Preview

Complex Issues of Cardiovascular Diseases

Advanced search

Radiomic features of epicardial adipose tissue in coronary atherosclerosis

https://doi.org/10.17802/2306-1278-2021-10-4-6-16

Abstract

Aim. To investigate the association of the radiomic characteristics of epicardial adipose tissue (EAT) on contrast-free computed tomography (CT) of the heart with the severity of obstructive coronary lesion and myocardial ischemia.

Methods. The study included 68 patients with coronary heart disease (mean age of 63.5±9.4, 45 men and 23 women), and 15 patients (mean age 30±4.8; 14 men and 1 woman) without cardiovascular disease as a control group. All the patients underwent multispiral computed coronary angiography, coronary calcium scores (CCS) determination and stress myocardial perfusion scintigraphy. Radiomic characteristics of EAT (texture analysis by gradations of gray color) were determined on non-contrast computer tomogram images of the heart using 3D-Sliser software and the SliserRadiomics module (version 4.10.2). The obtained indicators were compared between a control and under the study groups as well as between subgroups of patients divided according to the degree of obstruction of the coronary arteries, the size of the perfusion defect, and the value of the CCS.

Results. The comparative analysis of radiomic indicators of EAT between patients with coronary artery disease and the control group showed the presence of statistically significant differences between them. At the same time, the correlation analysis in the study group did not reveal any correlations between the radiomic parameters and the size of the perfusion defect, CCS or degree of stenosis of the lumen of the coronary arteries.

Conclusion. The textural characteristics of EAT in patients with coronary heart disease differ from those in individuals without cardiovascular pathology. At the same time, these indicators are not associated with the severity of obstructive lesions of the coronary arteries, the value of the CCS, and the size of the perfusion defect according to scintigraphy.

About the Authors

E. V. Popov
Cardiology Research Institute, Federal State Budgetary Scientific Institution “Tomsk National Research Medical Center of the Russian Academy of Sciences”
Russian Federation

Popov Evgeniy V., resident at Nuclear department

111a, St. Kievskaya, Tomsk, 634012



Zh. Zh. Anashbaev
Cardiology Research Institute, Federal State Budgetary Scientific Institution “Tomsk National Research Medical Center of the Russian Academy of Sciences”
Russian Federation

Anashbaev Zhanat Zh., resident at Nuclear department

111a, St. Kievskaya, Tomsk, 634012



A. N. Maltseva
Cardiology Research Institute, Federal State Budgetary Scientific Institution “Tomsk National Research Medical Center of the Russian Academy of Sciences”
Russian Federation

Maltseva Alina N., resident and laboratory researcher at Nuclear department

111a, St. Kievskaya, Tomsk, 634012



S. I. Sazonova
Cardiology Research Institute, Federal State Budgetary Scientific Institution “Tomsk National Research Medical Center of the Russian Academy of Sciences”
Russian Federation

Sazonova Svetlana I., PhD, leading researcher at Nuclear department

111a, St. Kievskaya, Tomsk, 634012



References

1. Demographic book of Russia. Statistical book. Rosstat. Moscow; 2019. 252 p. Available at: https://rosstat.gov.ru/storage/mediabank/Dem_ejegod-2019.pdf (rosstat.gov.ru) (accessed 15.11.2021) (In Russian)

2. Townsend N., Wilson L., Bhatnagar P., Wickramasinghe K., Rayner M., Nichols M. Cardiovascular disease in Europe: epidemiological update 2016. Eur Heart J. 2016;37(42):3232- 3245. doi: 10.1093/eurheartj/ehw334.

3. Dey D., Wong N.D., Tamarappoo B., Nakazato R., Gransar H., Cheng V.Y., Ramesh A., Kakadiaris I., Germano G., Slomka P.J., Berman D.S. Computer-aided non-contrast CT-based quantification of pericardial and thoracic fat and their associations with coronary calcium and Metabolic Syndrome. Atherosclerosis. 2010;209(1):136-41. doi: 10.1016/j.atherosclerosis.2009.08.032.

