Affiliation:
1. Nuclear Medicine Laboratory, University Hospital of Larissa, University of Thessaly, Mezourlo, 41110 Larissa, Greece
2. Medical Physics Laboratory, University Hospital of Larissa, University of Thessaly, Mezourlo, 41110 Larissa, Greece
3. Department of Cardiology, University Hospital of Larissa, University of Thessaly, Mezourlo, 41110 Larissa, Greece
Abstract
Background and Objectives: Automated methods for the analysis of myocardial perfusion studies have been incorporated into clinical practice, but they are currently used as adjuncts to the visual interpretation. We aimed to investigate the role of automated measurements of summed stress score (SSS), summed rest score (SRS), and summed difference score (SDS) as long-term prognostic markers of morbidity and mortality, in comparison to the prognostic value of expert reading. Materials and Methods: The study was conducted at the Nuclear Medicine Laboratory of the University of Thessaly, in Larissa, Greece. A total of 378 consecutive patients with known or suspected coronary artery disease were enrolled in the study. All participants were referred to our laboratory for the performance of stress/rest myocardial perfusion single photon emission computed tomography. Automated measurements of SSS, SRS, and SDS were obtained by Emory Cardiac Toolbox (ECTb (Version 3.0), Emory University, Atlanta, GA, USA), Myovation (MYO, Xeleris version 3.05, GE Healthcare, Chicago, IL, USA), and Quantitative Perfusion SPECT (QPS (Version 4.0), Cedars-Sinai Medical Center, Los Angeles, CA, USA) software packages. Follow-up data were recorded after phone contacts, as well as through review of hospital records. Results: Expert scoring of SSS and SDS had significantly greater prognostic ability in comparison to all software packages (p < 0.001 for all comparisons). Similarly, ECTb-obtained SRS measurements had significantly lower prognostic ability in comparison to expert scoring (p < 0.001), while expert scoring of SRS showed significantly higher prognostic ability compared to MYO (p = 0.018) and QPS (p < 0.001). Conclusions: Despite the useful contribution of automated analyses in the interpretation of myocardial perfusion studies, expert reading should continue to have a crucial role, not only in clinical decision making, but also in the assessment of prognosis.