scholarly journals Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects

2018 ◽  
Vol 12 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Markus Goeller ◽  
Stephan Achenbach ◽  
Mohamed Marwan ◽  
Mhairi K. Doris ◽  
Sebastien Cadet ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Epicardial Adipose Tissue ◽  
Subclinical Atherosclerosis ◽  
Major Adverse Cardiac Events ◽  
Cardiac Events ◽  
Tissue Density ◽  
Adverse Cardiac Events ◽  
Asymptomatic Subjects

scholarly journals Pericoronary fat inflammation and Major Adverse Cardiac Events (MACE) in prediabetic patients with acute myocardial infarction: effects of metformin

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Celestino Sardu ◽  
Nunzia D’Onofrio ◽  
Michele Torella ◽  
Michele Portoghese ◽  
Francesco Loreni ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Adipose Tissue ◽  
Artery Bypass ◽  
Major Adverse Cardiac Events ◽  
Cardiac Events ◽  
Metformin Therapy ◽  
Adverse Cardiac Events ◽  
Factor Α

Abstract Background/objectives Pericoronary adipose tissue inflammation might lead to the development and destabilization of coronary plaques in prediabetic patients. Here, we evaluated inflammation and leptin to adiponectin ratio in pericoronary fat from patients subjected to coronary artery bypass grafting (CABG) for acute myocardial infarction (AMI). Furthermore, we compared the 12-month prognosis of prediabetic patients compared to normoglycemic patients (NG). Finally, the effect of metformin therapy on pericoronary fat inflammation and 12-months prognosis in AMI-prediabetic patients was also evaluated. Methods An observational prospective study was conducted on patients with first AMI referred for CABG. Participants were divided in prediabetic and NG-patients. Prediabetic patients were divided in two groups; never-metformin-users and current-metformin-users receiving metformin therapy for almost 6 months before CABG. During the by-pass procedure on epicardial coronary portion, the pericoronary fat was removed from the surrounding stenosis area. The primary endpoints were the assessments of Major-Adverse-Cardiac-Events (MACE) at 12-month follow-up. Moreover, inflammatory tone was evaluated by measuring pericoronary fat levels of tumor necrosis factor-α (TNF-α), sirtuin 6 (SIRT6), and leptin to adiponectin ratio. Finally, inflammatory tone was correlated to the MACE during the 12-months follow-up. Results The MACE was 9.1% in all prediabetic patients and 3% in NG-patients. In prediabetic patients, current-metformin-users presented a significantly lower rate of MACE compared to prediabetic patients never-metformin-users. In addition, prediabetic patients showed higher inflammatory tone and leptin to adiponectin ratio in pericoronary fat compared to NG-patients (P < 0.001). Prediabetic never-metformin-users showed higher inflammatory tone and leptin to adiponectin ratio in pericoronary fat compared to current-metformin-users (P < 0.001). Remarkably, inflammatory tone and leptin to adiponectin ratio was significantly related to the MACE during the 12-months follow-up. Conclusion Prediabetes increase inflammatory burden in pericoronary adipose tissue. Metformin by reducing inflammatory tone and leptin to adiponectin ratio in pericoronary fat may improve prognosis in prediabetic patients with AMI. Trial registration Clinical Trial NCT03360981, Retrospectively Registered 7 January 2018

scholarly journals METABOLIC SYNDROME AND AUTOMATED EPICARDIAL ADIPOSE TISSUE MEASURES PREDICT LONG-TERM RISK OF CARDIAC EVENTS IN ASYMPTOMATIC SUBJECTS

2020 ◽  
Vol 75 (11) ◽  
pp. 1717
Author(s):  
Andrew Lin ◽  
Nathan D. Wong ◽  
Frederic Commandeur ◽  
Sebastien Cadet ◽  
Heidi Gransar ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Adipose Tissue ◽  
Epicardial Adipose Tissue ◽  
Cardiac Events ◽  
Asymptomatic Subjects

scholarly journals DeepFat: Deep Learning Segmentation and Quantification Method for Assessing Epicardial Adipose Tissue in CT Calcium Score Scans

