Please use this identifier to cite or link to this item: http://elea.unisa.it/xmlui/handle/10556/4477
Title: Stress-first single photon emission computed myocardial perfusion imaging
Authors: Aquino, Carmen Imma
Scarano, Mariella
Squame, Fiorenzo
Casaburi, Giorgio
Nori, Stefania Lucia
Pace, Leonardo
Keywords: Myocardial perfusion imaging;Coronary artery disease;Radiation dose;Stress-first
Issue Date: 2016
Citation: Aquino C, Scarano M, Squame F, Casaburi G, Nori S L, Pace L. Stress-first single photon emission computed myocardial perfusion imaging. Translational Medicine @ UniSa 2016, 15(7): 48-52.
Abstract: Background. Myocardial perfusion imaging (MPI) with single photon emission tomography (SPET) is widely used in coronary artery disease evaluation. Recently major dosimetric concerns have arisen. The aim of this study was to evaluate if a pre-test scoring system could predict the results of stress SPET MPI, thus avoiding two radionuclide injections. Methods. All consecutive patients (n=309) undergoing SPET MPI during the first 6 months of 2014 constituted the study group. The scoring system is based on these characteristics: age >65 years (1 point), diabetes (2 points), typical chest pain (2 points), congestive heart failure (3 points), abnormal ECG (4 points), male gender (4 points), and documented previous CAD (5 points). The patients were divided on the basis of the prediction score into 3 classes of risk for an abnormal stress-first protocol. Results. An abnormal stress SPET MPI was present in 7/31 patients (23%) with a low risk score, in 24/90 (27%) with an intermediate score risk, and in 124/188 (66%) with an high score risk. ROC curve analysis showed good prediction of abnormal stress MPI. Conclusions. Our results suggest an appropriate use of a pre-test clinical prediction formula of abnormal stress MPI in a routine clinical setting.
URI: http://www.translationalmedicine.unisa.it/index
http://elea.unisa.it:8080/xmlui/handle/10556/4477
http://dx.doi.org/10.14273/unisa-2675
ISSN: 2239-9747
Appears in Collections:Translational Medicine @ UniSa. Volume 15 (may. - aug. 2016)

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