Neonatal CNS Circulation
Ultrasonic contrast-free microvascular imaging using ultrafast Doppler is an emerging technology which has enabled microvascular imaging in brain, tumor vascularization imaging, and functional ultrasound. However, the technology has, as far as we know, mostly be used in situations with little or no motion artefacts and using clinical transducer frequencies. The rabbit pup brain is a very useful model for the study of brain intraventricular hemorrhage. Ultrasonic microflow measurements are likely to provide original information of the disease. However, the measurements need to be carried out on awake rabbit pups which often creates severe motion artefacts particularly in ultrahigh frequency ultrasound imaging. We present the first motion compensated contrast-free microvascular measurement on awake rabbit pup using ultrahigh frequency ultrasound imaging.
We evaluated the optimal setting for contrast-free brain microvascular imaging of awake rabbit pups. We used three different transducers (UHF46x, UHF29x and L10-5) (Visualsonics Inc, Canada) on a Vevo F2 wide-band ultrasound scanner (Visualsonics Inc, Canada) and micro flow phantoms and awake rabbit pups. A clutter filter based on singular value decomposition was applied to beamformed RF signals obtained with coherent plane wave compounding and then power Doppler processing was applied to the clutter-filtered signals. The tissue movement was estimated by applying speckle tracking to pre-filtered signal because the clutter-filtered signals were fluctuated rapidly owing to blood flow.
Preliminary results show that the best quality is achieved using the UHF46x transducer (centre frequency 30 MHz) and the following settings PRF 10 kHz, 3 (-3⁰, 0⁰, 3⁰) or 6 (-5⁰, -3⁰, -1⁰, 1⁰, 3⁰, 5⁰) angles, 3 pulse cycles and low rail. The figure shows the averaged power Doppler representation of the microvascular imaging in awake rabbit pup brain A) with and B) without motion compensation. Note that more details are visible when the image is motion compensated.
Professor David Lay, MD, PhD
Magnus Gram, MD, PhD