4. Berg A.H., Scherer P.E. Adipose tissue, inflammation, and cardiovascular disease. Circ Res. 2005; 96(9):939–949. doi: 10.1161/01.RES.0000163635.62927.34

5. Alexopoulos N., McLean D.S., Janik M., Arepalli C.D., Stillman A.E., Raggi P. Epicardial adipose tissue and coronary artery plaque characteristics. Atherosclerosis. 2010; 210(1):150- 4. doi: 10.1016/j.atherosclerosis.2009.11.020.

6. Khawaja T., Greer C., Thadani S.R., Kato T.S., Bhatia K., Shimbo D., Kontak A., Bokhari S., Einstein A.J., Schulze P.C. Increased Regional Epicardial Fat Volume Associated with Reversible Myocardial Ischemia in Patients with Suspected Coronary Artery Disease. Journal of Nuclear Cardiology. 2015; 22(2): 325–333. doi:10.1007/s12350-014-0004-4

7. Ohashi N., Yamamoto H., Horiguchi J., Kitagawa T., Kunita E., Utsunomiya H., Oka T., Kohno N., Kihara Y. Association between visceral adipose tissue area and coronary plaque morphology assessed by CT angiography. JACC Cardiovasc Imaging. 2010; 3(9):908-17. doi: 10.1016/j.jcmg.2010.06.014

8. Shaikh F., Franc B., Mulero F. Radiomics as Applied in Precision Medicine. In: Clinical Nuclear Medicine. Ahmadzadehfar H., Biersack H.J., Freeman L.M., Zuckier L.S. editors. 2nd ed. Springer-Verlag Berlin Heidelberg; 2020. 193-206.

9. Zavadovskij K.V., Gulja M.O., Saushkin V.V., Saushkina Ju.V., Lishmanov Ju.B. Superimposed single-photon emission computed tomography and X-ray computed tomography of the heart: Methodical aspects. 2016; 97(4):235-242.(In Russian) doi: 10.20862/0042-4676-2016-97-4-8-15.

10. Neumann F.-J., Sousa-Uva M., Ahlsson A., Alfonso F., Banning A. P., Benedetto U. 2018 ESC/EACTS guidelines on myocardial revascularization. The Task Force on Myocardial Revascularization of the European Society of Cardiology (ESC) and the European Associationfor Cardio-Thoracic Surgery (EACTS). Developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI). European Heart Journal. 2018; 40(37): 87-165. doi: 10.1093/eurheartj/ehy394

11. Ficaro E., Lee B., Kritzman J., Corbett J. The Michigan method for quantitative nuclear cardiology. Corridor4DM: The Michigan method for quantitative nuclear cardiology. Journal of Nuclear Cardiology. 2007; 14(4):455-65. doi: 10.1016/j.nuclcard.2007.06.006

12. Prasad M., Slomka P.J., Fish M., Kavanagh P., Gerlach J., Hayes S., Berman D. S., Germano G. Improved quantification and normal limits for myocardial perfusion stress-rest change. Journal of Nuclear Medicine. 2010; 51(2): 204-9. doi: 10.2967/jnumed.109.067736

13. Cerqueira M.D., Weissman N. J., Dilsizian V., Jacobs A. K., Kaul S., Laskey W. K., Pennell D.J., Rumberger J.A., Ryan T., Verani M.S.; American Heart Association Writing Group on Myocardial Segmentation and Registration for Cardiac Imaging. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the cardiac imaging committee of the council on clinical cardiology of the american heart association. Circulation. 2002; 105: 539-542. doi: 10.1161/hc0402.102975

14. Oikonomou E.K., Williams M.C., Kotanidis C.P., Desai M.Y., Marwan M., Antonopoulos A.S., et al. A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CTangiography. European Heart Journal. 2019; 40(43):3529-3543. doi: 10.1093/eurheartj/ehz592

15. Kolossváry M., Karady J., Szilveszter B., Kitslaar P., Hoffmann U., Merkely B., Maurovich-Horvat P. Radiomic features are superior to conventional quantitative computed tomographic metrics to identify coronary plaques with NapkinRing Sign. Circ Cardiovasc Imaging. 2017;10(12), e006843. doi: 10.1161/CIRCIMAGING.117.006843

