Michaela M Hell1, Xiaowei Ding2, Mathieu Rubeaux3, Piotr Slomka4, Heidi Gransar5, Demetri Terzopoulos6, Sean Hayes7, Mohamed Marwan8, Stephan Achenbach9, Daniel S Berman10, Damini Dey11. 1. Department of Cardiology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: michaela.hell@uk-erlangen.de. 2. Computer Science Department, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, CA, USA. Electronic address: sjtu.xiaowei@gmail.com. 3. Cedars-Sinai Medical Center, Departments of Imaging and Medicine, Division of Cardiology and the Cedars-Sinai Heart Institute, Los Angeles, CA, USA. Electronic address: Mathieu.Rubeaux@cshs.org. 4. Cedars-Sinai Medical Center, Departments of Imaging and Medicine, Division of Cardiology and the Cedars-Sinai Heart Institute, Los Angeles, CA, USA. Electronic address: piotr.slomka@cshs.org. 5. Cedars-Sinai Medical Center, Departments of Imaging and Medicine, Division of Cardiology and the Cedars-Sinai Heart Institute, Los Angeles, CA, USA. Electronic address: heidi.gransar@cshs.org. 6. Computer Science Department, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, CA, USA. Electronic address: dt@cs.ucla.edu. 7. Cedars-Sinai Medical Center, Departments of Imaging and Medicine, Division of Cardiology and the Cedars-Sinai Heart Institute, Los Angeles, CA, USA. Electronic address: sean.hayes@cshs.org. 8. Department of Cardiology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: mohamed.marwan@uk-erlangen.de. 9. Department of Cardiology, University of Erlangen-Nuremberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: stephan.achenbach@uk-erlangen.de. 10. Cedars-Sinai Medical Center, Departments of Imaging and Medicine, Division of Cardiology and the Cedars-Sinai Heart Institute, Los Angeles, CA, USA. Electronic address: daniel.berman@cshs.org. 11. Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA. Electronic address: damini.dey@cshs.org.
Abstract
BACKGROUND: Epicardial adipose tissue (EAT) volume is associated with plaque formation and cardiovascular event risk, its density may reflect tissue composition and metabolic activity. OBJECTIVES: Global and regional associations between EAT volume and density, ischemia and coronary calcium were investigated using a novel automatic quantitative measurement software. METHODS: 71 patients with an intermediate pre-test probability for coronary artery disease and inducible ischemia by SPECT were matched to two same-gender controls (total of 213 patients, 90% male, age 60 ± 10 years). Non-contrast CT for assessment of EAT volume, density (in Hounsfield Unit [HU]) and coronary calcium score (CCS) was performed. RESULTS: Global EAT volume was significantly increased in ischemic patients compared to controls (96 ± 49 vs. 82 ± 36 cm(3), p = 0.04), density showed no significant difference (-75.6 ± 4.3 vs. -75.1 ± 4.1HU, p = 0.63). EAT volume and density differed significantly between coronary territories (LAD: 37 ± 18 cm(3), -77.8 ± 4.5HU; LCx: 16 ± 9 cm(3), -73.9 ± 4.1HU; RCA: 36 ± 17 cm(3), -71.7 ± 4.8HU, p < 0.001). For regional ischemia, only LCx territory showed a significantly higher EAT volume (18 ± 8 vs. 16 ± 9 cm(3), p = 0.048). Multivariable logistic regression revealed a significant association with ischemia for EAT volume (OR 2.09 (1.0; 4.3), p = 0.049) and CCS (OR 1.43 (1.1; 1.9), p = 0.006). EAT volume significantly improved discrimination of ischemia over CCS (Integrated Discrimination Improvement: 3.5%, 95%CI: 1.1-6.1%, p = 0.004). Hypertension was the only risk factor significantly influencing EAT volume and density (98 ± 48 vs. 78 ± 31 cm(3), p = 0.002, -76.0 ± 4.1 vs. -74.5 ± 4.1 HU, p = 0.01). CONCLUSIONS: EAT volume is associated with myocardial ischemia and improves the discriminative power for independent ischemia prediction over CCS. In hypertensive patients, EAT is characterized by lower density and higher volumes.
BACKGROUND: Epicardial adipose tissue (EAT) volume is associated with plaque formation and cardiovascular event risk, its density may reflect tissue composition and metabolic activity. OBJECTIVES: Global and regional associations between EAT volume and density, ischemia and coronary calcium were investigated using a novel automatic quantitative measurement software. METHODS: 71 patients with an intermediate pre-test probability for coronary artery disease and inducible ischemia by SPECT were matched to two same-gender controls (total of 213 patients, 90% male, age 60 ± 10 years). Non-contrast CT for assessment of EAT volume, density (in Hounsfield Unit [HU]) and coronary calcium score (CCS) was performed. RESULTS: Global EAT volume was significantly increased in ischemicpatients compared to controls (96 ± 49 vs. 82 ± 36 cm(3), p = 0.04), density showed no significant difference (-75.6 ± 4.3 vs. -75.1 ± 4.1HU, p = 0.63). EAT volume and density differed significantly between coronary territories (LAD: 37 ± 18 cm(3), -77.8 ± 4.5HU; LCx: 16 ± 9 cm(3), -73.9 ± 4.1HU; RCA: 36 ± 17 cm(3), -71.7 ± 4.8HU, p < 0.001). For regional ischemia, only LCx territory showed a significantly higher EAT volume (18 ± 8 vs. 16 ± 9 cm(3), p = 0.048). Multivariable logistic regression revealed a significant association with ischemia for EAT volume (OR 2.09 (1.0; 4.3), p = 0.049) and CCS (OR 1.43 (1.1; 1.9), p = 0.006). EAT volume significantly improved discrimination of ischemia over CCS (Integrated Discrimination Improvement: 3.5%, 95%CI: 1.1-6.1%, p = 0.004). Hypertension was the only risk factor significantly influencing EAT volume and density (98 ± 48 vs. 78 ± 31 cm(3), p = 0.002, -76.0 ± 4.1 vs. -74.5 ± 4.1 HU, p = 0.01). CONCLUSIONS: EAT volume is associated with myocardial ischemia and improves the discriminative power for independent ischemia prediction over CCS. In hypertensivepatients, EAT is characterized by lower density and higher volumes.
Authors: Markus Goeller; Stephan Achenbach; Mohamed Marwan; Mhairi K Doris; Sebastien Cadet; Frederic Commandeur; Xi Chen; Piotr J Slomka; Heidi Gransar; J Jane Cao; Nathan D Wong; Moritz H Albrecht; Alan Rozanski; Balaji K Tamarappoo; Daniel S Berman; Damini Dey Journal: J Cardiovasc Comput Tomogr Date: 2017-11-24
Authors: Amir Abbas Mahabadi; Bastian Balcer; Iryna Dykun; Michael Forsting; Thomas Schlosser; Gerd Heusch; Tienush Rassaf Journal: PLoS One Date: 2017-08-24 Impact factor: 3.240
Authors: Andrew Lin; Nathan D Wong; Aryabod Razipour; Priscilla A McElhinney; Frederic Commandeur; Sebastien J Cadet; Heidi Gransar; Xi Chen; Stephanie Cantu; Robert J H Miller; Nitesh Nerlekar; Dennis T L Wong; Piotr J Slomka; Alan Rozanski; Balaji K Tamarappoo; Daniel S Berman; Damini Dey Journal: Cardiovasc Diabetol Date: 2021-01-29 Impact factor: 9.951