Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics

Si, Nuo; Shi, Ke; Li, Na; Dong, Xiaolin; Zhu, Chentao; Guo, Yan; Hu, Jiesi; Cui, Jingjing; Yang, Fan; Zhang, Tong

doi:10.1007/s00330-022-08812-5

Cited by 41 publications

(23 citation statements)

References 32 publications

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“…One study suggested that an increase in the FAI around the proximal RCA and LAD on CCTA images may be associated with an increased risk of cardiac death ( 7 ). We found that patients with MI had a higher FAI around culprit lesions than did the patients with UA, as both MI and UA are caused by myocardial damage, whereas patients with MI have myocardial necrosis and a more severe inflammatory state ( 34 ). We also found that the FAI in other components, including non-culprit lesions and LAD ref to be higher in patients with MI than in those with UA; this is because patients with ACS are thought to have globally active coronary inflammation ( 34 ); that is, both patients with MI and UA develop diffuse inflammation due to a particular lesion, and as illustrated above, overall inflammation is more severe in patients with MI than in those with UA, thus causing the FAI around non-culprit lesions to be also higher in MI than in UA.…”

Section: Discussionmentioning

confidence: 82%

Identification of patients with acute coronary syndrome and representation of their degree of inflammation: application of pericoronary adipose tissue within different radial distances of the proximal coronary arteries

Dong¹,

Zhu²,

Li³

et al. 2023

Quant Imaging Med Surg

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Background: Pericoronary adipose tissue (PCAT) around the proximal right coronary artery (RCA) is considered a marker of coronary inflammation. We aimed to explore the segments of PCAT that represent coronary inflammation in patients with acute coronary syndrome (ACS) and to identify patients with ACS and stable coronary artery disease (CAD) prior to intervention. Methods:We retrospectively enrolled consecutive patients with ACS and stable CAD who underwent invasive coronary angiography (ICA) after coronary computed tomography angiography (CCTA) from November 2020 to October 2021 at the Fourth Affiliated Hospital of Harbin Medical University. The fat attenuation index (FAI) was obtained using PCAT quantitative measurement software, and the coronary Gensini score was also calculated to indicate the severity of CAD. The differences and correlations between FAI within different radial distances of proximal coronary arteries were evaluated, and the recognition ability of FAI for patients with ACS and stable CAD was evaluated by establishing receiver operator characteristic (ROC) curves.Results: A total of 267 patients were included in the cross-sectional study, including 173 patients with ACS. With the increase of radial distance from the outer wall of proximal coronary vessels, the FAI decreased (P<0.001). The FAI around the proximal left anterior descending artery (LAD) within the reference diameter from the outer wall of the vessel (LAD_ref) had the highest correlation with the FAI around culprit lesions [r=0.587; 95% confidence interval (CI): 0.489-0.671; P<0.001]. The model based on clinical features, Gensini score, and LAD_ref had the highest recognition performance for patients with ACS and stable CAD [area under the curve (AUC): 0.663; 95% CI: 0.540-0.785].

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Section: Discussionmentioning

confidence: 82%

Identification of patients with acute coronary syndrome and representation of their degree of inflammation: application of pericoronary adipose tissue within different radial distances of the proximal coronary arteries

Dong¹,

Zhu²,

Li³

et al. 2023

Quant Imaging Med Surg

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“…Recent studies found that texture and geometry-based radiomic parameters of PCAT may distinguish patients who have a MI, providing new information that was not captured by PCAT attenuation alone. [118][119][120] The CCTA-based radiomics phenotype of PCAT outperforms the pFAI model in discriminating acute MI from unstable angina. It is expected that the combination of PCAT radiomics and pFAI evaluation could further enhance the identification of patients at risk of MI.…”

Section: Future Perspectives: Radiomics Of Pericoronary Adipose Tissuementioning

confidence: 99%

“…Radiomics may play a role in exploring the relationship of atherosclerotic plaques with pericoronary inflammation. Recent studies found that texture and geometry-based radiomic parameters of PCAT may distinguish patients who have a MI, providing new information that was not captured by PCAT attenuation alone 118–120 . The CCTA-based radiomics phenotype of PCAT outperforms the pFAI model in discriminating acute MI from unstable angina.…”

Section: Future Perspectives: Radiomics Of Pericoronary Adipose Tissuementioning

confidence: 99%

Computed tomography and nuclear medicine for the assessment of coronary inflammation: clinical applications and perspectives

