[Predictive value of left ventricular ejection fraction reserve assessed by SPECT G-MPI for major adverse cardiovascular event in patients with coronary artery disease].

Objective: To evaluate the prognostic value of left ventricular ejection fraction (LVEF) reserve assessed by gated SPECT myocardial perfusion imaging (SPECT G-MPI) for major adverse cardiovascular event (MACE) in patients with coronary artery disease. Methods: This is a retrospective cohort study. From January 2017 to December 2019, patients with coronary artery disease and confirmed myocardial ischemia by stress and rest SPECT G-MPI, and underwent coronary angiography within 3 months were enrolled. The sum stress score (SSS) and sum resting score (SRS) were analyzed by the standard 17-segment model, and the sum difference score (SDS, SDS=SSS-SRS) was calculated. The LVEF at stress and rest were analyzed by 4DM software. The LVEF reserve (ΔLVEF) was calculated (ΔLVEF=stress LVEF-rest LVEF). The primary endpoint was MACE, which was obtained by reviewing the medical record system or by telephone follow-up once every twelve months. Patients were divided into MACE-free and MACE groups. Spearman correlation analysis was used to analyze the correlation between ΔLVEF and all MPI parameters. Cox regression analysis was used to analyze the independent factors of MACE, and the optimal SDS cutoff value for predicting MACE was determined by receiver operating characteristic curve (ROC). Kaplan-Meier survival curves were plotted to compare the difference in the incidence of MACE between different SDS groups and different ΔLVEF groups. Results: A total of 164 patients with coronary artery disease [120 male; age (58.6±10.7) years] were included. The average follow-up time was (26.5±10.4) months, and a total of 30 MACE were recorded during follow-up. Multivariate Cox regression analysis showed that SDS (HR=1.069, 95%CI: 1.005-1.137, P=0.035) and ΔLVEF (HR=0.935, 95%CI: 0.878-0.995, P=0.034) were independent predictors of MACE. According to ROC curve analysis, the optimal cut-off to predict MACE was a SDS of 5.5 with an area under the curve of 0.63 (P=0.022). Survival analysis showed that the incidence of MACE was significantly higher in the SDS≥5.5 group than in the SDS<5.5 group (27.6% vs. 13.2%, P=0.019), but the incidence of MACE was significantly lower in the ΔLVEF≥0 group than in theΔLVEF<0 group (11.0% vs. 25.6%, P=0.022). Conclusions: LVEF reserve (ΔLVEF) assessed by SPECT G-MPI serves as an independent protective factor for MACE, while SDS is an independent risk predictor in patients with coronary artery disease. SPECT G-MPI is valuable for risk stratification by assessing myocardial ischemia and LVEF.

Quantification of late gadolinium enhancement cardiovascular MRI in patients with coronary artery chronic total occlusion.

AIM: To determine the most accurate and reproducible semi-automated greyscale thresholding technique for quantifying late gadolinium enhancement (LGE) in cardiovascular magnetic resonance imaging (CMRI), by using positron-emission tomography (PET) as the reference standard in patients with coronary artery chronic total occlusion (CTO). MATERIALS AND METHODS: LGE in CMRI, single-photon-emission computed tomography (SPECT), and PET were performed within 1 week in each of 63 patients with known CTO. The presence and quantity of LGE were determined with greyscale thresholds of 2, 4, 5, 6, and 8 standard deviations (SDs) above the mean signal intensity for normal remote myocardium and full width at half maximum (FWHM). The infarcted myocardium was delineated by PET. RESULTS: Sixty-three patients and 1,008 segments were analysed. Based on patient analysis, with PET as the reference standard, the 5 SD method yielded the strongest correlation (r=0.85, p<0.0001) compared with the 2 SDs (r=0.42), 4 SDs (r=0.73), 6 SDs (r=0.81), 8 SDs (r=0.71), and FWHM (r=0.69; p<0.001 for all comparisons). The 5 SDs threshold quantification showed high interobserver and intra-observer agreement (intraclass correlation coefficient [ICC]=0.90, p<0.0001; ICC=0.93, p<0.0001, respectively). CONCLUSIONS: Semi-automated LGE CMRI greyscale thresholding with 5 SDs above the mean signal intensity for normal remote myocardium yields the strongest correlation to the extent of LGE identified using PET and is highly reproducible in patients with CTO.

