Assessment of natriuretic peptide clearance receptor with positron emission tomography in cardiovascular disease models

Yongjian Liu, R. Rossin, D. Abendschein, G. E. Woodard, J. Zheng, K. McCommis, P. K. Woodard, M. J. Welch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cardiovascular molecular imaging is a rapidly evolving field of research, aiming to image and quantify molecular and cellular targets in vivo. Natriuretic peptides (NPs) can acts as a potent inhibitor of vascular smooth muscle cell migration and proliferation through activation of the clearance receptor (NPR-C). In this study, the potential use of a C-type NP fragment (C-ANF) to image the NPR-C receptor expression in developing plaque-like lesions in a rabbit atherosclerosis model and surgically ligated thigh of murine hindlimb ischemia model by functionalization with 1,4,7,10-tetraazacyclododecane-1,4,7, 10-tetraacetic acid (DOTA) and labeled with copper-64 for non-invasive imaging with positron emission tomography (PET). Results clearly showed the significantly higher tracer uptake in the injured sites in both models compared to the contralateral control sites. PET imaging and competitive receptor blocking studies demonstrated the NPR-C receptor mediated tracer uptake.

Original languageEnglish
Title of host publicationComputers in Cardiology 2009, CinC 2009
Pages241-244
Number of pages4
StatePublished - Dec 1 2009
Event36th Annual Conference of Computers in Cardiology, CinC 2009 - Park City, UT, United States
Duration: Sep 13 2009Sep 16 2009

Publication series

NameComputers in Cardiology
Volume36
ISSN (Print)0276-6574

Conference

Conference36th Annual Conference of Computers in Cardiology, CinC 2009
CountryUnited States
CityPark City, UT
Period09/13/0909/16/09

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    Liu, Y., Rossin, R., Abendschein, D., Woodard, G. E., Zheng, J., McCommis, K., Woodard, P. K., & Welch, M. J. (2009). Assessment of natriuretic peptide clearance receptor with positron emission tomography in cardiovascular disease models. In Computers in Cardiology 2009, CinC 2009 (pp. 241-244). [5445424] (Computers in Cardiology; Vol. 36).