title: Atherosclerosis imaging and the Canadian Atherosclerosis Imaging Network.
abstract: Atherosclerosis exacts a large toll on society in the form of cardiovascular morbidity, mortality, and resource use and is exacerbated by the epidemics of obesity and diabetes. Consequently, there is a critical need for more-effective methods of diagnosis, treatment, and prevention of the complications of atherosclerosis. Careful and well-conducted large population studies are needed in order to truly understand the natural history of the disease, its imaging biomarkers, and their links to patient outcomes. The Canadian Atherosclerosis Imaging Network (CAIN) is a unique research network funded by the Canadian Institutes of Health Research and the Canada Foundation for Innovation and designed to address these needs and to enable large population-based imaging studies. The central objective of CAIN is to move innovations in imaging toward their broad application in clinical research and clinical practice for the improved evaluation of cardiac and neurologic vascular disease. CAIN is established as an international resource for studying the natural history, progression, and regression of atherosclerosis, as well as novel therapeutic interventions aimed at atherosclerosis. The network represents Canada's leading atherosclerosis imaging experts, embodying both basic imaging science and clinical imaging research. The network is improving methods of detection and treatment of atherosclerosis and, through a better understanding of the underlying disease itself, improving strategies for disease prevention. The benefits are expected to appear in the next 2 to 3 years. CAIN will drive innovation in imaging technology within the field of cardiology and neurology and improve health outcomes in Canada and worldwide.
authors.affiliation: Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada. jean-claude.tardif@icm-mhi.org
authors.forename: Jean-Claude
authors.initials: JC
authors.lastname: Tardif
authors.forename: J David
authors.initials: JD
authors.lastname: Spence
authors.forename: Therese M
authors.initials: TM
authors.lastname: Heinonen
authors.forename: Alan
authors.initials: A
authors.lastname: Moody
authors.forename: Josephine
authors.initials: J
authors.lastname: Pressacco
authors.forename: Richard
authors.initials: R
authors.lastname: Frayne
authors.forename: Philippe
authors.initials: P
authors.lastname: L'allier
authors.forename: Benjamin J W
authors.initials: BJ
authors.lastname: Chow
authors.forename: Matthias
authors.initials: M
authors.lastname: Friedrich
authors.forename: Sandra E
authors.initials: SE
authors.lastname: Black
authors.forename: Aaron
authors.initials: A
authors.lastname: Fenster
authors.forename: Brian
authors.initials: B
authors.lastname: Rutt
authors.forename: Rob
authors.initials: R
authors.lastname: Beanlands
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods; D050197:Atherosclerosis / Q000175:diagnosis* / Q000517:prevention & control / Q000628:therapy; D002170:Canada; D002339:Carotid Arteries / Q000000981:diagnostic imaging / Q000473:pathology; D003287:Contrast Media; D003952:Diagnostic Imaging / Q000379:methods*; D019560:Echocardiography, Three-Dimensional / Q000379:methods; D019317:Evidence-Based Medicine; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D064847:Multimodal Imaging / Q000379:methods; D049268:Positron-Emission Tomography; D012044:Regression Analysis; D012107:Research Design; D018570:Risk Assessment; D012307:Risk Factors; D014057:Tomography, X-Ray Computed / Q000379:methods
chemical_list: D003287:Contrast Media