SignificanceShuntodynia is patient reported pain at the site of the implanted ventriculoperitoneal (VP) shunt. Pediatric hydrocephalus requiring shunt placement is a chronic and prevalent standard of care treatment and requires lifetime management. Shuntodynia is a subjective measure of shunt dysfunction. Quantitative, white-light tissue spectroscopy could be used to objectively identify this condition in the clinic.AimPediatric subjects were recruited for optical sensing during routine clinical follow-up visits, post-VP shunt implantations. Acquired optical signals were translated into skin-hemodynamic signatures and were compared between subjects that reported shuntodynia versus those that did not.ApproachDiffuse reflectance spectroscopy (DRS) measurements were collected between 450 and 700 nm using a single-channel fiber-optical probe from (N=35) patients. Multiple reflectance spectra were obtained by the attending physician from regions both proximal and distal to the VP shunt sites and from a matched contralateral site for each subject. Acquired reflectance spectra were processed quantitatively into functional tissue optical endpoints. A two-way, repeated measures analysis of variance was used to assess whether and which of the optical variables were statistically separable, across subjects with shuntodynia versus those without.ResultsAnalyses indicated that intrapatient differences in vascular oxygen saturation measured between shunt sites relative to that obtained at the scar or contralateral sites was significantly lower in the pain group. We also find that the total hemoglobin concentrations at the shunt site were lowest relative to the other sites for subjects reporting pain. These findings suggest that shuntodynia pain arises in the scalp tissue around the implanted shunts and may be caused due to hypoxia and inflammation.ConclusionsOptically derived hemodynamic variables were statistically significantly different in subjects presenting with shuntodynia relative to those without. DRS could provide a viable mode in routine bedside monitoring of subjects with VP shunts for clinical management and assessment of shuntodynia.
UV-excited autofluorescence spectroscopy can provide information on the metabolic status of cellular systems, but applications to turbid media such as tissues can be complicated by the presence of multiple scattering, intrinsic absorption, and background fluorescence. Our broader aim is the sensing of cellular-level metabolic status in tissue based the real time assessment of autofluorescence signals using spectral phasor analysis. Previously, we analyzed metabolic responses in yeast cells embedded in turbid media containing significant background fluorescence from collagen. Not only were changes in metabolism detectable under these conditions, but responses associated with NADH- and NADPH-linked metabolisms could also be distinguished. NADH and NADPH are metabolic co-factors having nearly identical excited-state emission but playing significant and distinct roles in cellular metabolism. Here, we extend the phasor analysis approach by sensing metabolic responses of yeast cells embedded in turbid media containing hemoglobin as a source of optical absorption. A metabolic response is induced by chemical perturbation, e.g., by adding cyanide to inhibit cellular respiration or by adding peroxide to induce oxidative stress. We demonstrate that phasor analysis is a versatile tool, e.g., by showing that spectral response associated with changes to cellular metabolism versus optical absorption are spectrally distinct and cannot be accounted for using a two-component spectral model.
Time-resolved diffuse optical spectroscopy (TRDOS) provides a method for directly and independently determining the optical transport coefficients of turbid media. A multispectral, gated TRDOS system was built using a supercontinuum laser source and a fast single photon avalanche photodiode (SPAD) for detection. Electronic time-gating of the SPAD allowed for detection of time-gated photon distributions, and showed an increase of nearly 80x in dynamic range relative to ungated detection. TRDOS measurements using both ungated and gated detection schemes on two-layer tissue mimicking phantoms were acquired. The distribution of time-of-flight (DTOF) of photons was measured from a two-layered tissue simulating phantom at multiple source-detector separations and wavelengths. Measured DTOFs were matched to predictions from diffusion-theory (DT) for two-layered media after numerical convolution with measured instrument response functions. We show a dependence of the two-layer DT model on the input values of the upper layer thickness and refractive indices. It was found that both the upper layer thickness and refractive index parameters must well-determined for DT predictions to match measurements in two-layer media.
