Management of coronary artery disease with cardiac CT beyond gatekeeping

Stable ischemic heart disease: re-appraisal of coronary revascularization criteria in the light of contemporary evidence

The term "stable ischemic heart disease" includes a variety of clinical and pathophysiological situations resulting in different presentation modalities, often with complex referral patterns, and with multiple potential therapeutical options. Multifactorial pathogenesis and multiform expressivity are poorly captured by the traditional vision of ischemic heart disease (IHD) as the clogged pipes disease. The availability of different technologies for studying patients with symptoms suggestive of IHD, has shed a new light on the pathophysiology of the disease, but has also allowed appropriate follow-up of patients allocated to different therapeutical options. Though coronary revascularization has been one primary treatment option for obstructive coronary artery disease (CAD), the evidence for its efficacy in patients without acute presentation is far from optimal. A number of studies and meta-analyses strongly support the need for a personalized and optimized medical approach (including functional assessment and therapy) before the tailored option of revascularization in selected patients, in order to optimize its effects on symptoms and outcome. Most recent data have expanded the need for a more personalised approach to this complex situation, which should be patient-centered and not focused on technologies. In this review, we discuss the major pathophysiological factors and the most recent clinical data and guidelines suggestions, needed for a critical re-appraisal of the clinical decision-making to perform revascularization in patients with stable IHD. Moreover we aimed at suggesting the potential role for future studies to fill the existing knowledge gaps but also to counteract a reductive, hydraulic view of chronic IHD, which seems to be still alive and kicking, both in clinical and research communities, despite multiple evidences and recommendations.

Myocardial bridge-related coronary heart disease: Independent influencing factors and their predicting value

BACKGROUND

Myocardial bridge (MB) will compress the mural coronary artery (MCA) during the systole and cause myocardial ischemia. In the diagnosis of coronary heart disease (CHD), because the structure of MB is difficult to be observed by coronary angiography (CAG), the clinical study of the influence of MB on CHD is lacking. With the advancement of computed tomography coronary angiography technology, detailed observations of the MB anatomy have realized.

AIM

To explore the main influencing factors of MB-related CHD and to find potential indicators for predicting MB-related CHD.

METHODS

A total of 1718 patients with suspected CHD due to the symptoms of myocardial ischemia were enrolled as subjects. Patients diagnosed with CHD were included in a CHD group, and patients with no significant abnormalities were included in a control group. In the CHD group, patients were divided into an MB-CHD subgroup if MB-related CHD was found. In the control group, patients were divided into a simple MB subgroup if MB was found. The patient's clinical data and MB-related indicators, including the branch of MB, MB type (superficial/deep type), MB length, MB thickness, systolic and diastolic compression of the MCA, and MCA systolic stenosis rate were recorded and compared. Logistic regression analysis was used to explore the independent influencing factors of MD-related CHD. ROC curve was used to analyze the diagnostic efficacy of potential indicators for MB-related CHD.

RESULTS

There were 1060 cases in the CHD group and 658 cases in the control group, and there were 236 cases in the MB-CHD subgroup and 52 cases in the simple MB subgroup. Multivariate logistic regression analysis showed that the combined MB had a significant effect on the occurrence of CHD (P < 0.05). MB thickness, systolic compression, diastolic compression, and MCA systolic stenosis rate had significant effects on the occurrence of MB-related CHD (P < 0.05). The area under the curve (AUC) of the combination of these influencing factors for the diagnosis of MB-related CHD was 0.959, which was significantly higher than the AUCs of the four indicators separately (P < 0.05). The sensitivity was 97.06% and the specificity was 87.63%.

CONCLUSION

MB thickness, systolic compression, diastolic compression, and MCA systolic stenosis are independent influencing factors for MB-related CHD. The combination of these factors has potential diagnostic value for MB-related CHD.

Evidence of association of circulating epigenetic-sensitive biomarkers with suspected coronary heart disease evaluated by Cardiac Computed Tomography

Circulating biomarkers available in clinical practice do not allow to stratify patients with coronary heart disease (CHD) prior the onset of a clinically relevant event. We evaluated the methylation status of specific genomic segments and gene expression in peripheral blood of patients undergoing Cardiac Computed Tomography (CCT) for CHD (n = 95).

We choose to investigate cholesterol metabolism. Methylation and gene expression of low density lipoprotein receptor (LDLR), sterol regulatory element-binding factor 2 (SREBF2) and ATP-binding cassette transporter 1 (ABCA1) were evaluated by qRT-PCR. Calcium score (CACS), stenosis degree, total plaque volume (TPV), calcified plaque volume (CPV), non-calcified plaque volume (NCPV) and plaque burden (PB) were assessed in all CHD patients (n = 65). The percentage of methylation at the specific analyzed segment of LDLR promoter was higher in CHD patients vs healthy subjects (HS) (n = 30) (p = 0.001). LDLR, SREBF2 and ABCA1 mRNAs were up-regulated in CHD patients vs HS (p = 0.02; p = 0.019; p = 0.008). SREBF2 was overexpressed in patients with coronary stenosis ≥50% vs subjects with stenosis <50% (p = 0.036). After adjustment for risk factors and clinical features, ABCA1 (p = 0.005) and SREBF2 (p = 0.010) gene expression were identified as independent predictors of CHD and severity. ROC curve analysis revealed a good performance of ABCA1 on predicting CHD (AUC = 0.768; p<0.001) and of SREBF2 for the prediction of disease severity (AUC = 0.815; p<0.001). Moreover, adjusted multivariate analysis demonstrated SREBF2 as independent predictor of CPV, NCPV and TPV (p = 0.022; p = 0.002 and p = 0.006) and ABCA1 as independent predictor of NCPV and TPV (p = 0.002 and p = 0.013).

CHD presence and characteristics are related to selected circulating transcriptional and epigenetic-sensitive biomarkers linked to cholesterol pathway. More extensive analysis of CHD phenotypes and circulating biomarkers might improve and personalize cardiovascular risk stratification in the clinical settings.