A Coded Excitation Framework for High SNR Transcranial Ultrasound Imaging - Vienneau, Emelina P.; Byram, Brett C. (IEEE transactions on medical imaging, 2023)
Robust transcranial ultrasound imaging is difficult due to poor image quality. In particular, low signal-to-noise ratio (SNR) limits sensitivity to blood flow and has hindered clinical translation of transcranial functional ultrasound neuroimaging thus far. In this work, we present a coded excitation framework to increase SNR in transcranial ultrasound without negatively impacting frame rate or image quality. We applied this coded excitation framework in phantom imaging and showed SNR gains as large as 24.78 dB and signal-to-clutter ratio gains as high as 10.66 dB with a 65 bit code. We also analyzed how imaging sequence parameters can impact image quality and showed how coded excitation sequences can be designed to maximize image quality for a given application. In particular, we show that considering the number of active transmit elements and the transmit voltage is critical for coded excitation with long codes. Finally, we applied our coded excitation technique in transcranial imaging of ten adult subjects and showed an average SNR gain of 17.91 ± 0.96 dB without a significant increase in clutter using a 65 bit code. We also performed transcranial power Doppler imaging in three adult subjects and showed contrast and contrast-to-noise ratio improvements of 27.32 ± 8.08 dB and 7.25 ± 1.61 dB, respectively with a 65 bit code. These results show that transcranial functional ultrasound neuroimaging may be possible using coded excitation.