Modeling Light Transport in Tissues

Modeling light transport in tissues is crucial to the understanding of laser-tissue interactions. A Monte Carlo model of steady-state light transport in multi-layered tissues (MCML) and a companion convolution program (CONV) solving responses to a collimated finite diameter photon beam perpendicularly incident on a multi-layered tissue have been coded in ANSI Standard C; hence, the program can be executed on various computers. The program, employing the extended trapezoidal rule for integration, convolves the responses to an infinitely narrow photon beam computed by MCML. Dynamic data allocation is used for CONV as well as MCML; therefore, the number of tissue layers and grid elements of the grid system can be varied at run time. The program, including the source code, has been released to the public domain since 1992 and can be downloaded from here.

As an example of the many applications of the models, optimal laser light delivery into turbid biological tissues was studied using Monte Carlo simulations based on the delta-scattering technique. The goal was to efficiently deliver the maximum amount of optical power into buried tumors being treated, while avoiding potential damage to normal tissue caused by strong optical power deposition underneath the tissue surface illuminated by the laser beam. The buried tumors were considered to have much higher absorption than the surrounding normal tissue due to selective uptake of absorption-enhancement dye. The power delivering efficiency to buried tumors was investigated for various diameters of the laser beam. An optimal beam diameter was estimated to achieve the maximum product of the power coupling efficiency and the power delivered to the buried tumor. The distribution of power deposition was simulated for single beam delivery and multiple beam delivery as well. The simulated results showed that with an appropriate dye enhancement and an optimal laser delivery configuration, a high selectivity for laser treatment of tumor could be achieved.

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