Diffuse reflectance spectroscopy (DRS) is a well-established technology for quantitative, non-invasive, and rapid measurement of tissue hemodynamics. We used DRS scans collected between 450-700 nm using a single-channel fiber optical probe in hydrocephalus pediatric patients with implanted shunts to investigate whether idiopathic pain experienced at the shunt site was identifiable in hemodynamic signatures from measurements. The relationship between the presence of shunt-related pain by were examined using localized DRS measurements using an optical probe with short source-detector separation. DRS scans were collected at seven different sites around the implanted shunt and from a matched contralateral site, from subjects during routine clinical visits. Reflectance data were processed using an inverse Monte Carlo model to translate each DRS spectrum into the wavelength averaged scattering coefficient, the total hemoglobin concentration, and vascular blood oxygen saturation. DRS variables from acquired measurements were examined across patient groups using statistical t-tests. Preliminary results indicate a reduced hemoglobin saturation for subjects presenting with shuntodynia and need to be examined in greater detail to identify whether these optical signals indicate early-development of pressure injuries in tissues.
Our work applies neutral networks to solving forward and inverse problems in diffuse reflectance spectroscopy. Firstly, a neural network forward model is trained with Monte Carlo data so as to predict diffuse reflectance from given optical parameters. Secondly, an inverse model based on the neural network forward model is built to solve for optical parameters from diffuse reflectance, modified from the traditional Monte Carlo-based inverse model. Validation of our inverse model on experimentally measured phantom data is investigated.
Diffuse Reflectance Spectroscopy (DRS) uses light in the visible-near-infrared (NIR) spectrum for sub-surface sensing within optically turbid media such as biological tissues. Commonly, DRS based tissue sensing uses fiber-optic probes in direct contact with tissue, creating illumination and detection spots on the tissue sample at a fixed source-detector separation (SDS). Such a geometry eliminates Fresnel reflections from being collected by the detector and only samples multiply back-scattered light from the medium. Although fibers provide a straightforward means to implement DRS, physical contact of the fiber with tissue may perturb optical properties and, in several cases, may not be feasible. Here, we develop a non-contact, broadband optical system to acquire DRS measurements from a flat medium at a working distance of 2-3 cm. We characterize the beam profiles and geometry of our system and investigate the impact of varying working distance. Preliminary results show that the non-contact DRS system detects signatures of oxygenated hemoglobin in DRS measurements from human tissue and was sensitive to changes in spectral absorption in phantoms.
The reduced pyridine-nucleotides nicotinamide adenine dinucleotide (NADH) and nicotinamide adenine dinucleotide phosphate (NADPH) are ubiquitous metabolic cofactors playing significant, distinct roles in cellular metabolism. NADH and NADPH are primarily involved in cellular respiration and in maintaining antioxidant defenses, respectively, however their nearly identical fluorescence properties (the abbreviation NAD(P)H denotes this uncertainty) pose a challenge when interpreting and distinguishing autofluorescence signals. For sensing in turbid media such as tissue, additional challenges include the presence of multiple scattering, intrinsic absorption, and background fluorescence. Here, we assess an approach for distinguishing cellular-respiration and oxidative-stress responses when sensed in turbid media. Spectral phasor analysis, an analytical approach originally developed for the rapid segmentation of hyperspectral images, has been used on UV-excited autofluorescence for the real time monitoring of cellular NAD(P)H conformation. We showed previously that the spectral response to chemicals affecting NADH and NADPH pathways, e.g., in response to cyanide and hydrogen peroxide, does not follow two-component behavior and so could be distinguished in cell-only preparations. Here, we demonstrate pathway-level sensing in turbid media by monitoring the metabolic response of yeast cells embedded in a source for background emission. The distinguishability of UV-excited autofluorescence spectra to chemical perturbations affecting cellular respiration and oxidative stress are compared with previously reported cell-only observations.
We propose to use neural networks to learn and replace Monte Carlo (MC) simulations. Our neural networks are not only convenient to use but also are shown to be extremely time-saving compared to MC simulations with comparable accuracy. Furthermore, we employ the machine learning method called transfer learning to perform calibration between MC simulated diffuse reflectance and that measured by Diffuse Reflectance Spectroscopy (DRS). The transfer learning model is able to predict DRS measured diffuse reflectance spectrum by training the model using a small amount of DRS data.
