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Extraction of Optical Properties and Prediction of Light Distribution in Rat Brain Tissue

Extraction of Optical Properties and Prediction of Light Distribution in Rat Brain Tissue. Mehdi Azimipour 1 , Ryan Baumgartner 1 , Yuming Liu 2 , Steven Jacques 3 , Kevin Eliceiri 2 , Ramin Pashaie 1

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Extraction of Optical Properties and Prediction of Light Distribution in Rat Brain Tissue

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  1. Extraction of Optical Properties and Prediction of Light Distribution in Rat Brain Tissue Mehdi Azimipour1, Ryan Baumgartner1, Yuming Liu2, Steven Jacques3, Kevin Eliceiri2, Ramin Pashaie1 1Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee 2Laboratory for Optical and Computational Instrumentation , Department of Biomedical Engineering, University of Wisconsin-Madison 3Department of Biomedical Engineering, Oregon Health & Science University

  2. INTRODUCTION AND OBJECTIVE In recent years, optogenetics has opened up a new area in deep brain stimulation with light and the method is widely adapted by researchers for the study of the brain circuitries and the dynamics of neurological disorders. A key factor for a successful optogenetic stimulation is delivering adequate amount of light to the targeted brain objects. • Extracting optical properties (absorption coefficient, , scattering coefficient, , and anisotropy factor, ) of a rat brain tissue for three different wavelengths (405nm, 532nm, and 635nm) and three different cuts (Transverse, Sagittal and Dorsal) with spatial resolution of about 3000 sample points per square centimeter. • Developing a 3D database of the optical properties of rat brain tissue is extracted. • Using 3D Monte Carlo simulation for predicting distribution of light in brain tissue for different light source configurations. FIG 1: (A) Optical fiber implanted in the brain tissue to deliver light and stimulate deep brain objects in transfected areas, (B) A rat receiving two implants in the motor cortex on both hemispheres.

  3. METHODOLOGY • Measurement Procedures • Based on the IAD model, three different are required to extract the complete set of tissue optical properties including µa, µs, and g. Diffused reflectance and diffused transmittance were measured simultaneously using the double integrating spheres method (setup 1) and the ballistic transmittance measurements were performed by the optical setup 2. • Optical Properties Reconstruction • After collecting experimental data, the IAD method was employed to reconstruct the optical properties of the tissue. The IAD method is an iterative algorithm designed to extract the optical properties of a homogeneous sample from the three measurements discussed in the previous section. The iterations are initiated with some random values assigned to the optical properties of the medium. Then, in each iteration, the algorithm solves the radiative transport equation to calculate the transmission and reflection of the sample and compares these results with the experimental data. Next, it readjusts the values of the optical properties to minimize the error between the calculations and experimental results and continues this process until convergence.

  4. RESULTS AND CONCLUSION Conclusion In this work, we presented a new approach to extract the major optical properties (absorption and scattering coefficients, and anisotropy factor) of the rat brain tissue and using 3D Monte Carlo simulations for predicting light distribution in the tissue. Although the brain tissue and optogeneticneurostimulation was the main target in this study, the proposed approach for extracting optical properties and predicting the light distribution can be adapted as a general method for other tissue samples and different applications such laser surgery, laser therapy, optical tomography, etc. Experimental Data Reconstructed Optical Properties

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