title: The Quantitative Science of Evaluating Imaging Evidence.
abstract: Cardiovascular diagnostic imaging tests are increasingly used in everyday clinical practice, but are often imperfect, just like any other diagnostic test. The performance of a cardiovascular diagnostic imaging test is usually expressed in terms of sensitivity and specificity compared with the reference standard (gold standard) for diagnosing the disease. However, evidence-based application of a diagnostic test also requires knowledge about the pre-test probability of disease, the benefit of making a correct diagnosis, the harm caused by false-positive imaging test results, and potential adverse effects of performing the test itself. To assist in clinical decision making regarding appropriate use of cardiovascular diagnostic imaging tests, we reviewed quantitative concepts related to diagnostic performance (e.g., sensitivity, specificity, predictive values, likelihood ratios), as well as possible biases and solutions in diagnostic performance studies, Bayesian principles, and the threshold approach to decision making.
authors.affiliation: Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
authors.forename: Tessa S S
authors.initials: TS
authors.lastname: Genders
authors.affiliation: Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York.
authors.forename: Bart S
authors.initials: BS
authors.lastname: Ferket
authors.affiliation: Department of Epidemiology and Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts. Electronic address: m.hunink@erasmusmc.nl.
authors.forename: M G Myriam
authors.initials: MG
authors.lastname: Hunink
mesh_terms: D057791:Cardiac Imaging Techniques; D002318:Cardiovascular Diseases / Q000000981:diagnostic imaging* / Q000628:therapy; D000066491:Clinical Decision-Making; D003661:Decision Support Techniques; D019317:Evidence-Based Medicine; D006801:Humans; D011237:Predictive Value of Tests; D011379:Prognosis; D015203:Reproducibility of Results
keywords: cardiovascular diagnostic imaging; coronary artery disease; diagnostic performance