In vivo 3D Super-Resolution Ultrasound Imaging of a Rat Kidney using a Row-Column Array

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Super-resolution ultrasound imaging (SRI) is a widely used technique for visualization of the microvasculature. The technique generally relies on long observation times if the smallest vessels have to be resolved. This makes it impractical for 3D imaging due to the large amounts of data required. Especially, matrix probes suffer from this, as the channel count is typically above 1024, which results in either a limited acquisition time or a greatly reduced frame rate. This work investigated the feasibility of using a row-column array (RCA) for 3D SRI. The 3D vascular tree of a Sprague Dawley rat kidney was imaged in a 26×26×40 mm3 volume using only 128 active elements in receive for a 6 MHz 128+128 Vermon RCA connected to a Verasonics Vantage 256™ scanner. Forty eight virtual sources with an amplitude modulated sequences were used to acquire 36 seconds of contrast-enhanced volumes. The data rate was 2.74 GBytes/s. Then, the 3D visualization of the vasculature was provided by localization of peaks in the acquired volumes. The estimated resolution using Fourier shell correlation for the reconstructed vasculature in this volume was 43 μm with half-bit and 61 μm with one-bit threshold, which was a factor of 6 below the wavelength (λ = 256 μm). In conclusion, the study showed the feasibility of super-resolution vascular imaging of a rat kidney using a RCA.

TitelIUS 2022 - IEEE International Ultrasonics Symposium
ForlagIEEE Press
ISBN (Elektronisk)9781665466578
StatusUdgivet - 2022
Begivenhed2022 IEEE International Ultrasonics Symposium, IUS 2022 - Venice, Italien
Varighed: 10 okt. 202213 okt. 2022


Konference2022 IEEE International Ultrasonics Symposium, IUS 2022
SponsorIEEE, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (UFFC)

Bibliografisk note

Funding Information:
ACKNOWLEDGMENT The work was financially supported by European Research Council’s (ERC) Synergy Grant 854796.

Publisher Copyright:
© 2022 IEEE.

ID: 329687349