Monte Carlo modeling for perfusion monitoring

A Monte Carlo method was developed to model light transport through multi-layered tissue with the application focused on the development of an implantable perfusion monitor. The model was developed and then verified experimentally with a micro perfusion phantom. The program modeled a three-layer (tissue, capillary bed, tissue) scenario to investigate the source-detector separation effects for an implantable sensor. The Monte Carlo code was used specifically to model the effects of absorption and scattering properties of the surrounding tissue, the hemoglobin concentration in the middle layer, the ratio of thickness of the capillary layer to the first layer, and the probe-source separation distance on the propagation of the light through the tissue. The model was verified experimentally, using a simple in vitro system with optical source and detector fibers separated at various distances. The model was also used to investigate fluctuations in luminance as a result of hemoglobin concentrations and the response of the system to various wavelengths. The model was helpful for an ongoing project to develop an implantable perfusion monitor for transplanted organs or skin flaps.

[1]  Masatoshi Tarumi,et al.  Monte Carlo simulation of NIR spectrum changes induced by variations of glucose concentration , 2002, SPIE BiOS.

[2]  Gert E. Nilsson,et al.  Evaluation of a Laser Doppler Flowmeter for Measurement of Tissue Blood Flow , 1980, IEEE Transactions on Biomedical Engineering.

[3]  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.

[4]  Gert Nilsson,et al.  Monte Carlo simulations of light interaction with blood vessels in human skin in the red-wavelength region , 1998, Photonics West - Biomedical Optics.

[5]  W K Barnikol,et al.  Dependence of visible spectrum [epsilon (lambda)] of fully oxygenated hemoglobin on concentration of hemoglobin. , 1982, Journal of applied physiology: respiratory, environmental and exercise physiology.

[6]  Yurii P. Sinichkin,et al.  In vivo fluorescence spectroscopy of the human skin: experiments and models. , 1998, Journal of biomedical optics.

[7]  Peter R. Smith,et al.  A new method for pulse oximetry possessing inherent insensitivity to artifact , 2001, IEEE Transactions on Biomedical Engineering.

[8]  M. Ericson,et al.  In vivo application of a minimally invasive oximetry based perfusion sensor , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[9]  F F de Mul,et al.  Monte Carlo simulations of laser Doppler blood flow measurements in tissue. , 1990, Applied optics.

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

[11]  S. Jacques,et al.  Light distributions in artery tissue: Monte Carlo simulations for finite‐diameter laser beams , 1989, Lasers in surgery and medicine.

[12]  R. Nossal,et al.  Model for laser Doppler measurements of blood flow in tissue. , 1981, Applied optics.

[13]  D I McLean,et al.  Reconstruction of in vivo skin autofluorescence spectrum from microscopic properties by Monte Carlo simulation. , 1997, Journal of photochemistry and photobiology. B, Biology.