Monte Carlo Simulation to Study Propagation of Light through Biological Tissues

Abstract

Photoacoustic Imaging is a non-invasive optical imaging modality used to image biological tissues. In this method, a pulsating laser illuminates a region of tissues to be imaged, which then generates an acoustic wave due to thermal volume expansion. This wave is then sensed using an acoustic sensor such as a piezoelectric transducer and the resultant signal is converted into an imaging using the back projection algorithm. Since different types of tissues have different photo-acoustic properties, this imaging modality can be used for imaging different types of tissues and bodily organ systems. This study aims at quantifying the process of light conversion into the acoustic signal. Light travels through tissues and gets attenuated (scattered or absorbed) or reflected depending on the optical properties of the tissues. The process of light propagation through tissues is studied using Monte Carlo simulation software which predicts the propagation of light through tissues of various shapes and with different optical properties. This simulation gives the resultant energy distribution due to light absorption and scattering on a voxel by voxel basis. The Monte Carlo code alone is not sufficient to validate the photon propagation. The success of the Monte Carlo code depends on accurate prediction of the optical properties of the tissues. It also depends on accurately depicting tissue boundaries and thus the resolution of the imaging space. Hence, a validation algorithm has been designed so as to recover the optical properties of the tissues which are imaged and to successfully validate the simulation results. The accuracy of the validation code is studied for various optical properties and boundary conditions. The results are then compared and validated with real time images obtained from the photoacoustic scanner. The various parameters for the successful validation of Monte Carlo method are studied and presented. This study is then validated using the algorithm to study the conversion of light to sound. Thus it is a significant step in the quantification of the photoacoustic effect so as to accurately predict tissue properties.