A Monte Carlo model of light propagation in tissue

Prahl, Scott A.

doi:10.1117/12.2283590

Cited by 397 publications

(405 citation statements)

References 7 publications

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“…All photons were launched from a point on the cylindrical surface of the laser applicator. The photons were then moved a fixed step size (one-tenth of the mean free path (35)) arbitrarily varied by 25% to avoid interference with the fixed voxel size. The actual step width ⌬s was then calculated according to…”

Section: Mcs Detailsmentioning

confidence: 99%

Simulations of thermal tissue coagulation and their value for the planning and monitoring of laser‐induced interstitial thermotherapy (LITT)

Puccini

Bär

Bublat

et al. 2003

Magnetic Resonance in Med

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Section: Mcs Detailsmentioning

confidence: 99%

Simulations of thermal tissue coagulation and their value for the planning and monitoring of laser‐induced interstitial thermotherapy (LITT)

Puccini

Bär

Bublat

et al. 2003

Magnetic Resonance in Med

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“…The MC software used is an in-house software based on [1,2], with extended functionality to handle various geometries (cylinders, boxes) and Doppler shifts. The software, which has been validated to [2], has previously been used in [4,14].…”

Section: Methodsmentioning

confidence: 99%

“…In biophotonics, where the diffusion approximation occasionally is inadequate to solve the transport equation accurately, light transport can be simulated by tracing a large number of individual photon random walks using the MC method. Thorough, basic descriptions of the method in biophotonics have been given previously [1,2].…”

Section: Introductionmentioning

confidence: 99%

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Forced Detection Monte Carlo Algorithms for Accelerated Blood Vessel Image Simulations

Fredriksson

Larsson

Strömberg

2009

Journal of Biophotonics

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Two forced detection (FD) variance reduction Monte Carlo algorithms for image simulations of tissue‐embedded objects with matched refractive index are presented. The principle of the algorithms is to force a fraction of the photon weight to the detector at each and every scattering event. The fractional weight is given by the probability for the photon to reach the detector without further interactions. Two imaging setups are applied to a tissue model including blood vessels, where the FD algorithms produce identical results as traditional brute force simulations, while being accelerated with two orders of magnitude. Extending the methods to include refraction mismatches is discussed. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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“…While lasers are often used in medicine due to their precision, other irradiative techniques are gaining prominence, such as microwave irradiation [3]. Myriad tools currently exist to simulate the optical distribution within a material, principally using the Beer-Lambert equation to directly determine optical distribution, or MonteCarlo simulations to determine photon scattering and distribution [4,5]. No matter the method used, the optical distribution is then used to determine the thermal response of the material to the optical irradiation.…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo method for photon heating using temperature-dependent optical properties

Slade

Aguilar

2015

Computer Methods and Programs in Biomedicine

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Peer reviewed eScholarship.orgPowered by the California Digital Library University of California The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues.A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties.The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100 K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes.

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A Monte Carlo model of light propagation in tissue

Cited by 397 publications

References 7 publications

Simulations of thermal tissue coagulation and their value for the planning and monitoring of laser‐induced interstitial thermotherapy (LITT)

Simulations of thermal tissue coagulation and their value for the planning and monitoring of laser‐induced interstitial thermotherapy (LITT)

Forced Detection Monte Carlo Algorithms for Accelerated Blood Vessel Image Simulations

Monte Carlo method for photon heating using temperature-dependent optical properties

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