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

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.

Grant Number: 5R01EB031585-04
NIH Institute/Center: NIH
Principal Investigator: Mark Anastasio