Reflectance-based determination of optical properties in highly attenuating tissue

AAPM Task Group Report 311: Guidance for performance evaluation of fluorescence-guided surgery systems

The last decade has seen a large growth in fluorescence-guided surgery (FGS) imaging and interventions. With the increasing number of clinical specialties implementing FGS, the range of systems with radically different physical designs, image processing approaches, and performance requirements is expanding. This variety of systems makes it nearly impossible to specify uniform performance goals, yet at the same time, utilization of different devices in new clinical procedures and trials indicates some need for common knowledge bases and a quality assessment paradigm to ensure that effective translation and use occurs. It is feasible to identify key fundamental image quality characteristics and corresponding objective test methods that should be determined such that there are consistent conventions across a variety of FGS devices. This report outlines test methods, tissue simulating phantoms and suggested guidelines, as well as personnel needs and professional knowledge bases that can be established. This report frames the issues with guidance and feedback from related societies and agencies having vested interest in the outcome, coming from an independent scientific group formed from academics and international federal agencies for the establishment of these professional guidelines.

Application of transfer learning for rapid calibration of spatially resolved diffuse reflectance probes for extraction of tissue optical properties

Significance

Treatment planning for light-based therapies including photodynamic therapy requires tissue optical property knowledge. This is recoverable with spatially resolved diffuse reflectance spectroscopy (DRS) but requires precise source-detector separation (SDS) determination and time-consuming simulations.

Aim

An artificial neural network (ANN) to map from DRS at multiple SDS to optical properties was created. This trained ANN was adapted to fiber-optic probes with varying SDS using transfer learning (TL).

Approach

An ANN mapping from measurements to Monte Carlo simulation to optical properties was created with one fiber-optic probe. A second probe with different SDS was used for TL algorithm creation. Data from a third were used to test this algorithm.

Results

The initial ANN recovered absorber concentration with RMSE = 0.29    μ M (7.5% mean error) and μ s ' at 665 nm (μ s , 665 ' ) with RMSE = 0.77    cm - 1 (2.5% mean error). For probe 2, TL significantly improved absorber concentration (0.38 versus 1.67    μ M RMSE, p = 0.0005 ) and μ ' s , 665 (0.71 versus 1.8    cm - 1 RMSE, p = 0.0005 ) recovery. A third probe also showed improved absorber (0.7 versus 4.1    μ M RMSE, p < 0.0001 ) and μ s , 665 ' (1.68 versus 2.08    cm - 1 RMSE, p = 0.2 ) recovery.

Conclusions

TL-based probe-to-probe calibration can rapidly adapt an ANN created for one probe to similar target probes, enabling accurate optical property recovery with the target probe.

Remote dose imaging from cherenkov light using spatially-resolved CT calibration in breast radiotherapy

PURPOSE

Imaging Cherenkov light during radiotherapy allows the visualization and recording of frame-by-frame relative maps of the dose being delivered to the tissue at each control point used throughout treatment, providing one of the most complete real-time means of treatment quality assurance. In non-turbid media, the intensity of Cherenkov light is linear with surface dose deposited, however the emission from patient tissue is well-known to be reduced by absorbing tissue components such as hemoglobin, fat, water and melanin, and diffused by the scattering components of tissue. Earlier studies have shown that bulk correction could be achieved by using the patient planning CT scan for attenuation correction.

METHODS

In this study, CT maps were used for correction of spatial variations in emissivity. Testing was completed on Cherenkov images from radiotherapy treatments of post-lumpectomy breast cancer patients (n = 13), combined with spatial renderings of the patient radiodensity (CT number) from their planning CT scan.

RESULTS

The correction technique was shown to provide a pixel-by-pixel correction that suppressed many of the inter- and intra-patient differences in the Cherenkov light emitted per unit dose. This correction was established from a calibration curve that correlated Cherenkov light intensity to surface-rendered CT number (R_6MV ² = 0.70 and R_10MV ² = 0.72). The corrected Cherenkov intensity per unit dose standard error was reduced by nearly half (from ∼30% to ∼17%).

CONCLUSIONS

This approach provides evidence that the planning CT scan can mitigate some of the tissue-specific attenuation in Cherenkov images, allowing them to be translated into near surface dose images. This article is protected by copyright. All rights reserved.

Machine learning for direct oxygen saturation and hemoglobin concentration assessment using diffuse reflectance spectroscopy

SIGNIFICANCE

Diffuse reflectance spectroscopy (DRS) is frequently used to assess oxygen saturation and hemoglobin concentration in living tissue. Methods solving the inverse problem may include time-consuming nonlinear optimization or artificial neural networks (ANN) determining the absorption coefficient one wavelength at a time.

