Acoustoelectric brain imaging with different conductivities and acoustic distributions - Zhou, Yijie; Song, Xizi; Song, Yibo; Guo, Jiande; Han, Gangnan; Liu, Xiuyun; He, Feng; Ming, Dong (Frontiers in Physiology, 2023)
Objective. Acoustoelectric brain imaging (AEBI) is a promising imaging method for mapping brain biological current densities with high spatiotemporal resolution. Currently, it is still challenging to achieve human AEBI with unclear acoustoelectric (AE) signal response of medium characteristics particularly in conductivity and acoustic distribution. This study introduces different conductivities and acoustic distributions into AEBI experiment, and clarifies the response interaction between medium characteristics and AEBI performance to address these key challenges. Approach. The AEBI with different conductivities is explored by the imaging experiment, potential measurement and simulation on a pig fat, muscle and brain tissue. The AEBI with different acoustic distributions is evaluated on the imaging experiment and acoustic field measurement through a deep and surface transmitting model built on a human skullcap and pig brain tissue. Main results. The results show that the conductivity is not only inversely proportional to AE signal amplitude, but also leads to a higher AEBI spatial resolution as it increases. In addition, the current source and sulcus can be located simultaneously with a strong AE signal intensity. Transcranial focal zone enlargement, pressure attenuation in the deep-transmitting model and ultrasound echo enhancement in the surfacetransmitting model cause a reduced spatial resolution, FFT-SNR and timing correlation of AEBI.Under the comprehensive effect of conductivity and acoustics, AEBI with skull finally shows a reduced imaging performance for both models compared with no-skull AEBI. Differently, AE signal amplitude decreases in the deep-transmitting model and increases in the surface-transmitting model.Significance. This study reveals the response interaction between the medium characteristics and AEBI performance, and makes an essential step towards developing AEBI as a practical neuroimaging technique.