Related Experiment Video
Updated: Jun 8, 2026
Non-invasive In Vivo Fluorescence Optical Imaging of Inflammatory MMP Activity Using an Activatable Fluorescent Imaging Agent
Published on: May 8, 2017
In vivo fluorescence imaging of E-selectin: quantitative detection of endothelial activation in a mouse model of
Luke L Gompels1, Leigh Madden, Ngee Han Lim
1Kennedy Institute of Rheumatology, Imperial College London, London, UK. l.gompels@imperial.ac.uk
Objective:
In vivo optical imaging can delineate at the macroscopic level processes that are occurring at the cellular and molecular levels. E-selectin, a leukocyte adhesion molecule expressed on endothelium, is induced by tumor necrosis factor α (TNFα) and other cytokines involved in the pathogenesis of rheumatoid arthritis (RA). Collagen-induced arthritis (CIA) in mice is widely used to study the disease mechanisms and identify new treatments for RA. The purpose of this study was to demonstrate E-selectin-targeted fluorescence imaging in vivo in a mouse model of paw edema generated by local injection of TNFα as well as in mice with CIA.
Methods:
Animals with either CIA or TNFα-induced paw edema were injected with anti-E-selectin or control antibodies labeled with a DyLight 750-nm near-infrared (NIR) probe. In vivo imaging studies were undertaken using an NIR optical imaging system, and images were coregistered with plain radiographic images.
Results:
The mean fluorescence intensity measured over the time-course of TNFα-induced edema demonstrated a 1.97-fold increase (P<0.001) in signal in inflamed paws at 8 hours following injection of anti-E-selectin antibody, as compared to that in the isotype control. In the CIA model, a 2.34-fold increase in E-selectin-targeted signal was demonstrated (P<0.01). Furthermore, significant E-selectin-targeted signal was observed in the paws of animals immunized with collagen that did not display overt signs of arthritis.
Conclusion:
E-selectin-targeted fluorescence in vivo imaging is a quantifiable method of detecting endothelial activation in arthritis and can potentially be applied to the quantification of disease and the investigation of the effects of new therapies. Importantly, this approach may also be useful for the detection of subclinical disease in RA.
