scholarly journals Pericoronary Fat Attenuation Index Is Associated With Vulnerable Plaque Components and Local Immune‐Inflammatory Activation in Patients With Non‐ST Elevation Acute Coronary Syndrome

Author(s):  
Jia Teng Sun ◽  
Xin Cheng Sheng ◽  
Qi Feng ◽  
Yan Yin ◽  
Zheng Li ◽  
...  

Background The pericoronary fat attenuation index (FAI) is assessed using standard coronary computed tomography angiography, and it has emerged as a novel imaging biomarker of coronary inflammation. The present study assessed whether increased pericoronary FAI values on coronary computed tomography angiography were associated with vulnerable plaque components and their intracellular cytokine levels in patients with non‐ST elevation acute coronary syndrome. Methods and Results A total of 195 lesions in 130 patients with non‐ST elevation acute coronary syndrome were prospectively included. Lesion‐specific pericoronary FAI, plaque components and other plaque features were evaluated by coronary computed tomography angiography. Local T cell subsets and their intracellular cytokine levels were detected by flow cytometry. Lesions with pericoronary FAI values >−70.1 Hounsfield units exhibited spotty calcification (43.1% versus 25.0%, P =0.015) and low‐attenuation plaques (17.6% versus 4.2%, P =0.016) more frequently than lesions with lower pericoronary FAI values. Further quantitative plaque compositional analysis showed that increased necrotic core volume (Pearson’s r=0.324, P <0.001) and fibrofatty volume (Pearson’s r=0.270, P <0.001) were positively associated with the pericoronary FAI, and fibrous volume (Pearson’s r=−0.333, P <0.001) showed a negative association. An increasing proinflammatory intracellular cytokine profile was found in lesions with higher pericoronary FAI values. Conclusions The pericoronary FAI may be a reliable indicator of local immune‐inflammatory response activation, which is closely related to plaque vulnerability. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04792047.

Author(s):  
Jin Shang ◽  
Shaowei Ma ◽  
Yan Guo ◽  
Linlin Yang ◽  
Qian Zhang ◽  
...  

Abstract Objectives To evaluate whether radiomics signature of pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could improve the prediction of future acute coronary syndrome (ACS) within 3 years. Methods We designed a retrospective case-control study that patients with ACS (n = 90) were well matched to patients with no cardiac events (n = 1496) during 3 years follow-up, then which were randomly divided into training and test datasets with a ratio of 3:1. A total of 107 radiomics features were extracted from PCAT surrounding lesions and 14 conventional plaque characteristics were analyzed. Radiomics score, plaque score, and integrated score were respectively calculated via a linear combination of the selected features, and their performance was evaluated with discrimination, calibration, and clinical application. Results Radiomics score achieved superior performance in identifying patients with future ACS within 3 years in both training and test datasets (AUC = 0.826, 0.811) compared with plaque score (AUC = 0.699, 0.640), with a significant difference of AUC between two scores in the training dataset (p = 0.009); while the improvement of integrated score discriminating capability (AUC = 0.838, 0.826) was non-significant. The calibration curves of three predictive models demonstrated a good fitness respectively (all p > 0.05). Decision curve analysis suggested that integrated score added more clinical benefit than plaque score. Stratified analysis revealed that the performance of three predictive models was not affected by tube voltage, CT version, different sites of hospital. Conclusion CCTA-based radiomics signature of PCAT could have the potential to predict the occurrence of subsequent ACS. Radiomics-based integrated score significantly outperformed plaque score in identifying future ACS within 3 years. Key Points • Plaque score based on conventional plaque characteristics had certain limitations in the prediction of ACS. • Radiomics signature of PCAT surrounding plaques could have the potential to improve the predictive ability of subsequent ACS. • Radiomics-based integrated score significantly outperformed plaque score in the identification of future ACS within 3 years.


2019 ◽  
Vol 9 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Murat Arslan ◽  
Jeroen Schaap ◽  
Pleunie PM Rood ◽  
Koen Nieman ◽  
Ricardo PJ Budde ◽  
...  

Aims: Coronary computed tomography angiography is increasingly employed in the emergency department for suspected acute coronary syndrome patients. The HEART score has been proposed for initial risk stratification in these patients. The aim of this study was to investigate the diagnostic value and efficiency of the HEART score before coronary computed tomography angiography. Methods and results: We included patients suspected of acute coronary syndrome who underwent coronary computed tomography angiography in the emergency department. Based on the HEART score, patients were stratified as low-risk (HEART≤3), intermediate-risk (HEART4–6) and high-risk (HEART≥7). We assessed coronary computed tomography angiography for the presence of significant coronary artery disease (>50% stenosis). The primary outcome, the level of major adverse cardiac events, was a composite endpoint of all-cause mortality, acute coronary syndrome or coronary revascularisation within 30 days. The study population consisted of 340 patients (mean age: 55.6±10.1 years, 44.7% women), major adverse cardiac events occurred in 45 (13.2%) patients. The incidence of major adverse cardiac events in patients stratified as low-risk (35.0%), intermediate-risk (56.8%) and high-risk (8.2%) was 3.4%, 12.4% and 60.7%, respectively. All four low-risk patients with major adverse cardiac events had a HEART score of three. An algorithm where coronary computed tomography angiography is reserved for patients with HEART 3–6 resulted in a sensitivity of 97.8%, specificity of 84.1%, negative predictive value of 99.6% and positive predictive value of 48.4%, while reducing the need for coronary computed tomography angiography by 22% ( n=75). Conclusion: The predictive value of coronary computed tomography angiography for 30-day major adverse cardiac events in suspected acute coronary syndrome patients is good, and reserving coronary computed tomography angiography for HEART score 3–6 patients reduces the number of needed coronary computed tomography angiograms without affecting diagnostic accuracy.


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