Seeing is believing Translational imaging approaches in cardiovascular disease

Open Access
Authors
  • K.H. Zheng
Supervisors
Cosupervisors
  • B.F. Coolen
  • H.J. Verberne
Award date 30-10-2020
ISBN
  • 9789463759298
Number of pages 289
Organisations
  • Faculty of Medicine (AMC-UvA)
Abstract
In this thesis, novel imaging modalities take the center stage in translation of basic science concepts to patients with cardiovascular disease. We provide a brief overview of the cardiovascular landscape and highlight the opportunities for imaging modalities to fulfill unmet biomedical needs.
In the first part of this thesis, we used multimodality imaging including USPIO-MRI, DCE-MRI and 18F-FDG PET/CT to disentangle the different aspects of plaque inflammation in the arterial vessel wall. Next, we established the presence of the systemic inflammatory response in patients following an acute myocardial infarction using 18F-DPA-714 PET/CT. At last, we performed a phase I clinical study and determined the safety and biodistribution of 99mTc-fucoidan, a novel radiotracer for P-selectin imaging.
Secondly, we focused on calcification in aortic valve stenosis as the disease process of interest. We highlighted the importance of atherogenic apoB-containing lipoproteins, including Lp(a), in the pathogenesis and epidemiology of aortic valve stenosis. Importantly, we used an innovative multimodality imaging approach to establish the significance of Lp(a) as a key driver of calcifying disease activity in aortic valve stenosis.
Thirdly, we investigated the potential role of infusible HDL mimetics for clinical applications. Our findings in patients with familial hypoalphalipoproteinemia do not indicate a role for HDL infusion in treating atherosclerosis, although we await the CSL-112 phase III trial for definitive conclusions. We used 89Zr-PET/CT imaging to establish the accumulation of exogenously administered HDL in atherosclerotic plaques, as well as esophageal tumors, highlighting the translational potential for HDL as a nanomedicine platform.
Document type PhD thesis
Language English
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