Cristina Pasquinelli, Hazael Montanaro, Hyunjoo Jenny Lee, Lars G. Hanson, Hyungguk Kim, Niels Kuster, Hartwig R Siebner, Esra Neufeld and Axel Thielscher, Journal of Neural Engineering 2020, Volume 17, Issue 4, 046010, online 02 June 2020; doi: 10.1088/1741-2552/ab98dc
Low-intensity transcranial ultrasound stimulation (TUS) is emerging as a noninvasive brain stimulation technique with superior spatial resolution and the ability to selectively reach deep brain areas. Medical image-based computational modeling could be an important tool for individualized TUS dose control and targeting optimization, but requires further validation. This study aims to assess the impact of the transducer model on the accuracy of the simulations. Using hydrophone measurements, the acoustic beam of a single-element focused transducer (SEFT) with a flat piezoelectric disc and an acoustic lens was characterized. The acoustic beam was assessed in a homogeneous water bath and after transmission through obstacles (3D-printed shapes as well as skull samples). The acoustic simulations employed the finite-difference time-domain method and were informed by computed tomography (CT) images of the obstacles. Transducer models of varying complexity were tested, representing the SEFT either as a surface boundary condition with variable curvature, or accounting for the internal transducer geometry. In addition, a back-propagated pressure distribution from the first measurement plane was used as a source model. The simulations and measurements were quantitatively compared using key metrics for peak location, focus size, intensity and spatial distribution. While a surface boundary with an adapted, 'effective' curvature radius based on the specifications given by the manufacturer could reproduce the measured focus location and size in a homogeneous water bath, it regularly failed to accurately predict the beam after obstacle transmission. In contrast, models that reproduce the internal transducer structure and physics measurements performed substantially better in all cases with obstacles.
The scientific and technical impact of the study can be summarized as: