruits at eight different light source-detector separation (SDS) distances on fruit surface. Anthocyanins in apple were extracted using a solvent extraction technique, and their contents were quantified with a spectrophotometer. Partial least squares (PLS) regression analyses were performed to develop estimation models for anthocyanin content from spatially resolved interactance spectra. Results showed that the PLS models based on interactance spectra obtained at different SDS distances achieved different predictive accuracy. Further, the system demonstrated the possibility to detect the degree of red coloration in the flesh at specific depths by identifying an optimal SDS distance. This might contribute to provide a detailed profile of the red coloration (anthocyanins) that is unevenly distributed among different depths of the flesh. This new approach may be potentially applied to grading and sorting systems for red-fleshed apples in fruit industry.

Optical property recovery with spatially-resolved diffuse reflectance at short source-detector separations using a compact fiber-optic probe.

We describe a compact fiber-optic probe (2 mm outside diameter) that utilizes spatially-resolved diffuse reflectance for tissue optical property recovery. Validation was performed in phantoms containing Intralipid 20% as scatterer, and methylene blue (MB), MnTPPS, and/or India ink as absorbers. Over a range of conditions, the reduced scattering coefficient was recovered with a root mean square error (RMSE) of 0.86-2.7 cm-1 (average error = 3.8%). MB concentration was recovered with RMSE = 0.26-0.52 µM (average error = 15.0%), which did not vary with inclusion of MnTPPS (p=0.65). This system will be utilized to determine optical properties in human abscesses, in order to generate treatment plans for photodynamic therapy.

Brain Light-Tissue Interaction Modelling: Towards a non-invasive sensor for Traumatic Brain Injury.

Traumatic brain injury (TBI) is one of the leading causes of death worldwide, yet there is no systematic approach to monitor TBI non-invasively. The main motivation of this work is to create new knowledge relating to light brain interaction using a Monte Carlo Model, which could aid in the development of non-invasive optical sensors for the continuous assessment of TBI. To this aim, a multilayer model tissue-model of adult human head was developed and explored at the near-infrared optical wavelength. Investigation reveals that maximum light (40-50%) is absorbed in the skull and the minimum light is absorbed in the subarachnoid space (0-1%). It was found that the absorbance of light decreases with increasing source-detector separation up to 3cm where light travels through the subarachnoid space, after which the absorbance increases with the increasing separation. Such information will be helpful towards the modelling of neurocritical brain tissue followed by the sensor development.

Time-domain NIRS system based on supercontinuum light source and multi-wavelength detection: validation for tissue oxygenation studies.

We present and validate a multi-wavelength time-domain near-infrared spectroscopy (TD-NIRS) system that avoids switching wavelengths and instead exploits the full capability of a supercontinuum light source by emitting and acquiring signals for the whole chosen range of wavelengths. The system was designed for muscle and brain oxygenation monitoring in a clinical environment. A pulsed supercontinuum laser emits broadband light and each of two detection modules acquires the distributions of times of flight of photons (DTOFs) for 16 spectral channels (used width 12.5 nm / channel), providing a total of 32 DTOFs at up to 3 Hz. Two emitting fibers and two detection fiber bundles allow simultaneous measurements at two positions on the tissue or at two source-detector separations. Three established protocols (BIP, MEDPHOT, and nEUROPt) were used to quantitatively assess the system’s performance, including linearity, coupling, accuracy, and depth sensitivity. Measurements were performed on 32 homogeneous phantoms and two inhomogeneous phantoms (solid and liquid). Furthermore, measurements on two blood-lipid phantoms with a varied amount of blood and Intralipid provide the strongest validation for accurate tissue oximetry. The retrieved hemoglobin concentrations and oxygen saturation match well with the reference values that were obtained using a commercially available NIRS system (OxiplexTS) and a blood gas analyzer (ABL90 FLEX), except a discrepancy occurs for the lowest amount of Intralipid. In-vivo measurements on the forearm of three healthy volunteers during arterial (250 mmHg) and venous (60 mmHg) cuff occlusions provide an example of tissue monitoring during the expected hemodynamic changes that follow previously well-described physiologies. All results, including quantitative parameters, can be compared to other systems that report similar tests. Overall, the presented TD-NIRS system has an exemplary performance evaluated with state-of-the-art performance assessment methods.