AIM

To present an ANN-based method that directly outputs the oxygen saturation and the hemoglobin concentration using the shape of the measured spectra as input.

APPROACH

A probe-based DRS setup with dual source-detector separations in the visible wavelength range was used. ANNs were trained on spectra generated from a three-layer tissue model with oxygen saturation and hemoglobin concentration as target.

RESULTS

Modeled evaluation data with realistic measurement noise showed an absolute root-mean-square (RMS) deviation of 5.1% units for oxygen saturation estimation. The relative RMS deviation for hemoglobin concentration was 13%. This accuracy is at least twice as good as our previous nonlinear optimization method. On blood-intralipid phantoms, the RMS deviation from the oxygen saturation derived from partial oxygen pressure measurements was 5.3% and 1.6% in two separate measurement series. Results during brachial occlusion showed expected patterns.

CONCLUSIONS

The presented method, directly assessing oxygen saturation and hemoglobin concentration, is fast, accurate, and robust to noise.

Hybrid method to estimate two-layered superficial tissue optical properties from simulated data of diffuse reflectance spectroscopy

An iterative curve fitting method has been applied in both simulation [J. Biomed. Opt.17, 107003 (2012)JBOPFO1083-366810.1117/1.JBO.17.10.107003] and phantom [J. Biomed. Opt.19, 077002 (2014)JBOPFO1083-366810.1117/1.JBO.19.7.077002] studies to accurately extract optical properties and the top layer thickness of a two-layered superficial tissue model from diffuse reflectance spectroscopy (DRS) data. This paper describes a hybrid two-step parameter estimation procedure to address two main issues of the previous method, including (1) high computational intensity and (2) converging to local minima. The parameter estimation procedure contained a novel initial estimation step to obtain an initial guess, which was used by a subsequent iterative fitting step to optimize the parameter estimation. A lookup table was used in both steps to quickly obtain reflectance spectra and reduce computational intensity. On simulated DRS data, the proposed parameter estimation procedure achieved high estimation accuracy and a 95% reduction of computational time compared to previous studies. Furthermore, the proposed initial estimation step led to better convergence of the following fitting step. Strategies used in the proposed procedure could benefit both the modeling and experimental data processing of not only DRS but also related approaches such as near-infrared spectroscopy.

Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations

A robust modelling method was proposed to extract chromophore information in multi-layered skin tissue with spatially-resolved diffuse reflectance spectroscopy. Artificial neural network models trained with a pre-simulated database were first built to map geometric and optical parameters into diffuse reflectance spectra. Nine fitting parameters including chromophore concentrations and oxygen saturation were then determined by solving the inverse problem of fitting spectral measurements from three different parts of the skin. Compared to the Monte Carlo simulation accelerated by a graphics processing unit, the proposed modelling method not only reduced the computation time, but also achieved a better fitting performance.

Characterization of the Optical Properties of Turbid Media by Supervised Learning of Scattering Patterns

Fabricated tissue phantoms are instrumental in optical in-vitro investigations concerning cancer diagnosis, therapeutic applications, and drug efficacy tests. We present a simple non-invasive computational technique that, when coupled with experiments, has the potential for characterization of a wide range of biological tissues. The fundamental idea of our approach is to find a supervised learner that links the scattering pattern of a turbid sample to its thickness and scattering parameters. Once found, this supervised learner is employed in an inverse optimization problem for estimating the scattering parameters of a sample given its thickness and scattering pattern. Multi-response Gaussian processes are used for the supervised learning task and a simple setup is introduced to obtain the scattering pattern of a tissue sample. To increase the predictive power of the supervised learner, the scattering patterns are filtered, enriched by a regressor, and finally characterized with two parameters, namely, transmitted power and scaled Gaussian width. We computationally illustrate that our approach achieves errors of roughly 5% in predicting the scattering properties of many biological tissues. Our method has the potential to facilitate the characterization of tissues and fabrication of phantoms used for diagnostic and therapeutic purposes over a wide range of optical spectrum.