Near-infrared spectroscopy has been widely employed in biophotonics to study and quantify the optical properties of biological tissues. Unlike steady-state approaches, time-resolved spectroscopic techniques enable optical absorption and scattering properties of the medium to be separated, allowing for quantitation of depth-dependent absolute tissue optical properties. However, robust analysis of time-resolved signals requires careful consideration of calibration techniques and computational models. Here, we consider the effect of the time window employed when fitting a diffusion theory model to Monte-Carlo simulations. Next, we describe the impact of the temporal position of the instrument response function (IRF) in recovery of the optical properties. Finally, we discuss a technique to analyze time-resolved measurements without knowledge of the timescale of the IRF or the time-resolved measurement by fitting the relative shape of the photons’ distribution time-of-flight (DTOF).
An empirical approach to estimate the reduced scattering (μs’) and absorption (μa) coefficients of a turbid medium from time-resolved diffuse reflectance detected at multiple source-detector separations (SDS) is described. The dependence of the temporal point spread function (TPSF) on the medium’s optical properties has been previously well studied. Here, we exploit these findings by using the difference in photon arrival-times obtained from a pair of SDS at the (a) peak intensity and (b) longer-time trailing edge of the TPSF to estimate the transport coefficients. This difference may have little dependence on the instrument response functions (IRF). Consequently, real-time quantitation is possible since the method does not depend on non-linear fitting of measured reflectance and/or deconvolving the IRF. The approach uses Monte Carlo simulations to directly translate the difference in arrival times of the temporal reflectance profiles at multiple SDS into the medium’s optical properties. Here, we show that a small range in the optical properties could be defined using a pair of time differences in the TPSF.
Autofluorescence spectroscopy can provide information on the metabolic status of cellular systems, but extensions of these techniques to turbid media such as tissues is complicated by the presence of multiple scattering, background fluorescence, and intrinsic absorption. Phasor analysis is a class of analytical approaches for the real-time assessment of emission signals that could be used to decipher cellular-level metabolic status of tissues. Spectral phasor analysis was originally developed for the rapid segmentation of hyperspectral images and has since been used for monitoring cellular NAD(P)H conformation from UV-excited cellular autofluorescence. Specifically, we showed previously that chemically induced autofluorescence responses in Saccharomyces cerevisiae (baker’s yeast) suspensions could not be accounted for using the two-component free vs. protein-bound model for conformation. Rather, by considering a series of physically similar and dissimilar chemicals acting on multiple metabolic pathways, we showed that responses affecting different pathways, e.g., involving cellular respiration versus oxidative stress, could be distinguished. Here, we seek to extend this pathway-level interpretation to the sensing of cellular metabolism in tissues by monitoring the cyanide-induced metabolic response of yeast cells embedded in media containing 9-cyanoanthracene or collagen as sources of background emission. Despite the similarity between autofluorescence and background spectra, we observe spectral behavior consistent with the discrimination of the metabolic response from the background emission. Performance over specifically selected noncontinuous spectral bands to reject chromophore absorption is also assessed.
Integrating spheres (IS) facilitate accurate measurements of the total reflectance and transmittance of turbid media, which can be used to determine optical properties of the sample measured. Translation of measurements into optical properties are achieved using theoretical photon migration models. A widely used approach with IS measurements is to use the inverse adding-doubling (IAD) method that utilizes the forward adding-doubling method, which is a rigorous numerical forward solver of the 1-D radiative transport equation. In order to experimentally satisfy the 1-D nature of the theoretical model, samples must be large enough to be modeled as infinite in extent along axes normal to incident beam. Here, we explore constraint on the required sample dimensions by comparing errors in modeled reflectance and transmittance between the adding-doubling and Monte Carlo simulations. We compare both the forward predictions and the inverse extraction of the optical properties for samples with varying dimensions, sample optical properties and beam profiles. Lateral losses (loss of light from sides of the sample) were observed to be significant when illumination beam diameters become comparable to sample length. Errors of 2-3% were noted between MC predictions vs. the adding-doubling estimates for reflectance and transmittance and these translated to 5-30% errors in IAD estimated optical absorption while the extracted scattering coefficients remained unaffected and had errors < 2%, relative to simulated values. We find that when the incident beam had diameter less than 80% of the sample length, the estimated optical properties of the medium were well extracted using the IAD.
