Optical tomography in small animals with time-resolved Monte Carlo methods

Abstract

In this thesis, mathematical reconstruction models for time-resolved whole-body functional and molecular imaging in small animals were developed and optimized. These models were based on the Monte Carlo approach which is considered the most accurate model to simulate light propagation in bio-tissue. The reconstruction procedures were implemented under a massively parallel environment for computational efficiency. The novel reconstruction method was applied to quantitative estimation of intrinsic optical properties, then to direct reconstruction of functional parameters (blood volume and relative oxygenation maps) in small animals. Furthermore, this method was validated experimentally with widefield illumination techniques, which led to a significant reduction of computational and experimental time. The feasibility of the model in imaging fluorescence markers with lifetime contrast was also established through simulations, phantom and animal studies, and the information content for different time gates was analyzed. Additionally, the model was compared to other available Monte Carlo based methods for time efficiency, with an evaluation of the parameters affecting the computational burden. Lastly, a mesh-based Monte Carlo method for wide-field illumination was developed to further accelerate the calculation and improve accuracy.

Small animal imaging has become an essential translational tool between in vitro research and clinical application, enabling the study of human disease, as well as the response of disease to environmental factors and drugs in animal models. Among preclinical imaging modalities, optical imaging techniques play a central role thanks to their ability to non-invasively trace molecular probes with high sensitivity and low cost. These probes can be visualized three-dimensionally by optical tomography technique, thus providing quantitative maps of the functional and molecular status of tissue to identify biologic processes, diagnose disease progression and monitor drug delivery. However, the unwieldy instrument design and complex mathematical models limit the broad dissemination of tomography-based optical imagers due to the difficulties in achieving time efficiency, high resolution, and quantitative accuracy simultaneously in preclinical models. Especially, the development of an accurate mathematical model with a computationally efficient implementation thus becomes critical for broadening the impact of quantitative optical tomography.