A Method for Medical Diagnosis Based on Optical Fluence Rate Distribution at Tissue Surface

Optical differentiation is a promising tool in biomedical diagnosis mainly because of its safety. The optical parameters’ values of biological tissues differ according to the histopathology of the tissue and hence could be used for differentiation. The optical fluence rate distribution on tissue boundaries depends on the optical parameters. So, providing image displays of such distributions can provide a visual means of biomedical diagnosis. In this work, an experimental setup was implemented to measure the spatially-resolved steady state diffuse reflectance and transmittance of native and coagulated chicken liver and native and boiled breast chicken skin at 635 and 808 nm wavelengths laser irradiation. With the measured values, the optical parameters of the samples were calculated in vitro using a combination of modified Kubelka-Munk model and Bouguer-Beer-Lambert law. The estimated optical parameters values were substituted in the diffusion equation to simulate the fluence rate at the tissue surface using the finite element method. Results were verified with Monte-Carlo simulation. The results obtained showed that the diffuse reflectance curves and fluence rate distribution images can provide discrimination tools between different tissue types and hence can be used for biomedical diagnosis.

Simulation of laser backscattering system for imaging of inhomogeneity/tumor in biological tissues

BACKGROUND AND OBJECTIVES

The optical characteristics of biological tissues vary in health and diseases. By analysis of photons scattering process by Monte Carlo simulation (MCS) the inhomogeneities in tissues are to be identified and their images reconstructed.

METHODS

Digital phantoms with goat's heart as a control tissue embedded with inhomogeneities adipose (high scattering) and spleen (high absorption) are simulated. The phantoms considered are - (a) simulation of the developed stage of inhomogeneity by inclusion of adipose and spleen tissues in control and (b) its onset stage by increasing the optical parameters by 10% at fixed locations in control tissue. These phantoms are scanned by simulated system, consisting of nine ports for photon injection and backscattered photons from each port are received by three ports located at 2, 4 and 6mm from the injecting port, placed in the direction of x-axis. By the data collected from the entire surface, by processing, three grey-scale images are constructed. For localization of inhomogeneities these images are scanned in terms of normalized backscattered intensity (NBI).

RESULTS

The images obtained by MCS with 1 million photons, with error minimized, at respective ports, show the presence of inhomogeneities at various depths, which is further supported by the increase or decrease in the NBI compared to that of control for adipose or spleen, respectively. The increase or decrease is more at first port compared to others. The inhomogeneities located at 2mm below the surface are better identified by the receiving port located at 2mm on the surface. The same applies to inhomogeneities located at 4 and 6mm, respectively.

CONCLUSION

The present simulated system not only shows the presence of inhomogeneties at various depths in tissue phantom but also presents their characteristics.

Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties

Glioma itself accounts for 80% of all malignant primary brain tumors, and glioblastoma multiforme (GBM) accounts for 55% of such tumors. Diffuse reflectance and fluorescence spectroscopy have the potential to discriminate healthy tissues from abnormal tissues and therefore are promising noninvasive methods for improving the accuracy of brain tissue resection. Optical properties were retrieved using an experimentally evaluated inverse solution. On average, the scattering coefficient is 2.4 times higher in GBM than in low grade glioma (LGG), and the absorption coefficient is 48% higher. In addition, the ratio of fluorescence to diffuse reflectance at the emission peak of 460 nm is 2.6 times higher for LGG while reflectance at 650 nm is 2.7 times higher for GBM. The results reported also show that the combination of diffuse reflectance and fluorescence spectroscopy could achieve sensitivity of 100% and specificity of 90% in discriminating GBM from LGG during ex vivo measurements of 22 sites from seven glioma specimens. Therefore, the current technique might be a promising tool for aiding neurosurgeons in determining the extent of surgical resection of glioma and, thus, improving intraoperative tumor identification for guiding surgical intervention.

Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime

We propose and objectively evaluate an inverse Monte Carlo model for estimation of absorption and reduced scattering coefficients and similarity parameter ? from spatially resolved reflectance (SRR) profiles in the subdiffusive regime. The similarity parameter ? carries additional information on the phase function that governs the angular properties of scattering in turbid media. The SRR profiles at five source-detector separations were acquired with an optical fiber probe. The inverse Monte Carlo model was based on a cost function that enabled robust estimation of optical properties from a few SRR measurements without a priori knowledge about spectral dependencies of the optical properties. Validation of the inverse Monte Carlo model was performed on synthetic datasets and measured SRR profiles of turbid phantoms comprising molecular dye and polystyrene microspheres. We observed that the additional similarity parameter ? substantially reduced the reflectance variability arising from the phase function properties and significantly improved the accuracy of the inverse Monte Carlo model. However, the observed improvement of the extended inverse Monte Carlo model was limited to reduced scattering coefficients exceeding ?15??cm?1, where the relative root-mean-square errors of the estimated optical properties were well within 10%.

