DOI QR코드

DOI QR Code

Microvascular Myocardial Ischemia in Patients With Diabetes Without Obstructive Coronary Stenosis and Its Association With Angina

  • Yarong Yu (Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Wenli Yang (Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Xu Dai (Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine) ;
  • Lihua Yu (Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Ziting Lan (Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Xiaoying Ding (Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Jiayin Zhang (Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine)
  • 투고 : 2023.04.24
  • 심사 : 2023.07.30
  • 발행 : 2023.11.01

초록

Objective: To investigate the incidence of microvascular myocardial ischemia in diabetic patients without obstructive coronary artery disease (CAD) and its relationship with angina. Materials and Methods: Diabetic patients and an intermediate-to-high pretest probability of CAD were prospectively enrolled. Non-diabetic patients but with an intermediate-to-high pretest probability of CAD were retrospectively included as controls. The patients underwent dynamic computed tomography-myocardial perfusion imaging (CT-MPI) and coronary computed tomography angiography (CCTA) to quantify coronary stenosis, myocardial blood flow (MBF), and extracellular volume (ECV). The proportion of patients with microvascular myocardial ischemia, defined as any myocardial segment with a mean MBF ≤ of 100 mL/min/100 mL, in patients without obstructive CAD (Coronary Artery Disease-Reporting and Data System [CAD-RADS] grade 0-2 on CCTA) was determined. Various quantitative parameters of the patients with and without diabetes without obstructive CAD were compared. Multivariable analysis was used to determine the association between microvascular myocardial ischemia and angina symptoms in diabetic patients without obstructive CAD. Results: One hundred and fifty-two diabetic patients (mean age: 59.7 ± 10.7; 77 males) and 266 non-diabetic patients (62.0 ± 12.3; 167 males) were enrolled; CCTA revealed 113 and 155 patients without obstructive CAD, respectively. For patients without obstructive CAD, the mean global MBF was significantly lower for those with diabetes than for those without (152.8 mL/min/100 mL vs. 170.4 mL/min/100 mL, P < 0.001). The mean ECV was significantly higher for diabetic patients (27.2% vs. 25.8%, P = 0.009). Among the patients without obstructive CAD, the incidence of microvascular myocardial ischemia (36.3% [41/113] vs. 10.3% [16/155], P < 0.001) and interstitial fibrosis (69.9% [79/113] vs. 33.3% [8/24], P = 0.001) were significantly higher in diabetic patients than in the controls. The presence of microvascular myocardial ischemia was independently associated with angina symptoms (adjusted odds ratio = 3.439, P = 0.037) in diabetic patients but without obstructive CAD. Conclusion: Dynamic CT-MPI + CCTA revealed a high incidence of microvascular myocardial ischemia in diabetic patients without obstructive CAD. Microvascular myocardial ischemia is strongly associated with angina.

키워드

과제정보

This study is supported by The National Key Research and Development Program of China (Grant No.: 2021YFF0501402), Shanghai Committee of Science and Technology (Grant No.: 21ZR1452200) and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (Grant No.: 20161428).

