Association of body mass index with coronary plaque regression: 6-month prospective study

Imaging of coronary atherosclerosis in various susceptible groups

Coronary artery disease (CAD) is the leading cause of death and disability worldwide. Atherosclerosis, which is the primary pathophysiologic mechanism for the development of plaque leading to CAD, is a multifactorial process resulting from a complex interplay between genetic susceptibility and various risk factors such as hypertension (HT), dyslipidaemia, diabetes mellitus (DM) and smoking. In addition, influences from other disease states such as chronic kidney disease (CKD), obesity and the metabolic syndrome as well as gender and ethnic diversity also contribute to the disease process. Insights from pathological observations and advances in cellular and molecular biology have helped us understand the process of plaque formation, progression and rupture leading to events. Several intravascular imaging techniques such as intravascular ultrasound (IVUS), Virtual histology IVUS (VH-IVUS) and optical coherence tomography (OCT) allow in vivo assessment of plaque burden, plaque morphology and response to therapy. In addition, non invasive assessment using coronary artery calcium (CAC) score allows risk stratification and plaque burden assessment whilst computed tomography coronary angiography (CTCA) allows evaluation of luminal stenosis, plaque characterisation and quantification. This review aims to summarise the results of invasive and non-invasive imaging studies of coronary atherosclerosis seen in various high-risk populations including DM, metabolic syndrome, obesity, CKD and, gender differences and ethnicity. Understanding the phenotype of plaques in various susceptible groups may allow potential development of personalised therapies.

Guideline treatment results in regression of atherosclerosis in type 2 diabetes mellitus

BACKGROUND

Efficacy of guideline cardiovascular disease prevention regimens may differ between patients with or without type II diabetes mellitus. We therefore compared change in carotid artery wall dimensions in type II diabetes mellitus and non-type II diabetes mellitus patients with a history of a major cardiovascular disease event, using magnetic resonance imaging.

METHODS

Thirty type II diabetes mellitus patients and 29 age- and sex-matched non-diabetes mellitus patients with a history of stroke or myocardial infarction and a carotid artery stenosis (15%-70%) were included. In all patients, treatment was according to cardiovascular risk management guidelines. At baseline and follow-up, carotid artery vessel wall dimensions were measured using 1.5 T magnetic resonance imaging.

RESULTS

After 2 years of follow-up, total wall volume of the carotid artery in type II diabetes mellitus patients decreased by 9.6% (p = 0.016). In contrast, stabilization rather than regression of carotid artery wall dimensions was observed in non-diabetes mellitus patients over a 2-year period. Body mass index was identified as a predictor of total wall volume decrease.

CONCLUSIONS

Guideline treatment arrests atherogenesis in non-diabetes mellitus patients and even decreases vessel wall dimensions in type II diabetes mellitus patients. Baseline body mass index predicts cardiovascular disease prevention efficacy expressed as decrease in total wall volume. These data emphasize the importance of optimal cardiovascular-prevention, particularly in diabetes patients with a high body mass index.

Coronary artery plaque volume and obesity in patients with diabetes: the factor-64 study

PURPOSE

To determine the relationship between coronary plaque detected with coronary computed tomographic (CT) angiography and clinical parameters and cardiovascular risk factors in asymptomatic patients with diabetes.

MATERIALS AND METHODS

All patients signed institutional review board-approved informed consent forms before enrollment. Two hundred twenty-four asymptomatic diabetic patients (121 men; mean patient age, 61.8 years; mean duration of diabetes, 10.4 years) underwent coronary CT angiography. Total coronary artery wall volume in all three vessels was measured by using semiautomated software. The coronary plaque volume index (PVI) was determined by dividing the wall volume by the coronary length. The relationship between the PVI and cardiovascular risk factors was determined with multivariable analysis.

RESULTS

The mean PVI (±standard deviation) was 11.2 mm(2) ± 2.7. The mean coronary artery calcium (CAC) score (determined with the Agatston method) was 382; 67% of total plaque was noncalcified. The PVI was related to age (standardized β = 0.32, P < .001), male sex (standardized β = 0.36, P < .001), body mass index (BMI) (standardized β = 0.26, P < .001), and duration of diabetes (standardized β = 0.14, P = .03). A greater percentage of soft plaque was present in younger individuals with a shorter disease duration (P = .02). The soft plaque percentage was directly related to BMI (P = .002). Patients with discrepancies between CAC score and PVI rank quartiles had a higher percentage of soft and fibrous plaque (18.7% ± 3.3 vs 17.4% ± 3.5 [P = .008] and 52.2% ± 7.2 vs 47.2% ± 8.8 [P < .0001], respectively).

CONCLUSION

In asymptomatic diabetic patients, BMI was the primary modifiable risk factor that was associated with total and soft coronary plaque as assessed with coronary CT angiography.

Association of the low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratio and body mass index with coronary plaque regression

BACKGROUND

The change (Δ) in the low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein cholesterol (HDL-C) ratio (ΔLDL-C/HDL-C) and obesity are known to play important roles in the progression of coronary atherosclerosis. We hypothesized that a reasonable predictive model of coronary plaque regression could be constructed using ΔLDL-C/HDL-C and the body mass index (BMI).

OBJECTIVE

The purpose of this study was to establish a predictive model of coronary plaque regression using ΔLDL-C/HDL-C and BMI.

METHODS AND RESULTS

A 6-month prospective observational study was conducted among 114 patients with coronary artery disease (CAD) who were treated with pravastatin. The plaque volume, as assessed using volumetric intravascular ultrasound, decreased significantly by 9.9% (p < 0.0001 vs baseline). In a multivariate regression analysis with traditional risk factors, ΔLDL-C/HDL-C (β: 0.473, p = 0.0001) and the baseline BMI (β: 0.249, p = 0.004) were identified as independent predictors of the Δplaque volume. The patients were divided using the 50th percentile of the baseline BMI and the 50th percentile of the ΔLDL-C/HDL-C ratio as cutoffs, and a model for predicting coronary atherosclerotic regression was prepared using a combination of the two variables. The Δplaque volumes were -18.3%, -14.1%, -4.8%, and -2.2% for the groups with ΔLDL-C/HDL-C ≤ -22.2% and a BMI ≤ 24.1 kg/m(2), ΔLDL-C/HDL-C ≤ -22.2% and ΔBMI >24.1 kg/m(2), ΔLDL-C/HDL-C > -22.2% and BMI ≤ 24.1 kg/m(2), and ΔLDL-C/HDL-C > -22.2% and BMI >24.1 kg/m(2), respectively (p = 0.003).

CONCLUSION

A predictive model for coronary plaque regression based on a combination of ΔLDL-C/HDL-C and the baseline BMI may be a useful clinical tool in patients with CAD.