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Validation of Ultrasound Super-Resolution Imaging of Vasa Vasorum in Rabbit Atherosclerotic Plaques

Title
Validation of Ultrasound Super-Resolution Imaging of Vasa Vasorum in Rabbit Atherosclerotic Plaques
Author(s)
Chen, QiyangYu, JaesokLukashova, LyudmilaLatoche, Joseph D.Zhu, JianhuiLavery, LindaVerdelis, KonstantinosAnderson, Carolyn JKim, Kang
Issued Date
2020-08
Citation
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, v.67, no.8, pp.1725 - 1729
Type
Article
Author Keywords
Atherosclerotic plaque (AP)experiment protocolsuper resolutionultrasound (US) imagingvasa vasorum (VV)
Keywords
ANGIOGENESISMICROVASCULATUREHETEROGENEITYVULNERABILITYPROGRESSIONMORPHOLOGYARTERIALINTRAVASCULAR ULTRASOUNDIN-VIVONEOVASCULARIZATION
ISSN
0885-3010
Abstract
Acute coronary syndromes and strokes are mainly caused by atherosclerotic plaque (AP) rupture. Abnormal increase of vasa vasorum (VV) is reported as a key evidence of plaque progression and vulnerability. However, due to their tiny size, it is still challenging to noninvasively identify VV near the major vessels. Ultrasound super resolution (USR), a technique that provides high spatial resolution beyond the acoustic diffraction limit, demonstrated an adequate spatial resolution for VV detection in early studies. However, a thorough validation of this technology in the plaque model is particularly needed in order to continue further extended preclinical studies. In this letter, we present an experiment protocol that verifies the USR technology for VV identification with subsequent histology and ex vivo micro-computed tomography ( \mu CT). Deconvolution-based USR imaging was applied on two rabbits to identify the VV near the AP in the femoral artery. Histology and ex vivo \mu CT imaging were performed on excised femoral tissue to validate the USR technique both pathologically and morphologically. This established validation protocol could facilitate future extended preclinical studies toward the clinical translation of USR imaging for VV identification. © IEEE.
URI
http://hdl.handle.net/20.500.11750/12802
DOI
10.1109/tuffc.2020.2974747
Publisher
Institute of Electrical and Electronics Engineers
Related Researcher
  • 유재석 Yu, Jaesok
  • Research Interests Biomedical ultrasound/photoacoustic imaging and therapeutics; Medical image processing; Machine learning-based diagnosis and signal processing; Nano-theranostic platform
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Appears in Collections:
Department of Robotics and Mechatronics Engineering Advanced Ultrasound Research Laboratory 1. Journal Articles

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