참고문헌

  1. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, et al. IDF diabetes atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract 2018;138:271-281 
  2. Valensi P, Prevost G, Pinto S, Halimi JM, Donal E. The impact of diabetes on heart failure development: the cardio-renal-metabolic connection. Diabetes Res Clin Pract 2021;175:108831 
  3. Ritchie RH, Abel ED. Basic mechanisms of diabetic heart disease. Circ Res 2020;126:1501-1525 
  4. Haase R, Schlattmann P, Gueret P, Andreini D, Pontone G, Alkadhi H, et al. Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data. BMJ 2019;365:l1945 
  5. Newby DE, Adamson PD, Berry C, Boon NA, Dweck MR, Flather M, et al. Coronary CT angiography and 5-year risk of myocardial infarction. N Engl J Med 2018;379:924-933 
  6. Halon DA, Lavi I, Barnett-Griness O, Rubinshtein R, Zafrir B, Azencot M, et al. Plaque morphology as predictor of late plaque events in patients with asymptomatic type 2 diabetes: a long-term observational study. JACC Cardiovasc Imaging 2019;12(7 Pt 2):1353-1363 
  7. Kim U, Leipsic JA, Sellers SL, Shao M, Blanke P, Hadamitzky M, et al. Natural history of diabetic coronary atherosclerosis by quantitative measurement of serial coronary computed tomographic angiography: results of the PARADIGM study. JACC Cardiovasc Imaging 2018;11:1461-1471 
  8. Malik S, Zhao Y, Budoff M, Nasir K, Blumenthal RS, Bertoni AG, et al. Coronary artery calcium score for long-term risk classification in individuals with type 2 diabetes and metabolic syndrome from the multi-ethnic study of atherosclerosis. JAMA Cardiol 2017;2:1332-1340 
  9. Coenen A, Kim YH, Kruk M, Tesche C, De Geer J, Kurata A, et al. Diagnostic accuracy of a machine-learning approach to coronary computed tomographic angiography-based fractional flow reserve: result from the MACHINE consortium. Circ Cardiovasc Imaging 2018;11:e007217 
  10. Mrgan M, Norgaard BL, Dey D, Gram J, Olsen MH, Gram J, et al. Coronary flow impairment in asymptomatic patients with early stage type-2 diabetes: detection by FFRCT. Diab Vasc Dis Res 2020;17:1479164120958422 
  11. Di Carli MF, Janisse J, Grunberger G, Ager J. Role of chronic hyperglycemia in the pathogenesis of coronary microvascular dysfunction in diabetes. J Am Coll Cardiol 2003;41:1387-1393 
  12. Shimizu M, Umeda K, Sugihara N, Yoshio H, Ino H, Takeda R, et al. Collagen remodelling in myocardia of patients with diabetes. J Clin Pathol 1993;46:32-36 
  13. Jespersen L, Hvelplund A, Abildstrom SZ, Pedersen F, Galatius S, Madsen JK, et al. Stable angina pectoris with no obstructive coronary artery disease is associated with increased risks of major adverse cardiovascular events. Eur Heart J 2012;33:734-744 
  14. Deux JF, Nouri R, Tacher V, Zaroui A, Derbel H, Sifaoui I, et al. Diagnostic value of extracellular volume quantification and myocardial perfusion analysis at CT in cardiac amyloidosis. Radiology 2021;300:326-335 
  15. Li Y, Yu M, Dai X, Lu Z, Shen C, Wang Y, et al. Detection of hemodynamically significant coronary stenosis: CT myocardial perfusion versus machine learning CT fractional flow reserve. Radiology 2019;293:305-314 
  16. American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2020. Diabetes Care 2020;43(Suppl 1):S14-S31 
  17. Xu Y, Yu L, Shen C, Lu Z, Zhu X, Zhang J. Prevalence and disease features of myocardial ischemia with non-obstructive coronary arteries: insights from a dynamic CT myocardial perfusion imaging study. Int J Cardiol 2021;334:142-147 
  18. Ohta Y, Kishimoto J, Kitao S, Yunaga H, Mukai-Yatagai N, Fujii S, et al. Investigation of myocardial extracellular volume fraction in heart failure patients using iodine map with rapid-kV switching dual-energy CT: segmental comparison with MRI T1 mapping. J Cardiovasc Comput Tomogr 2020;14:349-355 