16. Kolossváry M., Kellermayer M., Merkely B., Maurovich-Horvat P., Maurovich-Horvat P. Cardiac computed tomography radiomics: a comprehensive review on radiomic techniques. J Thorac Imaging. 2018; 33(1):26–34. doi: 10.1097/RTI.0000000000000268

17. Lambin P., Rios-Velazquez E., Leijenaar R., Carvalho S., van Stiphout R.G., Granton P., Zegers C.M., Gillies R., Boellard R., Dekker A., Aerts H.J. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012; 48(4):441-6. doi: 10.1016/j.ejca.2011.11.036

18. De Jong M.C., Genders T.S.S., Van Geuns R-J., Moelker A., Hunink M.G.M. Diagnostic performance of stress myocardial perfusion imaging for coronary artery disease: a systematic review and meta-analysis. European Radiology. 2012; 22 (9): 1881–1895. doi: 10.1007/s00330-012-2434-1

19. Radiomic Features. Available at: https://pyradiomics.readthedocs.io/en/latest/features.html. (accessed: 01.07.2020)

20. Knuuti J., Wijns W., Saraste A., Capodanno D., Barbato E., Funck-Brentano C., Prescott E., Storey R.F., Deaton C., Cuisset T., Agewall S., Dickstein K., Edvardsen T., Escaned J., Gersh B.J., Svitil P., Gilard M., Hasdai D., Hatala R., Mahfoud F., Masip J., Muneretto C., Valgimigli M., Achenbach S., Bax J.J.; ESC Scientific Document Group. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC). European Heart Journal. 2019;41: 407-477.doi:10.1093/eurheartj/ehz425

21. Agatston A.S., Janowitz W.R., Hildner F.J., Zusmer N.R., Viamonte M., Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. Journal of the American College of Cardiology. 1990; 15(4): 827-832. doi:10.1016/0735-1097(90)90282-T

22. Hyafil F., Gimelli A., Slart R.H.J.A., Georgoulias P., Rischpler C., Lubberink M., Sciagra R., Bucerius J., Agostini D., Verberne H.J., behalf of the Cardiovascular Committee of the European Association of Nuclear Medicine (EANM). EANM procedural guidelines for myocardial perfusion scintigraphy using cardiac-centered gamma cameras. European J Hybrid Imaging. 2019; 3(11): doi.org/10.1186/s41824-019-0058-2

23. A.N Kokov, N.K. Brel, V.L. Masenko, O.V. Gruzdeva, V.N. Karetnikova, V.V. Kashtalap, O.L. Barbarash. Quanntitative assessment of visceral adipose depot in patients with ischemic heart disease by using of modern tomographic methods. Complex Issues of Cardiovascular Diseases. 2017;3:113-119. doi: 10.17802/2306-1278-2017-6-3-113-119. (In Russian)

24. Mazurek T., Zhang L., Zalewski A., Mannion J.D., Diehl J.T., Arafat H., Sarov-Blat L., O'Brien S., Keiper E.A., Johnson A.G., Martin J., Goldstein B.J., Shi Y. Human epicardial adipose tissue is a source of inflammatory mediators. Circulation. 2003; 108(20):2460-6. doi: 10.1161/01.CIR.0000099542.57313.C5

25. Kolossváry M., Park J., Bang J.I., Zhang J., Lee J.M., Paeng J.C., Merkely B., Narula J., Kubo T., Akasaka T., Koo B.K., Maurovich-Horvat P. Identification of invasive and radionuclide imagingmarkers of coronary plaque vulnerability using radiomic analysis of coronary computed tomography angiography. European Heart Journal - Cardiovascular Imaging. 2019; 20(11): 1250–1258. doi: 10.1093/ehjci/jez033


Review

For citations:


Popov E.V., Anashbaev Zh.Zh., Maltseva A.N., Sazonova S.I. Radiomic features of epicardial adipose tissue in coronary atherosclerosis. Complex Issues of Cardiovascular Diseases. 2021;10(4):6-16. https://doi.org/10.17802/2306-1278-2021-10-4-6-16

Views: 541


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2306-1278 (Print)
ISSN 2587-9537 (Online)