Open AccessEvaluating the Prognostic Value of Positron‐Emission Tomography Myocardial Perfusion Imaging Using Automated Software to Calculate Perfusion Defect Size
Author(s) -
Williams Brent A.,
Dorn Joan M.,
LaMonte Michael J.,
Donahue Richard P.,
Trevisan Maurizio,
Leonard Deborah A.,
Greene Robert S.,
Merhige Michael E.
Publication year - 2012
Publication title -
clinical cardiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.263
H-Index - 72
eISSN - 1932-8737
pISSN - 0160-9289
DOI - 10.1002/clc.22058
Subject(s) - medicine , perfusion , coronary artery disease , myocardial perfusion imaging , positron emission tomography , cardiac pet , radiology , cardiology , cad , nuclear medicine , perfusion scanning , engineering drawing , engineering
Background: Myocardial perfusion imaging by positron‐emission tomography (PET MPI) is regarded as a valid technique for the diagnosis of coronary artery disease (CAD), but the incremental prognostic value of PET MPI among individuals with known or suspected CAD is not firmly established. Hypothesis: Myocardial perfusion defect sizes as measured by PET MPI using automated software will provide incremental prognostic value for cardiac and all‐cause mortality. Methods: This study included 3739 individuals who underwent rest‐stress rubidium‐82 PET MPI for the evaluation of known or suspected CAD. Rest, stress, and stress‐induced myocardial perfusion defect sizes were determined objectively by automated computer software. Study participants were followed for a mean of 5.2 years for cardiac and all‐cause mortality. Cox proportional hazards models were developed to evaluate the incremental prognostic value of PET MPI. Results: A strong correlation was observed between perfusion defect sizes assessed visually and by automated software ( r = 0.76). After adjusting for cardiac risk factors, known CAD, noncoronary vascular disease, and use of cardioprotective medications, stress perfusion defect size was strongly associated with cardiac death ( P < 0.001). Rest perfusion defects demonstrated a stronger association with cardiac death ( P < 0.001) than stress‐induced perfusion defects ( P = 0.01), yet both were highly significant. Similar patterns held for all‐cause death. Conclusions: The current study is the largest to date demonstrating PET MPI provides incremental prognostic value among individuals with known or suspected CAD. Automated calculation of perfusion defect sizes may provide valuable supplementary information to visual assessment. This work was partially funded by a predoctoral fellowship grant awarded to the first author by the American Heart Association's Founders' Affiliate. Additional funding was provided by Niagara Falls Memorial Medical Center, Positron Corporation, the University at Buffalo, and Niagara University. The authors have no other funding, financial relationships, or conflicts of interest to disclose.