Laser speckle contrast imaging (LSCI) is a wide-field, optical technique capable of assessing changes in flow rates of scattering fluids. In biomedical applications, LSCI has been used to quantify changes of blood perfusion in various tissue. One limitation of LSCI is its limited depth sensitivity- it can only sense blood flow in superficial layers of tissue. The goal of this study was to experimentally investigate the depth-sensitivity of LSCI for detecting fluid flow embedded in a turbid optical phantom. LSCI was used to image a flow channel buried by the scattering medium at incremental depths ranging from 0 mm to 2.4 mm. The flow measurements were successively repeated using two illumination wavelengths, 633 nm and 785 nm. Images were captured with and without flow present through the phantom for each wavelength and analyzed to develop a flow-sensitivity parameter. This provided a metric of LSCI’s ability for detecting flow as a function of channel depth. At a depth of 1.5 mm, the flow sensitivity decreased by 80% with the 633 nm illumination and 65% for the 785 nm illumination relative to a depth of 0 mm. The results demonstrate that the flow sensitivity of the 785 nm source diminished at a slower rate as the buried depth was increased than the sensitivity of the 633 nm source. This study suggests that the flow depth and illumination wavelength should be considered while using LSCI.
Diffuse Correlation Spectroscopy (DCS) is a non-invasive and easy to operate device for determining tissue perfusion in clinical applications. DCS detects temporal fluctuations in the diffusely reflected intensity from an incident coherent laser source and relates these fluctuations theoretically to calculate the mean-square displacement of moving light scattering particles. The objective of these studies was to experimentally investigate DCS signals from a turbid optical phantom containing a flow channel. By changing the depth of the flow channel (from the surface of the phantom) we investigated the depth sensitivity of DCS with changes in the optical properties of the phantom media containing the flow channel. Two sets of experiments were conducted: in the first task the sensitivity of the depth dependence of DCS measurements was investigated. The second task was to then determine how varying optical properties, within ranges measured in real tissue, altered the DCS measurements in regions of zero, low, and high relative flow rates. Concentrations of scattering and absorbing particles in the phantom surrounding the flowing solution were varied and the resulting changes in the autocorrelation curves were monitored. We report here that varying the concentrations of the absorbing and scattering particles in the phantom impacted the DCS autocorrelation decay measurements. Thus, it will be important to have robust estimates of the surrounding tissue optical properties to extract absolute flow-rates using DCS.
In tissue optics, it is important to measure the wavelength-dependent scattering, absorption and anisotropy coefficients of tissues to describe interactions of light with such turbid media. Here, we use the inverse adding-doubling (IAD) technique coupled to measurements acquired using an integrating sphere (IS). The IS system provides a method to acquire highly accurate measurements for the total reflectance and transmittance for thin turbid samples. The IAD is an iterative technique that uses a numerical solver to radiative transport capable of fitting a set of measured reflectance and transmittance values and thereby yield optical absorption and reduced scattering coefficients of thin samples. We test the validity and performance of the IS/IAD system by obtaining measurements on a set of liquid phantoms prepared with controlled absorption and scattering properties. We explore sources of errors and discuss how the the accuracy these techniques may be improved. We demonstrate that the IAD/IS technique allows the accurate recovery of chromophore spectral properties.
In reconstructive surgery, the ability to detect blood flow interruptions to grafted tissue represents a critical step in preventing postsurgical complications. We have developed and pilot tested a compact, fiber-based device that combines two complimentary modalities—diffuse correlation spectroscopy (DCS) and diffuse reflectance spectroscopy—to quantitatively monitor blood perfusion. We present a proof-of-concept study on an in vivo porcine model (n=8). With a controllable arterial blood flow supply, occlusion studies (n=4) were performed on surgically isolated free flaps while the device simultaneously monitored blood flow through the supplying artery as well as flap perfusion from three orientations: the distal side of the flap and two transdermal channels. Further studies featuring long-term monitoring, arterial failure simulations, and venous failure simulations were performed on flaps that had undergone an anastomosis procedure (n=4). Additionally, benchtop verification of the DCS system was performed on liquid flow phantoms. Data revealed relationships between diffuse optical measures and state of occlusion as well as the ability to detect arterial and venous compromise. The compact construction of the device, along with its noninvasive and quantitative nature, would make this technology suitable for clinical translation.
