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Korean Journal of Radiology ; : 871-880, 2017.
Article in English | WPRIM | ID: wpr-191319

ABSTRACT

In 2010, the Asian Society of Cardiovascular Imaging (ASCI) provided recommendations for cardiac CT and MRI, and this document reflects an update of the 2010 ASCI appropriate use criteria (AUC). In 2016, the ASCI formed a new working group for revision of AUC for noninvasive cardiac imaging. A major change that we made in this document is the rating of various noninvasive tests (exercise electrocardiogram, echocardiography, positron emission tomography, single-photon emission computed tomography, radionuclide imaging, cardiac magnetic resonance, and cardiac computed tomography/angiography), compared side by side for their applications in various clinical scenarios. Ninety-five clinical scenarios were developed from eight selected pre-existing guidelines and classified into four sections as follows: 1) detection of coronary artery disease, symptomatic or asymptomatic; 2) cardiac evaluation in various clinical scenarios; 3) use of imaging modality according to prior testing; and 4) evaluation of cardiac structure and function. The clinical scenarios were scored by a separate rating committee on a scale of 1–9 to designate appropriate use, uncertain use, or inappropriate use according to a modified Delphi method. Overall, the AUC ratings for CT were higher than those of previous guidelines. These new AUC provide guidance for clinicians choosing among available testing modalities for various cardiac diseases and are also unique, given that most previous AUC for noninvasive imaging include only one imaging technique. As cardiac imaging is multimodal in nature, we believe that these AUC will be more useful for clinical decision making.


Subject(s)
Humans , Area Under Curve , Asian People , Clinical Decision-Making , Consensus , Coronary Artery Disease , Echocardiography , Electrocardiography , Heart Diseases , Magnetic Resonance Imaging , Methods , Positron-Emission Tomography , Radionuclide Imaging , Tomography, Emission-Computed
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