Computed Tomography Angiography Characteristics of Thin-Cap Fibroatheroma in Patients With Diabetes

Overview

Journal J Am Heart Assoc

Specialty Cardiology & Vascular Diseases

Date 2024 May 14

PMID 38742509

Authors

Keishi Suzuki

Daisuke Kinoshita

Takayuki Niida

Haruhito Yuki

Daichi Fujimoto

Damini Dey

Hang Lee

Iris McNulty

Masamichi Takano

Kyoichi Mizuno

Maros Ferencik

Tsunekazu Kakuta

Ik-Kyung Jang

Affiliations

Soon will be listed here.

Abstract

Background: It was recently reported that thin-cap fibroatheroma (TCFA) detected by optical coherence tomography was an independent predictor of future cardiac events in patients with diabetes. However, the clinical usefulness of this finding is limited by the invasive nature of optical coherence tomography. Computed tomography angiography (CTA) characteristics of TCFA have not been systematically studied. The aim of this study was to investigate CTA characteristics of TCFA in patients with diabetes.

Methods And Results: Patients with diabetes who underwent preintervention CTA and optical coherence tomography were included. Qualitative and quantitative analyses were performed for plaques on CTA. TCFA was assessed by optical coherence tomography. Among 366 plaques in 145 patients with diabetes, 111 plaques had TCFA. The prevalence of positive remodeling (74.8% versus 50.6%, <0.001), low attenuation plaque (63.1% versus 33.7%, <0.001), napkin-ring sign (32.4% versus 11.0%, <0.001), and spotty calcification (55.0% versus 34.9%, <0.001) was significantly higher in TCFA than in non-TCFA. Low-density noncalcified plaque volume (25.4 versus 15.7 mm, <0.001) and remodeling index (1.30 versus 1.20, =0.002) were higher in TCFA than in non-TCFA. The presence of napkin-ring sign, spotty calcification, high low-density noncalcified plaque volume, and high remodeling index were independent predictors of TCFA. When all 4 predictors were present, the probability of TCFA increased to 82.4%.

Conclusions: The combined qualitative and quantitative plaque analysis of CTA may be helpful in identifying TCFA in patients with diabetes.

Registration Information: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194.

References

Yang D, Kang S, Koo H, Chang M, Kang J, Lim T . Coronary CT angiography characteristics of OCT-defined thin-cap fibroatheroma: a section-to-section comparison study. Eur Radiol. 2017; 28(2):833-843. DOI: 10.1007/s00330-017-4992-8. View

Yahagi K, Kolodgie F, Lutter C, Mori H, Romero M, Finn A . Pathology of Human Coronary and Carotid Artery Atherosclerosis and Vascular Calcification in Diabetes Mellitus. Arterioscler Thromb Vasc Biol. 2016; 37(2):191-204. PMC: 5269516. DOI: 10.1161/ATVBAHA.116.306256. View

Achenbach S, Ropers D, Hoffmann U, MacNeill B, Baum U, Pohle K . Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol. 2004; 43(5):842-7. DOI: 10.1016/j.jacc.2003.09.053. View

Araki M, Yonetsu T, Kurihara O, Nakajima A, Lee H, Soeda T . Predictors of Rapid Plaque Progression: An Optical Coherence Tomography Study. JACC Cardiovasc Imaging. 2020; 14(8):1628-1638. DOI: 10.1016/j.jcmg.2020.08.014. View

Araki M, Park S, Dauerman H, Uemura S, Kim J, Di Mario C . Optical coherence tomography in coronary atherosclerosis assessment and intervention. Nat Rev Cardiol. 2022; 19(10):684-703. PMC: 9982688. DOI: 10.1038/s41569-022-00687-9. View

Wen W, Gao M, Yun M, Meng J, Yu W, Zhu Z . In Vivo Coronary F-Sodium Fluoride Activity: Correlations With Coronary Plaque Histological Vulnerability and Physiological Environment. JACC Cardiovasc Imaging. 2023; 16(4):508-520. DOI: 10.1016/j.jcmg.2022.03.018. View

Schramm T, Gislason G, Kober L, Rasmussen S, Rasmussen J, Abildstrom S . Diabetes patients requiring glucose-lowering therapy and nondiabetics with a prior myocardial infarction carry the same cardiovascular risk: a population study of 3.3 million people. Circulation. 2008; 117(15):1945-54. DOI: 10.1161/CIRCULATIONAHA.107.720847. View