Video Photoplethysmography (VPPG) is a numerical technique to process standard RGB video data of exposed human skin and extracting the heart-rate (HR) from the skin areas. Being a non-contact technique, VPPG has the potential to provide estimates of subject’s heart-rate, respiratory rate, and even the heart rate variability of human subjects with potential applications ranging from infant monitors, remote healthcare and psychological experiments, particularly given the non-contact and sensor-free nature of the technique. Though several previous studies have reported successful correlations in HR obtained using VPPG algorithms to HR measured using the gold-standard electrocardiograph, others have reported that these correlations are dependent on controlling for duration of the video-data analyzed, subject motion, and ambient lighting. Here, we investigate the ability of two commonly used VPPG-algorithms in extraction of human heart-rates under three different laboratory conditions. We compare the VPPG HR values extracted across these three sets of experiments to the gold-standard values acquired by using an electrocardiogram or a commercially available pulseoximeter. The two VPPG-algorithms were applied with and without KLT-facial feature tracking and detection algorithms from the Computer Vision MATLAB® toolbox. Results indicate that VPPG based numerical approaches have the ability to provide robust estimates of subject HR values and are relatively insensitive to the devices used to record the video data. However, they are highly sensitive to conditions of video acquisition including subject motion, the location, size and averaging techniques applied to regions-of-interest as well as to the number of video frames used for data processing.
It is essential to monitor tissue perfusion during and after reconstructive surgery, as restricted blood flow can result in graft failures. Current clinical procedures are insufficient to monitor tissue perfusion, as they are intermittent and often subjective. To address this unmet clinical need, a compact, low-cost, multimodal diffuse correlation spectroscopy and diffuse reflectance spectroscopy system was developed. We verified system performance via tissue phantoms and experimental protocols for rigorous bench testing. Quantitative data analysis methods were employed and tested to enable the extraction of tissue perfusion parameters. This design verification study assures data integrity in future in vivo studies.
In reconstructive surgery, impeded blood flow in microvascular free flaps due to a compromise in arterial or venous patency secondary to blood clots or vessel spasms can rapidly result in flap failures. Thus, the ability to detect changes in microvascular free flaps is critical. In this paper, we report progress on in vivo pre-clinical testing of a compact, multimodal, fiber-based diffuse correlation and reflectance spectroscopy system designed to quantitatively monitor tissue perfusion in a porcine model’s surgically-grafted free flap. We also describe the device’s sensitivity to incremental blood flow changes and discuss the prospects for continuous perfusion monitoring in future clinical translational studies.
In reconstructive surgery, tissue perfusion/vessel patency is critical to the success of microvascular free tissue flaps. Early detection of flap failure secondary to compromise of vascular perfusion would significantly increase the chances of flap salvage. We have developed a compact, clinically-compatible monitoring system to enable automated, minimally-invasive, continuous, and quantitative assessment of flap viability/perfusion. We tested the system’s continuous monitoring capability during extended non-recovery surgery using an in vivo porcine free flap model. Initial results indicated that the system could assess flap viability/perfusion in a quantitative and continuous manner. With proven performance, the compact form constructed with cost-effective components would make this system suitable for clinical translation.
Reactive hyperemia refers to an increase of blood flow in tissue post release of an occlusion in the local vasculature. Measuring the temporal response of reactive hyperemia, post-occlusion in patients has the potential to shed information about microvascular diseases such as systemic sclerosis and diabetes. Laser speckle contrast imaging (LSCI) is an imaging technique capable of sensing superficial blood flow in tissue which can be used to quantitatively assess reactive hyperemia. Here, we employ LSCI using coherent sources in the blue, green and red wavelengths to evaluate reactive hyperemia in healthy human volunteers. Blood flow in the forearms of subjects were measured using LSCI to assess the time-course of reactive hyperemia that was triggered by a pressure cuff applied to the biceps of the subjects. Raw speckle images were acquired and processed to yield blood-flow parameters from a region of interest before, during and after application of occlusion. Reactive hyperemia was quantified via two measures - (1) by calculating the difference between the peak LSCI flow during the hyperemia and baseline flow, and (2) by measuring the amount of time that elapsed between the release of the occlusion and peak flow. These measurements were acquired in three healthy human participants, under the three laser wavelengths employed. The studies shed light on the utility of in vivo LSCI-based flow sensing for non-invasive assessment of reactive hyperemia responses and how they varied with the choice source wavelength influences the measured parameters.
Radiation therapy is often used as the preferred clinical treatment for control of localized head and neck cancer.