In vivo spatial frequency domain spectroscopy of two layer media

Monitoring of tissue blood volume and local oxygen saturation can inform the assessment of tissue health, healing, and dysfunction. These quantities can be estimated from the contribution of oxyhemoglobin and deoxyhemoglobin to the absorption spectrum of the dermis. However, estimation of blood related absorption in skin can be confounded by the strong absorption of melanin in the epidermis and epidermal thickness and pigmentation varies with anatomic location, race, gender, and degree of disease progression. Therefore, a method is desired that decouples the effect of melanin absorption in the epidermis from blood absorption in the dermis for a large range of skin types and thicknesses. A previously developed inverse method based on a neural network forward model was applied to simulated spatial frequency domain reflectance of skin for multiple wavelengths in the near infrared. It is demonstrated that the optical thickness of the epidermis and absorption and reduced scattering coefficients of the dermis can be determined independently and with minimal coupling. Then, the same inverse method was applied to reflectance measurements from a tissue simulating phantom and in vivo human skin. Oxygen saturation and total hemoglobin concentrations were estimated from the volar forearms of weakly and strongly pigmented subjects using a standard homogeneous model and the present two layer model.

Optical imaging modalities for biomedical applications

Optical photographic imaging is a well known imaging method that has been successfully translated into biomedical applications such as microscopy and endoscopy. Although several advanced medical imaging modalities are used today to acquire anatomical, physiological, metabolic, and functional information from the human body, optical imaging modalities including optical coherence tomography, confocal microscopy, multiphoton microscopy, multispectral endoscopy, and diffuse reflectance imaging have recently emerged with significant potential for non-invasive, portable, and cost-effective imaging for biomedical applications spanning tissue, cellular, and molecular levels. This paper reviews methods for modeling the propagation of light photons in a biological medium, as well as optical imaging from organ to cellular levels using visible and near-infrared wavelengths for biomedical and clinical applications.

Joint derivation method for determining optical properties based on steady-state spatially resolved diffuse reflectance measurement at small source-detector separations and large reduced albedo range: theory and simulation

Accurate determination of the optical properties (the absorption coefficient μ(a) and the reduced scattering coefficient μ(s) (')) of tissues is very important in a variety of diagnostic and therapeutic procedures. Optical diffusion theory is frequently used as the forward model for describing the photon transfer in media with large reduced albedos (a(')) and in large source-detector separations (SDS). Several other methods (PN approximation, hybrid diffusion-P3 approximation) have also been published that describe photon transfer in media with low a(') or small SDSs. We studied the theoretical models for the steady-state spatially resolved diffuse reflectance measurement to accurately determine μ(a) and μ(s) (') at large a(') range but small SDSs. Instead of using a single model, a joint derivation method is proposed. The developed method uses one of the best aforementioned theoretical methods separately in five ranges of a(') determined from several forward models. In the region of small SDSs (the range between 0.4 and 8 mm) and large a(') range (between 0.5 and 0.99), the best theoretical derivation model was determined. The results indicate that the joint derivation method can improve the derivation accuracy and that a(') range can be determined by the steady-state spatially resolved diffuse reflectance measurement.

Diffuse reflectance spectroscopy as a tool to measure the absorption coefficient in skin: system calibration

An individualised laser skin treatment may enhance the treatment and reduces risks and side-effects. The optical properties (absorption and scattering coefficients) are important parameters in the propagation of laser light in skin tissue. The differences in the melanin content of different skin phototypes influence the absorption of the light. The absorption coefficient at the treatment wavelength for an individual can be determined by diffuse reflectance spectroscopy, using a probe containing seven fibres. Six of the fibres deliver the light to the measurement site and the central fibre collects the diffused reflected light. This is an in vivo technique, offering benefits for near-real-time results. Such a probe, with an effective wavelength band from 450 to 800 nm, was used to calibrate skin-simulating phantoms consisting of intralipid and ink. The calibration constants were used to calculate the absorption coefficients from the diffuse reflectance measurements of three volunteers (skin phototypes, II, IV and V) for sun-exposed and non-exposed areas on the arm.

