Evaluation of 2D super-resolution ultrasound imaging of the rat renal vasculature using ex vivo micro-computed tomography

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Sofie Bech Andersen
Iman Taghavi
Hans Martin Kjer
Stinne Byrholdt Søgaard
Carsten Gundlach
Vedrana Andersen Dahl
Michael Bachmann Nielsen
Anders Bjorholm Dahl
Jørgen Arendt Jensen
Charlotte Mehlin Sørensen
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[1] University of Copenhagen,Department of Biomedical Sciences
[2] Rigshospitalet,Department of Radiology
[3] Technical University of Denmark,Center for Fast Ultrasound Imaging, Department of Health Technology
[4] Technical University of Denmark,Department of Applied Mathematics and Computer Science
[5] Technical University of Denmark,Department of Physics
[6] University of Copenhagen,Department of Clinical Medicine
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Super-resolution ultrasound imaging (SRUS) enables in vivo microvascular imaging of deeper-lying tissues and organs, such as the kidneys or liver. The technique allows new insights into microvascular anatomy and physiology and the development of disease-related microvascular abnormalities. However, the microvascular anatomy is intricate and challenging to depict with the currently available imaging techniques, and validation of the microvascular structures of deeper-lying organs obtained with SRUS remains difficult. Our study aimed to directly compare the vascular anatomy in two in vivo 2D SRUS images of a Sprague–Dawley rat kidney with ex vivo μCT of the same kidney. Co-registering the SRUS images to the μCT volume revealed visually very similar vascular features of vessels ranging from ~ 100 to 1300 μm in diameter and illustrated a high level of vessel branching complexity captured in the 2D SRUS images. Additionally, it was shown that it is difficult to use μCT data of a whole rat kidney specimen to validate the super-resolution capability of our ultrasound scans, i.e., validating the actual microvasculature of the rat kidney. Lastly, by comparing the two imaging modalities, fundamental challenges for 2D SRUS were demonstrated, including the complexity of projecting a 3D vessel network into 2D. These challenges should be considered when interpreting clinical or preclinical SRUS data in future studies.
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