However, during the course of treatment (6-8 weeks), feedback about functional and/or physiological changes within
impacted tissue are not obtained, given the onerous financial and/or logistical burdens of scheduling MRI, PET or CT
scans. Diffuse optical sensing is well suited to address this problem since the instrumentation can be made low-cost and
portable while still being able to non-invasively provide information about vascular oxygenation in vivo. Here we report
results from studies that employed an optical fiber-based portable diffuse reflectance spectroscopy (DRS) system to
longitudinally monitor changes in tumor vasculature within two head and neck cancer cell lines (SCC-15 and FaDu)
xenografted in the flanks of nude mice, in two separate experiments. Once the tumor volumes were 100mm3, 67% of
animals received localized (electron beam) radiation therapy in five fractions (8Gy/day, for 5 days) while 33% of the
animals served as controls. DRS measurements were obtained from each animal on each day of treatment and then for
two weeks post-treatment. Reflectance spectra were parametrized to extract total hemoglobin concentration and blood
oxygen-saturation and the resulting time-trends of optical parameters appear to be dissimilar for the two cell-lines.
These findings are also compared to previous animal experiments (using the FaDu line) that were irradiated using a
photon beam radiotherapy protocol. These results and implications for the use of fiber-based DRS measurements made
at local (irradiated) tumor site as a basis for identifying early radiotherapy-response are presented and discussed.
Repair of soft tissue defects of the lips as seen in complex maxillofacial injuries, requires pre-vascularized multi-tissue
composite grafts. Protocols for fabrication of human ex-vivo produced oral mucosal equivalents (EVPOME) composed
of epithelial cells and a dermal equivalent are available to create prelaminated flaps for grafting in patients. However, invivo
assessment of neovascularization of the buried prelaminated flaps remains clinically challenging. Here, we use
diffuse reflectance spectroscopy (DRS) and diffuse correlation spectroscopy (DCS) to non-invasively quantify
longitudinal changes in the vessel density and blood-flow within EVPOME grafts implanted in the backs of SCID mice
and subsequently to determine the utility of these optical techniques for assessing vascularization of implanted grafts. 20
animals were implanted with EVPOME grafts (1x1x0.05 cm3) in their backs. DRS and DCS measurements were
obtained from each animal both atop the graft site and far away from the graft site, at one week post-implantation, each
week, for four consecutive weeks. DRS spectra were analyzed using an inverse Monte Carlo model to extract tissue
absorption and scattering coefficients, which were then used to extract blood flow information by fitting the
experimental DCS traces. There were clear differences in the mean optical parameters (averaged across all mice) at the
graft site vs. the off-site measurements. Both the total hemoglobin concentration (from DRS) and the relative blood flow
(from DCS) peaked at week 3 at the graft site and declined to the off-site values by week 4. The optical parameters
remained relatively constant throughout 4 weeks for the off-site measurements.
Extraction of optical absorption and scattering coefficients from experimental measurements of spatially and/or
spectrally resolved diffuse reflectance typically requires that measurements made on unknown samples be calibrated
using those made on reference phantoms with well characterized optical properties. Here, we derive the optical
scattering and absorption spectra of a solid homogenous resin-phantom using two analytical methods: radially resolved
diffuse reflectance (RRDR) based fitting and spectrally resolved diffuse reflectance (SRDR) based fitting. Radially
resolved data was acquired using a fabricated probe holder which connected one source fiber to 7 detector fibers with
distances ranging between 1.65 to 12.5 mm. Each detector fiber was connected to a spectrometer and spectra ranging
450 to 800 nm were measured when a broadband halogen lamp was used as the source. Diffusion theory based, as well
as scaled Monte Carlo based models were used to fit the spectrally and radially resolved reflectance (on a per
wavelength basis) to derive the absorption and scattering spectra of the solid phantom. To assess the accuracy of these
derived absorption and scattering properties, they were used as reference measurements to reconstruct the optical
properties of liquid phantoms, with well-determined absorption and scattering. Reference optical properties determined
using the SRDR methods were more accurate in reconstructing the optical properties in liquid phantoms. However,
RRDR methods are useful to obtain a spectral profile of the absorption coefficient of an unknown media, for subsequent
analyses using SRDR.