Spatial frequency domain spectroscopy of two layer media

Monitoring of tissue blood volume and oxygen saturation using biomedical optics techniques has the potential to inform the assessment of tissue health, healing, and dysfunction. These quantities are typically estimated from the contribution of oxyhemoglobin and deoxyhemoglobin to the absorption spectrum of the dermis. However, estimation of blood related absorption in superficial tissue such as the skin can be confounded by the strong absorption of melanin in the epidermis. Furthermore, epidermal thickness and pigmentation varies with anatomic location, race, gender, and degree of disease progression. This study describes a technique for decoupling the effect of melanin absorption in the epidermis from blood absorption in the dermis for a large range of skin types and thicknesses. An artificial neural network was used to map input optical properties to spatial frequency domain diffuse reflectance of two layer media. Then, iterative fitting was used to determine the optical properties from simulated spatial frequency domain diffuse reflectance. Additionally, an artificial neural network was trained to directly map spatial frequency domain reflectance to sets of optical properties of a two layer medium, thus bypassing the need for iteration. In both cases, the optical thickness of the epidermis and absorption and reduced scattering coefficients of the dermis were determined independently. The accuracy and efficiency of the iterative fitting approach was compared with the direct neural network inversion.

Characteristics of stand-alone microlenses in fiber-based fluorescence imaging applications

Microlens-ended fibers, which have found tremendous interest in the recent past, find potential biomedical applications, in particular, in endoscopic imaging. The work presented in this paper focuses on the stand-alone microlenses along with custom-fabricated specialty optical fiber, such as imaging fiber, for probe imaging applications. Stand-alone self-aligned microlenses have been fabricated employing microcompression molding and then attached at the end facet of imaging fiber. A detailed characterization of the fabricated microlens is carried and it demonstrates appropriate focusing ability, high fluorescence collection efficiency and imaging ability for biomedical applications. The surface roughness of the microlens is found to be 25 nm with a minimum spot size of 38 μm. The probe imaging system is found to be able to image the fluorescence microspheres of 10 μm size. The collection efficiency of the fiber probe with lens found to be enhanced by three times approximately.

Rapid and accurate determination of tissue optical properties using least-squares support vector machines

Diffuse reflectance spectroscopy (DRS) has been extensively applied for the characterization of biological tissue, especially for dysplasia and cancer detection, by determination of the tissue optical properties. A major challenge in performing routine clinical diagnosis lies in the extraction of the relevant parameters, especially at high absorption levels typically observed in cancerous tissue. Here, we present a new least-squares support vector machine (LS-SVM) based regression algorithm for rapid and accurate determination of the absorption and scattering properties. Using physical tissue models, we demonstrate that the proposed method can be implemented more than two orders of magnitude faster than the state-of-the-art approaches while providing better prediction accuracy. Our results show that the proposed regression method has great potential for clinical applications including in tissue scanners for cancer margin assessment, where rapid quantification of optical properties is critical to the performance.

Study of laser-induced thermoelastic deformation of native and coagulated ex-vivo bovine liver tissues for estimating their optical and thermomechanical properties

Several studies have explored the potential of optoacoustic imaging for monitoring thermal therapies, yet the origin of the contrast in the images is not well understood. A technique is required to measure the changes in the optical and thermomechanical properties of tissues upon coagulation to better understand this contrast. An interferometric method is presented for measuring simultaneously the optical and thermomechanical properties of native and coagulated ex-vivo bovine tissue samples based on analysis of the surface displacement of irradiated samples. Surface displacements are measured after irradiation by short laser pulses at 750 nm. A 51% decrease in the optical attenuation depth is observed for coagulated liver samples compared to native samples. No significant differences in the Grüneisen coefficient are measured in the native and coagulated tissue samples. A mean value of 0.12 for the Grüneisen coefficient is measured for both native and coagulated liver tissues. The displacement profiles exhibit consistent differences between the two tissue types. To assess the changes in the sample mechanical properties, the experimental data also are compared to numerical solutions of the equation for thermoelastic deformation. The results demonstrate that differences in the tissue expansion dynamics arise from higher values of elastic modulus for coagulated liver samples compared to native ones.

Experimental and theoretical evaluation of a fiber-optic approach for optical property measurement in layered epithelial tissue

Improvements in measurement of epithelial tissue optical properties (OPs) in the ultraviolet and visible (UV-Vis) may lead to enhanced understanding of optical techniques for neoplasia detection. In this study, we investigated an approach based on fiber-optic measurement of reflectance to determine absorption and reduced scattering coefficients (μ(a) and μ(s)') in two-layer turbid media. Neural network inverse models were trained on simulation data for a wide variety of OP combinations (μ(a) = 1-22.5, μ(s)' = 5-42.5 cm(-1)). Experimental measurements of phantoms with top-layer thicknesses (D) ranging from 0.22 to 0.66 mm were performed at three UV-Vis wavelengths. OP estimation accuracy was calculated and compared to theoretical results. Mean prediction errors were strongly correlated with D and ranged widely, from 1.5 to 12.1 cm(-1). Theoretical analyses indicated the potential for improving accuracy with alternate probe geometries. Although numerous challenges remain, this initial experimental study of an unconstrained approach for fiber-optic-based OP determination in two-layer epithelial tissue indicates the potential to provide useful measurements.

