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Atherosclerotic inflammation imaging using somatostatin receptor-2 positron emission tomography 10.17863/CAM.15485 Tarkin, Jason Michael Rudd, James Systemic inflammatory networks and local signaling cascades trigger culprit pathogenic mechanisms relating clinical cardiovascular disease (CVD) risk factors to atherosclerotic plaque progression and rupture. Imaging vascular inflammation affords a valuable marker of atherosclerotic disease activity to reveal important mechanistic insights for CVD research, to quantify early anti-inflammatory effects of new atherosclerosis drugs, and, ultimately, to help improve CVD risk prediction. While carotid, aortic, and peripheral arterial inflammation can be measured by 18F-fluorodeoxyglucose (FDG) PET-computed tomography (CT), as a glucose analog, high 18F-FDG signal spillover owing to physiological myocardial muscle metabolism prevents reliable coronary interpretation. Lack of cell specificity, and the influence of hypoxia on 18F-FDG uptake within macrophages and other plaque cells, are further limitations that drive the search for an alternative PET tracer for imaging inflammation in atherosclerosis. Up-regulation of the G-protein coupled receptor somatostatin receptor subtype-2 (SST2) occurs on the cell surface of activated macrophages. The central hypothesis tested in this thesis is that vascular SST2 PET imaging using 68Ga-DOTATATE might offer a more accurate marker of macrophage inflammation than 18F-FDG, with superior coronary imaging and therefore better power to discriminate high-risk vs. low-risk atherosclerotic lesions. Comprehensive molecular, histological and clinical evaluation of this experimental CVD imaging biomarker was undertaken, including a prospective clinical study with head-to-head comparison to 18F-FDG in coronary, carotid, and aortic vasculature. In vitro data showed that (i) target SSTR2 gene expression occurred in “pro-inflammatory” M1 macrophages, (ii) specific 68Ga-DOTATATE ligand binding to SST2 receptors occurred in CD68-positive macrophage-rich carotid plaque regions, and (iii) and carotid SSTR2 mRNA was highly correlated with both the pan-macrophage marker CD68 and in vivo 68Ga-DOTATATE PET signals. In clinical imaging, increased 68Ga-DOTATATE inflammatory signals correctly identified culprit vs. non-culprit arteries in patients with acute coronary syndrome and transient ischemic attack/stroke. 68Ga-DOTATATE also demonstrated good diagnostic accuracy for high-risk coronary CT features, and strong correlations with clinical CVD risk factors and 18F-FDG-defined vascular inflammation. While 18F-FDG also differentiated culprit vs. non-culprit carotid and high-risk coronary arteries, myocardial 18F-FDG overspill rendered coronary scans uninterpretable in most patients. In contrast, 68Ga-DOTATATE allowed unimpeded coronary interpretation in all patients. Findings of this thesis provide compelling evidence, from gene, to cell, to plaque, to patient, that SST2 PET imaging using 68Ga-DOTATATE provides a quantifiable marker of macrophage-related atherosclerotic inflammation and disease activity. Further studies are needed to establish whether 68Ga-DOTATATE PET can improve CVD risk prediction when added to current clinical methods, or offer a novel imaging platform to rapidly test the anti-inflammatory capacity of emerging atherosclerosis drugs. Broader translational applications of 68Ga-DOTATATE PET include possible use in diagnosis and therapeutic monitoring of vasculitis, endocarditis, myocarditis, and other manifestations of cardiovascular inflammation. University of Cambridge 2017-11-01 Thesis Doctoral Doctor of Philosophy (PhD) en Wellcome Trust https://www.repository.cam.ac.uk/handle/1810/269285 https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/50780d0a-4872-423c-98aa-3065b84b482c/download 87eda9de84448d1f82354d60eee3eb5f https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/54f96700-ec9d-4e97-acd0-a28c03d8fff5/download 0328c473a3b028e94dad1270fc064613 https://www.rioxx.net/licenses/all-rights-reserved/ atherosclerosis inflammation somatostatin receptor-2 positron emission tomography