[Association between brain glucose metabolism and cardiac dysfunction in patients with ischemic heart disease undergoing (18)F-FDG PET/CT imaging].

Objective: To evaluate the relationship between the brain glucose metabolism and left ventricular function parameters, and to explore the cerebral glucose metabolism reduction regions in patients with ischemic heart disease (IHD). Methods: A total of 110 consecutive IHD patients who underwent gated (99)Tc(m)-sestamibi (MIBI) SPECT/CT myocardial perfusion imaging, gated (18)F-fluorodeoxyglucose (FDG) PET/CT myocardial and brain glucose metabolic imaging within three days in Beijing Anzhen Hospital from April 2016 to October 2017, were enrolled in this study. Left ventricular functional parameters of SPECT/CT and PET/CT including end-diastolic volume (EDV), end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) were analyzed by QGS software. Viable myocardium and myocardial infarction region were determined by 17-segment and 5 score system, and the ratio of viable myocardium and scar myocardium was calculated. According to the range of viable myocardium, the patients were divided into viable myocardium<10% group (n=44), viable myocardium 10%-<20% group (n=36) and viable myocardium≥20% group (n=30). Pearson correlation analysis was used to analyze the correlation between the range of viable myocardium and scar myocardium and the level of cerebral glucose metabolism. Brain glucose metabolism determined by the mean of standardized uptake value (SUV(mean)) was analyzed by SPM. The ratio of SUV(mean) in whole brain and SUV(mean) in cerebellum were calculated, namely taget/background ratio (TBR). Differences in cerebral glucose metabolism among various groups were analyzed by SPM. Results: There were 101 males, and age was (57±10) years in this cohort. The extent of viable myocardium and the extent of scar, LVEF evaluated by SPECT/CT and PET/CT were significantly correlated with TBR (r=0.280, r=-0.329, r=0.188, r=0.215 respectively,all P<0.05). TBR value was significantly lower in viable myocardium<10% group, compared with viable myocardium 10%-<20% group (1.25±0.97 vs. 1.32±0.17, P<0.05) and viable myocardium≥20% group (1.25±0.97 vs. 1.34±0.16, P<0.05). Furthermore, in comparison with viable myocardium≥20% group, the hypo-metabolic regions of viable myocardium<10% group were located in the precuneus, frontal lobe, postcentral gyrus, parietal lobe, temporal lobe, and so on. Conclusions: There is a correlation between impaired left ventricular function and brain glucose metabolism in IHD patients. In IHD patients with low myocardial viability, the level of glucose metabolism in the whole brain is decreased, especially in the brain functional areas related to cognitive function.

Comparison of cardiac MRI with PET for assessment of myocardial viability in patients with coronary chronic total occlusion.

AIM: To compare cardiac magnetic resonance imaging (MRI) and positron-emission tomography (PET) assessment of myocardial viability in patients with coronary chronic total occlusion (CTO). MATERIALS AND METHODS: Eighty patients with coronary CTO underwent cardiac MRI and PET. Cardiac MRI images were analysed using a 17-segment model, and late gadolinium enhancement (LGE) and wall motion were scored. PET was used to classify myocardial viability via myocardial perfusion and 18F-fluorodeoxyglucose, digital superscript uptake. RESULTS: With PET as the reference standard, the sensitivity of cardiac MRI in detecting myocardial viability was 95.3%, specificity was 87.5%, positive predictive value was 96.8%, negative predictive value was 84.2%, and accuracy was 93.8% on a per patient basis. The receiver operator characteristic curve was used to analyse the performance of cardiac MRI in the detection of myocardial viability on a per-patient basis and the area under the curve was 0.910 (95% confidence interval 0.805 to 1). Cardiac MRI had the highest sensitivity and specificity for differentiating viable and non-viable myocardium as defined by PET when the cut-off value of LGE was 50%. The motion consistency and correlation of cardiac MRI and PET were analysed and kappa was 0.788 (r=0.825; p<0.001). CONCLUSION: Compared with PET, cardiac MRI assessment of myocardial viability in patients with coronary CTO has high sensitivity, specificity, and accuracy. Therefore, cardiac MRI can be used as an important method for evaluating myocardial viability in coronary CTO patients.