A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo

We have a toolbox to quantify tissue optical properties that is composed of specialized fiberoptic probes for UV-visible diffuse reflectance spectroscopy and a fast, scalable inverse Monte Carlo (MC) model. In this paper, we assess the robustness of the toolbox for quantifying physiologically relevant parameters from turbid tissue-like media. In particular, we consider the effects of using different instruments, fiberoptic probes, and instrument-specific settings for a wide range of optical properties. Additionally, we test the quantitative accuracy of the inverse MC model for extracting the biologically relevant parameters of hemoglobin saturation and total hemoglobin concentration. We also test the effect of double-absorber phantoms (hemoglobin and crocin to model the absorption of hemoglobin and beta carotene, respectively, in the breast) for a range of absorption and scattering properties. We include an assessment on which reference phantom serves as the best calibration standard to enable accurate extraction of the absorption and scattering properties of the target sample. We found the best reference-target phantom combinations to be ones with similar scattering levels. The results from these phantom studies provide a set of guidelines for extracting optical parameters from clinical studies.

Frequency domain measurements on turbid media with strong absorption using the PN approximation

We have applied the frequency-domain technique to measurement of the optical properties of turbid media with strong absorption in the infinite medium limit. Absorption coefficients up to 2.3 cm(-1) for a modified scattering coefficient of 4.3 cm(-1) are studied, which corresponds to a reduced scattering albedo of 0.65. Low phase noise and good phase stability are required for these low albedo conditions. As the degree of absorption increases, the phase changes are reduced while amplitude changes increase. For this reason, correction of amplitude-phase cross talk is essential to achieve accurate measurements with strong absorption. Careful control of stray reflections is required to properly measure amplitude-phase cross talk. Because the diffusion approximation becomes less accurate, measurements are compared to calculations performed in the PN approximation, which is essentially an exact solution for the infinite medium limit. Agreement between theory and experiment is only obtained when correction for amplitude-phase cross talk is performed. These measurements can provide a good method for testing amplitude-phase cross talk.

In vivo fluorescence imaging: a personal perspective

In vivo fluorescence imaging with near-infrared (NIR) light holds enormous potential for a wide variety of molecular diagnostic and therapeutic applications. Because of its quantitative sensitivity, inherent biological safety, and relative ease of use (i.e., with respect to cost, time, mobility, and its familiarity to a diverse population of investigators), fluorescence-based imaging techniques are being increasingly utilized in small-animal research. Moreover, there is substantial interest in the translation of novel optical techniques into the clinic, where they will prospectively aid in noninvasive and quantitative screening, disease diagnosis, and post-treatment monitoring of patients. Effective deep-tissue fluorescence imaging requires the application of exogenous NIR-emissive contrast agents. Currently, available probes fall into two major categories: organic and inorganic NIR fluorophores (NIRFs). In the studies reviewed herein, we utilized polymersomes (50 nm to 50 microm diameter polymer vesicles) for the incorporation and delivery of large numbers of highly emissive oligo (porphyrin)-based, organic NIRFs.

Spectral determination of a two-parametric phase function for polydispersive scattering liquids

A method for determining a two-parametric Gegenbauer-kernel phase function that accurately describes the diffuse reflectance from a polydispersive scattering media at small source-detector separations (0.23 to 1.2 mm), is presented. The method involves spectral collimated transmission measurements, spatially resolved spectral diffuse reflectance (SRDR) measurements, and inverse Monte Carlo technique. Both absolute calibration (using a monodispersive polystyrene microsphere suspension) and relative calibration (eliminating differences between fibers) of SRDR spectra yielded comparable results. When applied to water dilutions of milk, simulated and measured spectra deviated less than 6.5% and 2.5% for the absolute and relative calibration case, respectively, even for the closest fiber separation. Corresponding values for milk including ink as an absorber, were 13.4% and 7.3%.

A strategy for quantitative spectral imaging of tissue absorption and scattering using light emitting diodes and photodiodes

A diffuse reflectance spectroscopy system was modified as a step towards miniaturization and spectral imaging of tissue absorption and scattering. The modified system uses a tunable source and an optical fiber for illumination and a photodiode in contact with tissue for detection. Compared to the previous system, it is smaller, less costly, and has comparable performance in extracting optical properties in tissue phantoms. Wavelength reduction simulations show the feasibility of replacing the source with LEDs to further decrease system size and cost. Simulated crosstalk analysis indicates that this evolving system can be multiplexed for spectral imaging in the future.

