Coupled forward-adjoint Monte Carlo simulation of spatial-angular light fields to determine optical sensitivity in turbid media (original) (raw)
Related papers
Journal of Biomedical Optics, 2007
The use of perturbation and differential Monte Carlo ͑pMC/ dMC͒ methods in conjunction with nonlinear optimization algorithms were proposed recently as a means to solve inverse photon migration problems in regionwise heterogeneous turbid media. We demonstrate the application of pMC/dMC methods for the recovery of optical properties in a two-layer extended epithelial tissue model from experimental measurements of spatially resolved diffuse reflectance. The results demonstrate that pMC/dMC methods provide a rapid and accurate approach to solve two-region inverse photon migration problems in the transport regime, that is, on spatial scales smaller than a transport mean free path and in media where optical scattering need not dominate absorption. The pMC/dMC approach is found to be effective over a broad range of absorption ͑50 to 400%͒ and scattering ͑70 to 130%͒ perturbations. The recovery of optical properties from spatially resolved diffuse reflectance measurements is examined for different sets of source-detector separation. These results provide some guidance for the design of compact fiber-based probes to determine and isolate optical properties from both epithelial and stromal layers of superficial tissues.
Monte Carlo methods for light propagation in biological tissues
Mathematical biosciences, 2015
Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis-Hastings algorithm. The resulting estimating methods are then compared to the so-called Wang-Prahl (or Wang) method. Finally, the formal representation allows to derive a non-linear optimization algorithm close to Levenberg-Marquardt that is used for the estimation of the scattering and absorption coefficients of the tissue from measurements.
2007
We introduce a novel Monte Carlo method for the analysis of optical probe design that couples a forward and an adjoint simulation to produce spatial-angular maps of the detected light field within the tissue under investigation. Our technique utilizes a generalized reciprocity theory for radiative transport and is often more efficient than using either forward or adjoint simulations alone. For a given probe configuration, the technique produces rigorous, transport-based estimates of the joint probability that photons will both visit any specified target subvolume and be detected. This approach enables the entire tissue region to be subdivided into a collection of target subvolumes to provide a phase-space map of joint probabilities. Such maps are generated efficiently using only one forward and one adjoint simulation for a given probe configuration. These maps are used to identify those probe configurations that best interrogate targeted subvolumes. Inverse solutions in a layered tissue model serve to illustrate and reinforce our analysis.
Multipurpose Monte Carlo simulator for photon transport in turbid media
2009 Ieee Nuclear Science Symposium Conference Record, Vols 1-5, 2009
Monte Carlo methods provide a flexible and rigorous solution to the problem of light transport in turbid media, which enable approaching complex geometries for a closed analytical solution is not feasible. The simulator implements local rules of propagation in the form of probability density functions that depend on the local optical properties of the tissue.
IEEE Journal of Selected Topics in Quantum Electronics, 2000
In order to facilitate rapid simulation of reflectance spectroscopy for biological tissue, we have derived convolution equations needed to apply the condensed Monte Carlo (MC) modeling approach to single illumination-detection fiber probes. This approach was validated against a standard MC model, and then implemented to perform three computationally demanding tasks. First, by performing simulations at a wide range of optical property combinations, we characterized the effect of fiber diameter on the relationship between reflectance and tissue optical properties. Second, we simulated reflectance from 400 to 500 nm based on the optical properties of malignant and adipose breast tissues to elucidate the effect of fiber diameter on detected reflectance spectra. The third task involved evaluating the effect of adding an illumination-detection fiber to a linear array fiber probe for optical property determination. The implications of this approach for optimization of probe geometries are discussed. In addition to providing an important tool for high-volume MC simulation, this study has generated unique insights into the role of device design for reflectance spectroscopy.
A Robust Monte Carlo Model for the Extraction of Biological Absorption and Scattering In Vivo
IEEE Transactions on Biomedical Engineering, 2000
We have a toolbox to quantify tissue optical properties that is composed of specialized fiberoptic probes for UVvisible 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 instrumentspecific 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.
Applied Optics, 1996
To validate models of light propagation in biological tissue, experiments to measure the mean time of flight have been carried out on several solid cylindrical layered phantoms. The optical properties of the inner cylinders of the phantoms were close to those of adult brain white matter, whereas a range of scattering or absorption coefficients was chosen for the outer layer. Experimental results for the mean optical path length have been compared with the predictions of both an exact Monte Carlo 1MC2 model and a diffusion equation, with two differing boundary conditions implemented in a finite-element method 1FEM2. The MC and experimental results are in good agreement despite poor statistics for large fiber spacings, whereas good agreement with the FEM prediction requires a careful choice of proper boundary conditions.
A Monte Carlo model of light propagation in tissue
1989
ABSTRACT The Monte Carlo method is rapidly becoming the model of choice for simulating light transport in tissue. This paper provides all the details necessary for implementation of a Monte Carlo program. Variance reduction schemes that improve the efficiency of the Monte Carlo method are discussed. Analytic expressions facilitating convolution calculations for finite flat and Gaussian beams are included. Useful validation benchmarks are presented.
Monte Carlo modeling of light–tissue interactions in narrow band imaging
Journal of Biomedical Optics, 2013
Light–tissue interactions that influence vascular contrast enhancement in narrow band imaging (NBI) have not been the subject of extensive theoretical study. In order to elucidate relevant mechanisms in a systematic and quantitative manner we have developed and validated a Monte Carlo model of NBI and used it to study the effect of device and tissue parameters, specifically, imaging wavelength (415 versus 540 nm) and vessel diameter and depth. Simulations provided quantitative predictions of contrast—including up to 125% improvement in small, superficial vessel contrast for 415 over 540 nm. Our findings indicated that absorption rather than scattering—the mechanism often cited in prior studies—was the dominant factor behind spectral variations in vessel depth-selectivity. Narrow-band images of a tissue-simulating phantom showed good agreement in terms of trends and quantitative values. Numerical modeling represents a powerful tool for elucidating the factors that affect the performance of spectral imaging approaches such as NBI.