An inverse Monte Carlo based model has been developed to extract intrinsic fluorescence from turbid media. The goal of this work was to experimentally validate the model to extract intrinsic fluorescence of three biologically meaningful fluorophores related to metabolism from turbid media containing absorbers and scatterers. Experimental studies were first carried out on tissue-mimicking phantoms that contained individual fluorophores and their combinations, across multiple absorption, scattering, and fluorophore concentrations. The model was then tested in a murine tumor model to determine both the kinetics of fluorophore uptake as well as overall tissue fluorophore concentration through extraction of the intrinsic fluorescence of an exogenous contrast agent that reports on glucose uptake. Results show the model can be used to recover the true intrinsic fluorescence spectrum with high accuracy (R2 = 0.988) as well as accurately compute fluorophore concentration in both single and multiple fluorophores phantoms when appropriate calibration standards are available. In the murine tumor, the model-corrected intrinsic fluorescence could be used to differentiate drug dose injections between different groups. A strong linear correlation was observed between the extracted intrinsic fluorescence intensity and injected drug dose, compared with the distorted turbid tissue fluorescence.
Noninvasive and longitudinal monitoring of tumor oxygenation status using quantitative diffuse reflectance spectroscopy is used to test whether a final treatment outcome could be estimated from early optical signatures in a murine model of head and neck cancer when treated with radiation. Implanted tumors in the flank of 23 nude mice are exposed to 39 Gy of radiation, while 11 animals exposed to sham irradiation serve as controls. Diffuse optical reflectance is measured from the tumors at baseline (prior to irradiation) and then serially until 17 days posttreatment. The fastest and greatest increase in baseline-corrected blood oxygen saturation levels are observed from the animals that show complete tumor regression with no recurrence 90 days postirradiation, relative to both untreated and treated animals with local recurrences. These increases in saturation are observed starting 5 days posttreatment and last up to 17 days posttreatment. This preclinical study demonstrates that diffuse reflectance spectroscopy could provide a practical method far more effective than the growth delay assay to prognosticate treatment outcome in solid tumors and may hold significant translational promise
Monte Carlo (MC) simulations are considered the "gold standard" for mathematical description of photon transport in
tissue, but they can require large computation times. Therefore, it is important to develop simple and efficient methods
for accelerating MC simulations, especially when a large "library" of related simulations is needed. A semi-analytical
method involving MC simulations and a path-integral (PI) based scaling technique generated time-resolved reflectance
curves from layered tissue models. First, a zero-absorption MC simulation was run for a tissue model with fixed
scattering properties in each layer. Then, a closed-form expression for the average classical path of a photon in tissue
was used to determine the percentage of time that the photon spent in each layer, to create a weighted Beer-Lambert
factor to scale the time-resolved reflectance of the simulated
zero-absorption tissue model. This method is a unique
alternative to other scaling techniques in that it does not require the path length or number of collisions of each photon to
be stored during the initial simulation. Effects of various layer thicknesses and absorption and scattering coefficients on
the accuracy of the method will be discussed.
KEYWORDS: 3D modeling, Data modeling, Monte Carlo methods, Absorption, Spherical lenses, Optical properties, Bioluminescence, Photon transport, Diffusion, 3D image processing
A three dimensional (3D) photon transport model has been developed based on the frequency domain simplified
spherical harmonics approximation (SPN) to the Radiative Transport Equation. Based on preliminary Monte Carlo
studies, it is shown that for problems exhibiting strong absorption, the solutions using the 7th order SPN model (N = 7) are
significantly more accurate than those from a standard Diffusion (SP1) based solver. This advance is of particular
interest in the field of bioluminescent imaging where the peak emission of light emitting molecular markers are closer to
the visible range (500 - 650 nm) corresponding to strong absorption due to hemoglobin.
Photon transport in complex biological tissues is most accurately predicted via Monte Carlo (MC)
modeling methods, which often require lengthy computation times. In this report, a semi-analytical
technique (henceforth referred to as PI-scaling) was derived that combines MC simulation, absorption
scaling, and path integrals (PI) to rapidly reconstruct time-resolved reflectance from the surface of bilayered
epithelial tissue models. Comparisons to forward MC simulations indicated that the PI−scaling
method was accurate to better than 10% for tissue models where the optical properties of the
top layer did not greatly influence the time-resolved reflectance. Employing such a method should
provide a novel solution to the first step of the problem of rapid simulation of time-resolved
reflectance of photons in layered tissues.