Confidence intervals on fit parameters derived from optical reflectance spectroscopy measurements

We validate a simple method for determining the confidence intervals on fitted parameters derived from modeling optical reflectance spectroscopy measurements using synthetic datasets. The method estimates the parameter confidence intervals as the square roots of the diagonal elements of the covariance matrix, obtained by multiplying the inverse of the second derivative matrix of chi2 with respect to its free parameters by chi2/v, with v the number of degrees of freedom. We show that this method yields correct confidence intervals as long as the model used to describe the data is correct. Imperfections in the fitting model introduces a bias in the fitted parameters that greatly exceeds the estimated confidence intervals. We investigate the use of various methods to identify and subsequently minimize the bias in the fitted parameters associated with incorrect modeling.

Use of Genetic Algorithms to Optimize Fiber Optic Probe Design for the Extraction of Tissue Optical Properties

This paper outlines a framework by which the optimal illumination/collection geometry can be identified for a particular biomedical application. In this paper, this framework was used to identify the optimal probe geometry for the accurate determination of tissue optical properties representative of that in the ultraviolet-visible (UV-VIS) spectral range. An optimal probe geometry was identified which consisted of a single illumination and two collection fibers, one of which is insensitive to changes in scattering properties, and the other is insensitive to changes in the attenuation coefficient. Using this probe geometry in conjunction with a neural network algorithm, the optical properties could be extracted with root-mean-square errors of 0.30 cm(-1) for the reduced scattering coefficient (tested range of 3-40 cm(-1)), and 0.41 cm(-1) for the absorption coefficient (tested range of 0-80 cm(-1)).

Targeting spectral signatures of progressively dysplastic stratified epithelia using angularly variable fiber geometry in reflectance Monte Carlo simulations

A key component of accurate spectroscopic-based cancer diagnostics is the ability to differentiate spectral variations resulting from epithelial tissue dysplasia. Such measurement may be enhanced by discretely probing the optical properties of the epithelial tissue where the morphological and biochemical features vary according to tissue depths. More precisely, layer-specific changes in tissue optical properties correlated to cellular dysplasia can be determined by conventional reflectance spectroscopy when it is coupled with angularly variable fiber geometry. Thus, this study addresses how angularly variable fiber geometry can resolve spatially specific spectral signatures of tissue pathology by interpreting and analyzing the reflectance spectra of increasingly dysplastic epithelial tissue in reflectance-mode Monte Carlo simulation. Specifically, by increasing the obliquity of the collection fibers from 0 to 40 deg in the direction facing toward the illumination fiber, the spectral sensitivity to tissue abnormalities in the epithelial layer is thereby improved, whereas orthogonal fibers are more sensitive to the changes in the stromal layer.

Comparison of spectral variation from spectroscopy to spectral imaging

Optical biopsy has been shown to discriminate between normal and diseased tissue with high sensitivity and specificity. Fiber-optic probe-based spectroscopy systems do not provide the necessary spatial information to guide therapy effectively, ultimately requiring a transition from probe-based spectroscopy to spectral imaging. The effect of such a transition on fluorescence and diffuse reflectance line shape is investigated. Inherent differences in spectral line shape between spectroscopy and imaging are characterized and many of these differences may be attributed to a shift in illumination-collection geometry between the two systems. Sensitivity of the line-shape disparity is characterized with respect to changes in sample absorption and scattering as well as to changes in various parameters of the fiber-optic probe design (e.g., fiber diameter, beam steering). Differences in spectral line shape are described in terms of the relative relationship between the light diffusion within the tissue and the distribution of source-detector separation distances for the probe-based and imaging illumination-collection geometries. Monte Carlo simulation is used to determine fiber configurations that minimize the line-shape disparity between the two systems. In conclusion, we predict that fiber-optic probe designs that mimic a spectral imaging geometry and spectral imaging systems designed to emulate a probe-based geometry will be difficult to implement, pointing toward a posteriori correction for illumination-collection geometry to reconcile imaging and probe-based spectral line shapes or independent evaluation of tissue discrimination accuracy for probe-based and spectral imaging systems.

