Automated Analysis vs. Expert Reading in Nuclear Cardiology: Correlations with the Angiographic Score.

Background and Objectives: Myocardial perfusion imaging (MPI) has an important role in the non-invasive investigation of coronary artery disease. The interpretation of MPI studies is mainly based on the visual evaluation of the reconstructed images, while automated quantitation methods may add useful data for each patient. However, little evidence is currently available regarding the actual incremental clinical diagnostic performance of automated MPI analysis. In the present study, we aimed to assess the correlation between automated measurements of Summed Stress Score (SSS), Summed Rest Score (SRS) and Summed Difference Score (SDS), with the corresponding expert reading values, using coronary angiography as the gold standard. Materials and Methods: The study was conducted at the Nuclear Medicine Laboratory of the University Hospital of Larissa, Larissa, Greece, οver an one-year period (January 2019-January 2020). 306 patients, with known or suspected coronary artery disease, were enrolled in the study. Each participant underwent a coronary angiography, prior to or after the scintigraphic study (within a three-month period). Either symptom-limited treadmill test, or pharmacologic testing using adenosine or regadenoson, was performed in all participants, and the scintigraphic studies were carried out using technetium 99m (99mTc) tetrofosmin (one-day stress/rest protocol). Coronary angiographies were scored according to a 4-point scoring system (angiographic score; O: normal study, 1: one-vessel disease, 2: two-vessel disease, 3: three-vessel disease). Moreover, automated measurements of SSS, SRS and SDS were derived by three widely available software packages (Emory Cardiac Toolbox, Myovation, Quantitative Perfusion SPECT). Results: Interclass Correlation Coefficients of SSS, SRS and SDS between expert reading and software packages were moderate to excellent. Visually defined SSS, SRS and SDS were significantly correlated with the corresponding results of all software packages. However, visually defined SSS, SRS and SDS were more strongly correlated with the angiographic score, indicating a better performance of expert reading when compared to automated analysis. Conclusions: Based on our results, visual evaluation continues to have a crucial role for the interpretation of MPI images. Software packages can provide automated measurements of several parameters, particularly contributing to the investigation of cases with ambiguous scintigraphic findings.

HPA axis responses to acute exercise differ in smokers and non-smokers.

Physical exercise has been proposed as an adjunct in addiction treatment, including tobacco cigarette smoking. The physiological and biochemical mechanisms that could be affected by physical exercise in smokers and that could help quit smoking have not been investigated yet. OBJECTIVE: To investigate whether the effects of acute exercise on smoking behavior and HPA axis activation in smokers are intensity-dependent. METHODS: Healthy, non-systematically exercising individuals [25 smokers (age: 33±1.4 years) and 10 non-smokers (age: 34±2.1 years)] underwent three trials [moderate intensity (MI), high intensity (HI) exercise, control (C)] in a counterbalanced order, after an overnight fast and smoking abstinence, separated by at least six days. MI involved cycling at 50-60% of Heart Rate Reserve (HRR) for 30 min, HI involved cycling at 65-75% HRR for 30 min, while in C participants rested for 30 min. Time till the first cigarette following each trial was recorded. Smoking urge was evaluated and blood samples, [analyzed for ß-endorphin (ß-E), adrenocorticotropic hormone (ACTH), cortisol and catecholamines], were obtained prior to and immediately after each trial. RESULTS: ß-E, ACTH, catecholamines and cortisol responses to exercise were intensity-dependent and differed in smokers and non-smokers. Resting ß-E levels were 2-2.5 times lower in smokers compared to non-smokers. HI resulted in increased ß-E levels in both groups, with smokers exhibiting similar levels to that observed in non-smokers. Although smoking urge did not change post-exercise in smokers, time till first cigarette increased following both MI (64.6%) and HI (77.9%) compared to C. CONCLUSIONS: HPA axis activation in response to exercise may differ between smokers and non-smokers. Smokers have lower resting levels of ß-E compared to non-smokers and, since HI exercise increases ß-E to similar levels to those of non-smokers and delays smoking, this may be used as an adjunct in smoking cessation.