Guaricci

Neglia

Acampa

et al. 2023

Journal of Cardiovascular Medicine

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There is increasing evidence that in patients with atherosclerotic cardiovascular disease (ASCVD) under optimal medical therapy, a persisting dysregulation of the lipid and glucose metabolism, associated with adipose tissue dysfunction and inflammation, predicts a substantial residual risk of disease progression and cardiovascular events. Despite the inflammatory nature of ASCVD, circulating biomarkers such as high-sensitivity C-reactive protein and interleukins may lack specificity for vascular inflammation. As known, dysfunctional epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) produce pro-inflammatory mediators and promote cellular tissue infiltration triggering further pro-inflammatory mechanisms. The consequent tissue modifications determine the attenuation of PCAT as assessed and measured by coronary computed tomography angiography (CCTA). Recently, relevant studies have demonstrated a correlation between EAT and PCAT and obstructive coronary artery disease, inflammatory plaque status and coronary flow reserve (CFR). In parallel, CFR is well recognized as a marker of coronary vasomotor function that incorporates the haemodynamic effects of epicardial, diffuse and small-vessel disease on myocardial tissue perfusion. An inverse relationship between EAT volume and coronary vascular function and the association of PCAT attenuation and impaired CFR have already been reported. Moreover, many studies demonstrated that 18F-FDG PET is able to detect PCAT inflammation in patients with coronary atherosclerosis. Importantly, the perivascular FAI (fat attenuation index) showed incremental value for the prediction of adverse clinical events beyond traditional risk factors and CCTA indices by providing a quantitative measure of coronary inflammation. As an indicator of increased cardiac mortality, it could guide early targeted primary prevention in a wide spectrum of patients. In this review, we summarize the current evidence regarding the clinical applications and perspectives of EAT and PCAT assessment performed by CCTA and the prognostic information derived by nuclear medicine.

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“…Furthermore, coronary artery calcium is an important marker for identifying CAD [ 16 ], and a high coronary artery calcium score (CACS) has been found to be a predictor of CAD and is independently associated with the occurrence of cardiovascular events [ 17 , 18 ]. Vascular inflammation is a major driver of atherosclerosis and plaque rupture [ 19 ], and pericoronary adipose tissue (PCAT) based on coronary CTA has been demonstrated in recent years as a new sensitive marker to indicate the degree of coronary inflammation, which can be used to identify and stratify CAD [ 20 ].The CRISP-CT study found that significantly higher PCAT attenuation (PCATA) around the left anterior descending artery (LAD) and right coronary artery (RCA) was an important risk factor for increased cardiac mortality [ 21 ]. PCATA has consequently been recognized as an important marker of increased cardiovascular risk.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study

Dong

Zhu

et al. 2023

Cardiovasc Diabetol

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Background Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to cardiovascular disease, and coronary artery disease (CAD) is their leading cause of death. We aimed to assess whether computed tomography (CT) based imaging parameters and radiomic features of pericoronary adipose tissue (PCAT) can improve the diagnostic efficacy of whether patients with T2DM have developed CAD. Methods We retrospectively recruited 229 patients with T2DM but no CAD history (146 were diagnosed with CAD at this visit and 83 were not). We collected clinical information and extracted imaging manifestations from CT images and 93 radiomic features of PCAT from all patients. All patients were randomly divided into training and test groups at a ratio of 7:3. Four models were constructed, encapsulating clinical factors (Model 1), clinical factors and imaging indices (Model 2), clinical factors and Radscore (Model 3), and all together (Model 4), to identify patients with CAD. Receiver operating characteristic curves and decision curve analysis were plotted to evaluate the model performance and pairwise model comparisons were performed via the DeLong test to demonstrate the additive value of different factors. Results In the test set, the areas under the curve (AUCs) of Model 2 and Model 4 were 0.930 and 0.929, respectively, with higher recognition effectiveness compared to the other two models (each p < 0.001). Of these models, Model 2 had higher diagnostic efficacy for CAD than Model 1 (p < 0.001, 95% CI [0.129–0.350]). However, Model 4 did not improve the effectiveness of the identification of CAD compared to Model 2 (p = 0.776); similarly, the AUC did not significantly differ between Model 3 (AUC = 0.693) and Model 1 (AUC = 0.691, p = 0.382). Overall, Model 2 was rated better for the diagnosis of CAD in patients with T2DM. Conclusions A comprehensive diagnostic model combining patient clinical risk factors with CT-based imaging parameters has superior efficacy in diagnosing the occurrence of CAD in patients with T2DM.

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Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics

Cited by 41 publications

References 32 publications

Identification of patients with acute coronary syndrome and representation of their degree of inflammation: application of pericoronary adipose tissue within different radial distances of the proximal coronary arteries

Identification of patients with acute coronary syndrome and representation of their degree of inflammation: application of pericoronary adipose tissue within different radial distances of the proximal coronary arteries

Computed tomography and nuclear medicine for the assessment of coronary inflammation: clinical applications and perspectives

Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study

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