A modeling-based assessment of acousto-optic sensing for monitoring high-intensity focused ultrasound lesion formation

Real-time acousto-optic (AO) sensing - a dual-wave modality that combines ultrasound with diffuse light to probe the optical properties of turbid media - has been demonstrated to non-invasively detect changes in ex vivo tissue optical properties during high-intensity focused ultrasound (HIFU) exposure. The AO signal indicates the onset of lesion formation and predicts resulting lesion volumes. Although proof-of-concept experiments have been successful, many of the underlying parameters and mechanisms affecting thermally induced optical property changes and the AO detectability of HIFU lesion formation are not well understood. In thesis, a numerical simulation was developed to model the AO sensing process and capture the relevant acoustic, thermal, and optical transport processes. The simulation required data that described how optical properties changed with heating. Experiments were carried out where excised chicken breast was exposed to thermal bath heating and changes in the optical absorption and scattering spectra (500 nm - 1100 nm) were measured using a scanning spectrophotometer and an integrating sphere assembly. Results showed that the standard thermal dose model currently used for guiding HIFU treatments needs to be adjusted to describe thermally induced optical property changes. To model the entire AO process, coupled models were used for ultrasound propagation, tissue heating, and diffusive light transport. The angular spectrum method was used to model the acoustic field from the HIFU source. Spatial-temporal temperature elevations induced by the absorption of ultrasound were modeled using a finite-difference time-domain solution to the Pennes bioheat equation. The thermal dose model was then used to determine optical properties based on the temperature history. The diffuse optical field in the tissue was then calculated using a GPU-accelerated Monte Carlo algorithm, which accounted for light-sound interactions and AO signal detection. The simulation was used to determine the optimal design for an AO guided HIFU system by evaluating the robustness of the systems signal to changes in tissue thickness, lesion optical contrast, and lesion location. It was determined that AO sensing is a clinically viable technique for guiding the ablation of large volumes and that real-time sensing may be feasible in the breast and prostate