Tissue engineered constructs can be employed to graft wounds or replace diseased tissue. Non-invasive methods are
required to assess cellular viability in these constructs both pre- and post-implantation into patients. In this study, Monte
Carlo simulations and fluorescence experiments were executed on ex vivo produced oral mucosa equivalent (EVPOME)
constructs to investigate the fluorescence emitted at 355 nm excitation from these constructs. Both simulations and
experiments indicated the need to investigate alternative excitation wavelengths in order to increase the cellular
fluorescence from these constructs, while decreasing contributions from extra-cellular fluorophores.
Numerical simulations of time-resolved light transport in inhomogeneous tissues reveal quantitative, 3D-distributions of excitation and fluorescent light. Visualizations generated can assist the optimization of endoscopy-compatible fiber-optic probes and optical imaging systems.
Time-Resolved Laser-Induced Fluorescence Spectroscopy (tr-LIFS) offers the potential for intra-operative diagnosis of primary brain tumors. However, both the intrinsic properties of endogenous fluorophores and the optical properties of brain tissue could affect the fluorescence measurements from brain. Scattering has been demonstrated to increase, for instance, detected lifetimes by 10-20% in media less scattering than the brain. The overall goal of this study is to investigate experimentally and computationally how optical properties of distinct types of brain tissue (normal porcine white and gray matter) affect the propagation of the excitation pulse and fluorescent transients and the detected fluorescence lifetime. A time-domain tr-LIFS apparatus (fast digitizer and gated detection) was employed to measure the propagation of ultra-short pulsed light through brain specimens (1-2.5-mm source-detector separation; 0.100-mm increment). A Monte Carlo model for semi-infinite turbid media was used to simulate time-resolved light propagation for arbitrary source-detector fiber geometries and optical fiber specifications; and to record spatially- and temporally resolved information. We determined a good correlation between experimental and computational results. Our findings provide means for quantification of time-resolved fluorescence spectra from healthy and diseased brain tissue.
This investigation explores the effect of index of refraction, as an optical property, on light transport through optically turbid media. We describe a model of light propagation that incorporates the influence of refractive index mismatch at boundaries within a domain. We measure light transmission through turbid cylindrical phantoms with different distributions of refractive index. These distributions approximate the heterogeneous, layered nature of biological tissue. Finite element method model calculations of diffuse transmittance through these phantoms show good agreement with the trends observed experimentally. We see that phase measurements of light that propagates through approximately 90 (mm) of scatter-dominated media may vary by 10 degrees depending upon the values of refractive index of the medium. Amplitude measurements are not as sensitive to this parameter as phase. Model calculations of diffuse reflectance from a semi-infinite slab geometry with different layers also shows good agreement with Monte Carlo simulations. We conclude that incorporating refractive index into light transport models may be worthwhile. Applying such a model in tomographic image reconstruction may improve the estimation of optical properties of biological tissues.
KEYWORDS: Tissues, Monte Carlo methods, Luminescence, Time resolved spectroscopy, Absorption, Quantum efficiency, Collagen, Colon, Pathology, In vivo imaging
We present a computational code capable of simulating time-resolved fluorescence emission from multi-layered biological tissues, and apply this code to model tissue fluorescence emission data acquired in vivo during clinical endoscopy. The code for multi-layered media is based on a Monte Carlo model we developed previously to simulate time-resolved fluorescence propagation in a semi-infinite turbid medium. Here, the code is applied to simulate data acquired from measurements on tissues in the lower gastrointestinal tract. Clinical data were obtained in vivo during endoscopy using a portable time-resolved fluorescence spectrometer employing a single fiber-optic probe for excitation and detection. Tissue was modeled as a two-layered medium consisting of a mucosal layer of finite thickness above a sub-mucosal layer. The emitted fluorescence was considered as arising from mucosal epithelial cells, due to the presence of nicotinamide dinucleotide as the constituent fluorophore (lifetime τ = 1.5 ns), and from sub-mucosal structural proteins (collagen, lifetime τ = 5.2 ns). Simulations modeled changes in tissue pathology as a function of independently changing the mucosal layer thickness, the fluorophore absorption coefficients and the fluorescence quantum yields. It was observed that the emanating fluorescence from the mucosal layer changes by ~50-60% with these changes resulting in appreciable differences of ~2 ns in the average lifetimes. These simulations indicate that it may be possible to quantify the fluorescence observed from tissue based on both biochemical and histological criteria. The simulations may also be used to provide a useful method for designing and testing the efficacies of different fiber-probe geometries.
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