Light transport in tissue by 3D Monte Carlo: Influence of boundary voxelization

Monte Carlo (MC) based simulations of photon transport in living tissues have become the "gold standard" technique in biomedical optics. Three-dimensional (3D) voxel-based images are the natural way to represent human (and animal) tissues. It is generally believed that the combination of 3D images and MC based algorithms allows one to produce the most realistic models of photon propagation. In the present work, it is shown that this approach may lead to large errors in the MC data due to the "roughness" of the geometrical boundaries generated by the presence of the voxels. In particular, the computed intensity of the light detected on the tissue surface of a simple cubic tissue phantom may display errors from -80% to 120%. It is also shown that these errors depend in a complex manner on optical and geometrical parameters such as the interoptode distance, scattering coefficient, refractive index, etc. and on the degree of voxelization ("roughness") of the boundaries. It is concluded that if one wants to perform reliable 3D Monte Carlo simulations on complex geometries, such as human brain, skin or trabecular bone, it is necessary to introduce boundary meshing techniques or other equivalent procedures in the MC code to eliminate the deleterious effect of voxelization.

[1]  S Andersson-Engels,et al.  Real-time method for fitting time-resolved reflectance and transmittance measurements with a monte carlo model. , 1998, Applied optics.

[2]  M S Patterson,et al.  Optical properties of normal and diseased human breast tissues in the visible and near infrared. , 1990, Physics in medicine and biology.

[3]  Simon R Arridge,et al.  Two-dimensional quantitative photoacoustic image reconstruction of absorption distributions in scattering media by use of a simple iterative method. , 2006, Applied optics.

[4]  Jun Q. Lu,et al.  Optical properties of porcine skin dermis between 900 nm and 1500 nm , 2001, Physics in medicine and biology.

[5]  Nick Everdell,et al.  Optical tomography of the breast using a multi-channel time-resolved imager , 2005, Physics in medicine and biology.

[6]  Xin-Hua Hu,et al.  Effect of surface roughness on determination of bulk tissue optical parameters. , 2003, Optics letters.

[7]  N. Ramanujam,et al.  Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms. , 2006, Applied optics.

[8]  Miloslav Ohlídal,et al.  IV: Scattering of Light from Multilayer Systems With Rough Boundaries , 1995 .

[9]  James B. Bassingthwaighte,et al.  Strategies for the Physiome Project , 2000, Annals of Biomedical Engineering.

[10]  Ilias Tachtsidis,et al.  A physiological model of cerebral blood flow control. , 2005, Mathematical biosciences.

[11]  I. M. Sobolʹ The Monte Carlo method , 1974 .

[12]  P Cerretelli,et al.  Muscle O(2) consumption by NIRS: a theoretical model. , 1999, Journal of applied physiology.

[13]  S R Arridge,et al.  The theoretical basis for the determination of optical pathlengths in tissue: temporal and frequency analysis. , 1992, Physics in medicine and biology.

[14]  Guillermo Aguilar,et al.  Comparison of diffusion approximation and Monte Carlo based finite element models for simulating thermal responses to laser irradiation in discrete vessels , 2005, Physics in medicine and biology.

[15]  S R Arridge,et al.  Recent advances in diffuse optical imaging , 2005, Physics in medicine and biology.

[16]  A. Welch,et al.  Optical Monte Carlo modeling of a true portwine stain anatomy. , 1998, Optics express.

[17]  G. Marsaglia,et al.  A New Class of Random Number Generators , 1991 .

[18]  D T Delpy,et al.  Parallel operation of Monte Carlo simulations on a diverse network of computers. , 1997, Physics in medicine and biology.

[19]  J. Spanier,et al.  Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues. , 2001, Optics letters.

[20]  S. Arridge,et al.  Optical imaging in medicine: II. Modelling and reconstruction , 1997, Physics in medicine and biology.

[21]  M. Ferrari,et al.  Principles, techniques, and limitations of near infrared spectroscopy. , 2004, Canadian journal of applied physiology = Revue canadienne de physiologie appliquee.

[22]  S. A. Prahl,et al.  A Monte Carlo model of light propagation in tissue , 1989, Other Conferences.

[23]  J. Briers,et al.  Laser Doppler, speckle and related techniques for blood perfusion mapping and imaging. , 2001, Physiological measurement.

[24]  D. Boas,et al.  Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. , 2002, Optics express.

[25]  M. Kohl,et al.  Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique. , 1998, Physics in medicine and biology.

[26]  D. Boas,et al.  Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging. , 2006, Applied optics.

[27]  Leonardo Dagdug,et al.  Effects of anisotropic optical properties on photon migration in structured tissues. , 2003, Physics in medicine and biology.

[28]  L Wang,et al.  MCML--Monte Carlo modeling of light transport in multi-layered tissues. , 1995, Computer methods and programs in biomedicine.

[29]  A. Witt,et al.  Multiple scattering in reflection nebulae. I - A Monte Carlo approach. II - Uniform plane-parallel nebulae with foreground stars. III - Nebulae with embedded illuminating stars , 1977 .

[30]  I. V. Meglinsky,et al.  Modelling the sampling volume for skin blood oxygenation measurements , 2006, Medical and Biological Engineering and Computing.

[31]  Thomas E. Milner,et al.  A three-dimensional modular adaptable grid numerical model for light propagation during laser irradiation of skin tissue , 1996 .

[32]  A. Welch,et al.  Modeling laser treatment of port wine stains with a computer‐reconstructed biopsy , 1999, Lasers in surgery and medicine.

[33]  L. C. Henyey,et al.  Diffuse radiation in the Galaxy , 1940 .

[34]  Heidrun Wabnitz,et al.  Non-invasive detection of fluorescence from exogenous chromophores in the adult human brain , 2006, NeuroImage.

[35]  H. J. van Staveren,et al.  The optical properties of lung as a function of respiration. , 1997, Physics in medicine and biology.

[36]  Jc Miranda-Valenzuela,et al.  Adaptive Meshing with Boundary Elements. Topics in Engineering, Vol 41 , 2002 .