2021 ◽  
Author(s):  
Ammar Hoori ◽  
Tao Hu ◽  
Juhwan Lee ◽  
Sadeer Al-Kindi ◽  
Sanjay Rajagopalan ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Deep Learning ◽  
Human Error ◽  
Epicardial Adipose Tissue ◽  
Calcium Score ◽  
Automatic Assessment ◽  
Cardiac Events ◽  
Look Ahead ◽  
Adverse Cardiac Events ◽  
Artery Disease

Abstract Epicardial adipose tissue volume (EAT) has been linked to coronary artery disease and the risk of major adverse cardiac events. As manual quantification of EAT is time-consuming, requires specialized training, and is prone to human error, we developed a method (DeepFat) for the automatic assessment of EAT on non-contrast low-dose CT calcium score images using deep learning. We segmented the tissue enclosed by the pericardial sac on axial slices, using two innovations. First, we applied a HU‑attention-window with a window/level 350/40-HU to draw attention to the sac and reduce numerical errors. Second, we applied look ahead slab-of-slices with bisection (“bisect”) in which we split the heart into halves and sequenced the lower half from bottom-to-middle and the upper half from top-to-middle, thereby presenting an always increasing curvature of the sac to the network. EAT volume was obtained by thresholding voxels within the sac in the fat window (-190/-30-HU). Compared to manual segmentation, our algorithm gave excellent results with volume Dice=88.52%±3.3, slice Dice=87.70%±7.5, EAT error=0.5%±8.1, and R=98.52%(p<0.001). HU-attention-window and bisect improved Dice volume scores by 0.49% and 3.2% absolute, respectively. Extensive augmentation improved results. Variability between analysts was comparable to variability with DeepFat. Results compared favorably to those of previous publications.

scholarly journals Prognostic Value of Systemic Immune-Inflammation Index for Major Adverse Cardiac Events and Mortality in Severe Aortic Stenosis Patients after TAVI

Medicina ◽  
2021 ◽  
Vol 57 (6) ◽  
pp. 588
Author(s):  
Aydin Rodi Tosu ◽  
Muhsin Kalyoncuoglu ◽  
Halil İbrahim Biter ◽  
Sinem Cakal ◽  
Murat Selcuk ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Prognostic Value ◽  
Major Adverse Cardiac Events ◽  
Cardiac Events ◽  
Short Term ◽  
Cox Regression Analysis ◽  
Adverse Cardiac Events ◽  
All Cause Mortality ◽  
Auc Value ◽  
Immune Inflammation

Background and objectives: In this study, we aimed to evaluate whether the systemic immune-inflammation index (SII) has a prognostic value for major adverse cardiac events (MACEs), including stroke, re-hospitalization, and short-term all-cause mortality at 6 months, in aortic stenosis (AS) patients who underwent transcatheter aortic valve implantation (TAVI). Materials and Methods: A total of 120 patients who underwent TAVI due to severe AS were retrospectively included in our study. The main outcome of the study was MACEs and short-term all-cause mortality at 6 months. Results: The SII was found to be higher in TAVI patients who developed MACEs than in those who did not develop them. Multivariate Cox regression analysis revealed that the SII (HR: 1.002, 95%CI: 1.001–1.003, p < 0.01) was an independent predictor of MACEs in AS patients after TAVI. The optimal value of the SII for MACEs in AS patients following TAVI was >1.056 with 94% sensitivity and 96% specificity (AUC (the area under the curve): 0.960, p < 0.01). We noted that the AUC value of SII in predicting MACEs was significantly higher than the AUC value of the C-reactive protein (AUC: 0.960 vs. AUC: 0.714, respectively). Conclusions: This is the first study to show that high pre-procedural SII may have a predictive value for MACEs and short-term mortality in AS patients undergoing TAVI.

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