Evaluation of a fiberoptic-based system for measurement of optical properties in highly attenuating turbid media

Background

Accurate measurements of the optical properties of biological tissue in the ultraviolet A and short visible wavelengths are needed to achieve a quantitative understanding of novel optical diagnostic devices. Currently, there is minimal information on optical property measurement approaches that are appropriate for in vivo measurements in highly absorbing and scattering tissues. We describe a novel fiberoptic-based reflectance system for measurement of optical properties in highly attenuating turbid media and provide an extensive in vitro evaluation of its accuracy. The influence of collecting reflectance at the illumination fiber on estimation accuracy is also investigated.

Methods

A neural network algorithm and reflectance distributions from Monte Carlo simulations were used to generate predictive models based on the two geometries. Absolute measurements of diffuse reflectance were enabled through calibration of the reflectance system. Spatially-resolved reflectance distributions were measured in tissue phantoms at 405 nm for absorption coefficients (μ_a) from 1 to 25 cm^-1 and reduced scattering coefficients (μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@) from 5 to 25 cm^-1. These data and predictive models were used to estimate the optical properties of tissue-simulating phantoms.

Results

By comparing predicted and known optical properties, the average errors for μ_a and μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ were found to be 3.0% and 4.6%, respectively, for a linear probe approach. When bifurcated probe data was included and samples with μ_a values less than 5 cm^-1 were excluded, predictive errors for μ_a and μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ were further reduced to 1.8% and 3.5%.

Conclusion

Improvements in system design have led to significant reductions in optical property estimation error. While the incorporation of a bifurcated illumination fiber shows promise for improving the accuracy of μ′s MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacuaH8oqBgaqbamaaBaaaleaacqqGZbWCaeqaaaaa@3007@ estimates, further study of this approach is needed to elucidate the source of discrepancies between measurements and simulation results at low μ_a values.

Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms

A flexible and fast Monte Carlo-based model of diffuse reflectance has been developed for the extraction of the absorption and scattering properties of turbid media, such as human tissues. This method is valid for a wide range of optical properties and is easily adaptable to existing probe geometries, provided a single phantom calibration measurement is made. A condensed Monte Carlo method was used to speed up the forward simulations. This model was validated by use of two sets of liquid-tissue phantoms containing Nigrosin or hemoglobin as absorbers and polystyrene spheres as scatterers. The phantoms had a wide range of absorption (0-20 cm(-1)) and reduced scattering coefficients (7-33 cm(-1)). Mie theory and a spectrophotometer were used to determine the absorption and reduced scattering coefficients of the phantoms. The diffuse reflectance spectra of the phantoms were measured over a wavelength range of 350-850 nm. It was found that optical properties could be extracted from the experimentally measured diffuse reflectance spectra with an average error of 3% or less for phantoms containing hemoglobin and 12% or less for phantoms containing Nigrosin.

Depth-sensitive reflectance measurements using obliquely oriented fiber probes

Computer simulation is used to facilitate the design of fiber-probe geometries that enable enhanced detection of optical signals arising from specific tissue depths. Obtaining understanding of the relationship between fiber-probe design and tissue interrogation is critical when developing strategies for optical detection of epithelial precancers that originate at known depths from the tissue surface. The accuracy of spectroscopic diagnostics may be enhanced by discretely probing the optical properties of epithelium and underlying stroma, within which the morphological and biochemical features vary as a function of depth. While previous studies have investigated controlling tissue-probing depth for fluorescence-based modalities, in this study we focus on the detection of reflected light scattered by tissue. We investigate how the depth of optical interrogation may be controlled through combinations of collection angles, source-detector separations, and numerical apertures. We find that increasing the obliquity of collection fibers at a given source-detector separation can effectively enhance the detection of superficially scattered signals. Fiber numerical aperture provides additional depth selectivity; however, the perturbations in sampling depth achieved through this means are modest relative to the changes generated by modifying the angle of collection and source-detection separation.

Use of the delta-P1 approximation for recovery of optical absorption, scattering, and asymmetry coefficients in turbid media

We introduce a robust method to recover optical absorption, reduced scattering, and single-scattering asymmetry coefficients (microa, micro's, g1) of infinite turbid media over a range of (micro's/microa) spanning 3 orders of magnitude. This is accomplished through the spatially resolved measurement of irradiance at source-detector separations spanning 0.25-8 transport mean free paths (l*). These measurements are rapidly processed by a multistaged nonlinear optimization algorithm in which the measured irradiances are compared with predictions given by the delta-P1 variant of the diffusion approximation to the Boltzmann transport equation. The ability of the delta-P1 model to accurately describe radiative transport within media of arbitrary albedo and on spatial scales comparable to l* is the key element enabling the separation of g1 from micro's.