Ferencik M, Mayrhofer T, Bittner D, Emami H, Puchner S, Lu M . Use of High-Risk Coronary Atherosclerotic Plaque Detection for Risk Stratification of Patients With Stable Chest Pain: A Secondary Analysis of the PROMISE Randomized Clinical Trial. JAMA Cardiol. 2018; 3(2):144-152. PMC: 5838601. DOI: 10.1001/jamacardio.2017.4973. View

Kedhi E, Berta B, Roleder T, Hermanides R, Fabris E, IJsselmuiden A . Thin-cap fibroatheroma predicts clinical events in diabetic patients with normal fractional flow reserve: the COMBINE OCT-FFR trial. Eur Heart J. 2021; 42(45):4671-4679. DOI: 10.1093/eurheartj/ehab433. View

10.

Goeller M, Achenbach S, Cadet S, Kwan A, Commandeur F, Slomka P . Pericoronary Adipose Tissue Computed Tomography Attenuation and High-Risk Plaque Characteristics in Acute Coronary Syndrome Compared With Stable Coronary Artery Disease. JAMA Cardiol. 2018; 3(9):858-863. PMC: 6233643. DOI: 10.1001/jamacardio.2018.1997. View

11.

Orasanu G, Plutzky J . The pathologic continuum of diabetic vascular disease. J Am Coll Cardiol. 2009; 53(5 Suppl):S35-42. PMC: 2663393. DOI: 10.1016/j.jacc.2008.09.055. View

12.

Andreini D, Magnoni M, Conte E, Masson S, Mushtaq S, Berti S . Coronary Plaque Features on CTA Can Identify Patients at Increased Risk of Cardiovascular Events. JACC Cardiovasc Imaging. 2019; 13(8):1704-1717. DOI: 10.1016/j.jcmg.2019.06.019. View

13.

Williams M, Moss A, Dweck M, Adamson P, Alam S, Hunter A . Coronary Artery Plaque Characteristics Associated With Adverse Outcomes in the SCOT-HEART Study. J Am Coll Cardiol. 2019; 73(3):291-301. PMC: 6342893. DOI: 10.1016/j.jacc.2018.10.066. View

14.

Ito T, Terashima M, Kaneda H, Nasu K, Matsuo H, Ehara M . Comparison of in vivo assessment of vulnerable plaque by 64-slice multislice computed tomography versus optical coherence tomography. Am J Cardiol. 2011; 107(9):1270-7. DOI: 10.1016/j.amjcard.2010.12.036. View

15.

Tomizawa N, Inoh S, Nojo T, Nakamura S . The association of hemoglobin A1c and high risk plaque and plaque extent assessed by coronary computed tomography angiography. Int J Cardiovasc Imaging. 2015; 32(3):493-500. DOI: 10.1007/s10554-015-0788-6. View

16.

Gaur S, Ovrehus K, Dey D, Leipsic J, Botker H, Jensen J . Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions. Eur Heart J. 2016; 37(15):1220-7. PMC: 4830909. DOI: 10.1093/eurheartj/ehv690. View

17.

Tesche C, Bauer M, Straube F, Rogowski S, Baumann S, Renker M . Association of epicardial adipose tissue with coronary CT angiography plaque parameters on cardiovascular outcome in patients with and without diabetes mellitus. Atherosclerosis. 2022; 363:78-84. DOI: 10.1016/j.atherosclerosis.2022.10.006. View

18.

van Diemen P, Bom M, Driessen R, Schumacher S, Everaars H, W de Winter R . Prognostic Value of RCA Pericoronary Adipose Tissue CT-Attenuation Beyond High-Risk Plaques, Plaque Volume, and Ischemia. JACC Cardiovasc Imaging. 2021; 14(8):1598-1610. DOI: 10.1016/j.jcmg.2021.02.026. View

19.

Yuan M, Wu H, Li R, Yu M, Dai X, Zhang J . The value of quantified plaque analysis by dual-source coronary CT angiography to detect vulnerable plaques: a comparison study with intravascular ultrasound. Quant Imaging Med Surg. 2020; 10(3):668-677. PMC: 7136737. DOI: 10.21037/qims.2020.01.13. View

20.

Hell M, Motwani M, Otaki Y, Cadet S, Gransar H, Miranda-Peats R . Quantitative global plaque characteristics from coronary computed tomography angiography for the prediction of future cardiac mortality during long-term follow-up. Eur Heart J Cardiovasc Imaging. 2017; 18(12):1331-1339. PMC: 5837249. DOI: 10.1093/ehjci/jex183. View