  19. Cury RC, Abbara S, Achenbach S, Agatston A, Berman DS, Budoff MJ, et al. CAD-RADS(TM): coronary artery disease - reporting and data system: an expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology. J Am Coll Radiol 2016;13(12 Pt A):1458-1466.e9 
  20. Motoyama S, Sarai M, Harigaya H, Anno H, Inoue K, Hara T, et al. Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol 2009;54:49-57 
  21. Conte E, Annoni A, Pontone G, Mushtaq S, Guglielmo M, Baggiano A, et al. Evaluation of coronary plaque characteristics with coronary computed tomography angiography in patients with non-obstructive coronary artery disease: a long-term follow-up study. Eur Heart J Cardiovasc Imaging 2017;18:1170-1178 
  22. Bamberg F, Klotz E, Flohr T, Becker A, Becker CR, Schmidt B, et al. Dynamic myocardial stress perfusion imaging using fast dual-source CT with alternating table positions: initial experience. Eur Radiol 2010;20:1168-1173 
  23. Cerqueira MD, Weissman NJ, Dilsizian V, Jacobs AK, Kaul S, Laskey WK, et al. 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 
  24. Yu L, Tao X, Dai X, Liu T, Zhang J. Dynamic CT myocardial perfusion imaging in patients without obstructive coronary artery disease: quantification of myocardial blood flow according to varied heart rate increments after stress. Korean J Radiol 2021;22:97-105 
  25. Kurita Y, Kitagawa K, Kurobe Y, Nakamori S, Nakajima H, Dohi K, et al. Estimation of myocardial extracellular volume fraction with cardiac CT in subjects without clinical coronary artery disease: a feasibility study. J Cardiovasc Comput Tomogr 2016;10:237-241 
  26. Scully PR, Patel KP, Saberwal B, Klotz E, Augusto JB, Thornton GD, et al. Identifying cardiac amyloid in aortic stenosis: ECV quantification by CT in TAVR patients. JACC Cardiovasc Imaging 2020;13:2177-2189 
  27. Nacif MS, Kawel N, Lee JJ, Chen X, Yao J, Zavodni A, et al. Interstitial myocardial fibrosis assessed as extracellular volume fraction with low-radiation-dose cardiac CT. Radiology 2012;264:876-883 
  28. Yu Y, Ohmori K, Kondo I, Yao L, Noma T, Tsuji T, et al. Correlation of functional and structural alterations of the coronary arterioles during development of type II diabetes mellitus in rats. Cardiovasc Res 2002;56:303-311 
  29. Sharma A, Rizky L, Stefanovic N, Tate M, Ritchie RH, Ward KW, et al. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) activator dh404 protects against diabetes-induced endothelial dysfunction. Cardiovasc Diabetol 2017;16:33 
  30. Zorach B, Shaw PW, Bourque J, Kuruvilla S, Balfour PC Jr, Yang Y, et al. Quantitative cardiovascular magnetic resonance perfusion imaging identifies reduced flow reserve in microvascular coronary artery disease. J Cardiovasc Magn Reson 2018;20:14 
  31. Vliegenthart R, De Cecco CN, Wichmann JL, Meinel FG, Pelgrim GJ, Tesche C, et al. Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension: insights from a multicenter registry. J Cardiovasc Comput Tomogr 2016;10:301-308 
  32. Huynh K, McMullen JR, Julius TL, Tan JW, Love JE, Cemerlang N, et al. Cardiac-specific IGF-1 receptor transgenic expression protects against cardiac fibrosis and diastolic dysfunction in a mouse model of diabetic cardiomyopathy. Diabetes 2010;59:1512-1520 
  33. Heinsen LJ, Pararajasingam G, Andersen TR, Auscher S, Sheta HM, Precht H, et al. High-risk coronary artery plaque in asymptomatic patients with type 2 diabetes: clinical risk factors and coronary artery calcium score. Cardiovasc Diabetol 2021;20:164 
  34. Kunadian V, Chieffo A, Camici PG, Berry C, Escaned J, Maas AHEM, et al. An EAPCI expert consensus document on ischaemia with non-obstructive coronary arteries in collaboration with European Society of Cardiology Working Group on Coronary Pathophysiology & Microcirculation Endorsed by Coronary Vasomotor Disorders International Study Group. Eur Heart J 2020;41:3504-3520