Development of artificial intelligence in epicardial and pericoronary adipose tissue imaging: a systematic review

[11] Nakagawa M(2017)Role of epicardial adipose tissue in health and disease: a matter of fat? Compr Physiol 7 1051-73

[12] Hijiya N(2018)Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects J Cardiovasc Comput Tomogr 12 67-1078

[13] Moriyama M(2020)Difference in epicardial adipose tissue distribution between paroxysmal atrial fibrillation and coronary artery disease Heart Vessels 35 1070-510

[14] Shimada T(2018)Deep learning for lung cancer prognostication: a retrospective multi-cohort radiomics study PLoS Med 15 e1002711-310

[15] Miyamoto S(2018)Artificial intelligence in radiology Nat Rev Cancer 18 500-543

[16] Takahashi N(2003)Epicardial fat from echocardiography: a new method for visceral adipose tissue prediction Obes Res 11 304-446

[17] Antonopoulos AS(2005)Epicardial adipose tissue: anatomic, biomolecular and clinical relationships with the heart Nat Clin Pract Cardiovasc Med 2 536-2383

[18] Sanna F(2012)Radiomics: Extracting more information from medical images using advanced feature analysis Eur J Cancer 48 441-1565

[19] Sabharwal N(2020)Myocardial Infarction associates with a distinct pericoronary adipose tissue radiomic phenotype: a prospective case-control study JACC Cardiovasc Imaging 13 2371-1395

[20] Thomas S(2019)State-of-the-art deep learning in cardiovascular image analysis JACC Cardiovasc Imaging 12 1549-497

[11] Nakagawa M(2017)Role of epicardial adipose tissue in health and disease: a matter of fat? Compr Physiol 7 1051-73

[12] Hijiya N(2018)Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects J Cardiovasc Comput Tomogr 12 67-1078

[13] Moriyama M(2020)Difference in epicardial adipose tissue distribution between paroxysmal atrial fibrillation and coronary artery disease Heart Vessels 35 1070-510

[14] Shimada T(2018)Deep learning for lung cancer prognostication: a retrospective multi-cohort radiomics study PLoS Med 15 e1002711-310

[15] Miyamoto S(2018)Artificial intelligence in radiology Nat Rev Cancer 18 500-543

[16] Takahashi N(2003)Epicardial fat from echocardiography: a new method for visceral adipose tissue prediction Obes Res 11 304-446

[17] Antonopoulos AS(2005)Epicardial adipose tissue: anatomic, biomolecular and clinical relationships with the heart Nat Clin Pract Cardiovasc Med 2 536-2383

[18] Sanna F(2012)Radiomics: Extracting more information from medical images using advanced feature analysis Eur J Cancer 48 441-1565

[19] Sabharwal N(2020)Myocardial Infarction associates with a distinct pericoronary adipose tissue radiomic phenotype: a prospective case-control study JACC Cardiovasc Imaging 13 2371-1395

[20] Thomas S(2019)State-of-the-art deep learning in cardiovascular image analysis JACC Cardiovasc Imaging 12 1549-497