Literature DB >> 28279374

The Quantitative Science of Evaluating Imaging Evidence.

Tessa S S Genders1, Bart S Ferket2, M G Myriam Hunink3.   

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.
Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Keywords:  cardiovascular diagnostic imaging; coronary artery disease; diagnostic performance

Mesh:

Year:  2017        PMID: 28279374     DOI: 10.1016/j.jcmg.2016.12.010

Source DB:  PubMed          Journal:  JACC Cardiovasc Imaging        ISSN: 1876-7591


  3 in total

1.  Coronary calcium score improves the estimation for pretest probability of obstructive coronary artery disease and avoids unnecessary testing in individuals at low extreme of traditional risk factor burden: validation and comparison of CONFIRM score and genders extended model.

Authors:  Minghui Wang; Yujie Liu; Xiujun Zhou; Jia Zhou; Hong Zhang; Ying Zhang
Journal:  BMC Cardiovasc Disord       Date:  2018-08-29       Impact factor: 2.298

2.  Merit of test: Perspective of information economics.

Authors:  Andrea Galeotti; Jakub Steiner; Paolo Surico
Journal:  Health Policy Technol       Date:  2020-09-03

3.  Visualizing the Invisible: Invisible Waste in Diagnostic Imaging.

Authors:  Bjørn Hofmann; Eivind Richter Andersen; Elin Kjelle
Journal:  Healthcare (Basel)       Date:  2021-12-07
  3 in total

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