A Computational Framework Enabling Virtual Imaging Trials of 3D Quantitative Optoacoustic Tomography Breast Imaging

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ABSTRACT Optoacoustic tomography (OAT), also known as photoacoustic computed tomography, is a non-invasive imaging modality actively being developed for breast cancer imaging and other biomedical applications. A unique feature of OAT is the ability to produce an image based on the endogenous optical contrast associated with the concentration and oxygenation state of hemoglobin within tissue, without ionizing radiation and without the loss of spatial resolution typically associated with purely optical techniques such as optical diffusion tomography. Because aggressively growing malignant breast tumors tend to be under hypoxia and decreased blood oxygen saturation due to substantially increased metabolic activity in comparison to healthy tissue, an optimized and validated OAT system can be a powerful tool for the management of breast cancer by assessing density of the tumor microvasculature and its blood oxygenation. Currently, there is no validated OAT method that is sufficiently accurate for widespread clinical imaging of the breast; important issues such as optimal hardware and image reconstruction designs, the ability to resolve lesions at depth, and quantitative imaging remain unresolved. Due to the competing requirements of light delivery and acoustic detection, a variety of different system designs for breast OAT have been proposed; this is unlike in x-ray mammography, breast MRI and breast ultrasound, where very similar implementations are in use per modality. Considering the large number of parameters involved, it is infeasible to systematically optimize breast OAT through human trials due to time- and cost-constraints and ethical concerns. However, virtual imaging trials (VITs), where an imaging study is conducted in silico by use of representative numerical phantoms and imaging models, can offer a rapid and cost-efficient means of assessing and optimizing new imaging concepts and technologies such as OAT. The ability to conduct VITs for 3D OAT is currently lacking. The broad objective of this project is to develop, validate, and demonstrate computational tools for performing VITs that can inform the development of clinically viable and effective 3D breast OAT technologies. This will afford researchers an unprecedented level of control in modeling and validating quantitative OAT imaging of the tumor and tissue oxygen saturation distributions necessary for assessing breast cancer. The results will be the first of their kind evaluating the task-based merits and capabilities of OAT and the knowledge attainable in these studies is critical for translating this technology to the clinic. The Specific Aims of the project are: Aim 1. To develop multi-physics simulation tools for the in silico simulation of realistic measurement data in 3D breast OAT; Aim 2. To systematically develop and refine quantitative OAT image reconstruction methods; Aim 3. To conduct physical experiments that will be used to validate the computational models; Aim 4. To conduct VITs to explore quantitative OAT system optimization.