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In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Prognostic implications of quantified coronary atherosclerosis and myocardial perfusion in diabetes
Matias Mäenpää1, Ruurt A Jukema2, Pepijn van Diemen2
1Turku PET Centre, Turku University Hospital and University of Turku, P.O. Box 52, 20521, Turku, Finland. matmae@utu.fi.
Insights
Coronary artery disease (CAD) risk increases with diabetes. Quantitative imaging shows plaque burden predicts outcomes in all patients, but normal perfusion doesn't guarantee safety in diabetics due to higher plaque burden.
Area of Science:
- Cardiovascular Imaging
- Diabetology
- Preventive Cardiology
Background:
- Coronary artery disease (CAD) significantly increases cardiovascular event risk in diabetic patients.
- Coronary computed tomography angiography (CTA) allows plaque burden quantification, while positron emission tomography (PET) assesses myocardial perfusion.
- This study investigates the prognostic value of quantitative plaque burden and perfusion in diabetic versus non-diabetic individuals with suspected CAD.
Purpose of the Study:
- To evaluate the prognostic implications of quantitative coronary plaque burden and myocardial perfusion in patients with suspected CAD, comparing diabetic and non-diabetic individuals.
- To determine if quantitative imaging markers can refine risk stratification in patients with diabetes and suspected CAD.
- To explore the interplay between diabetes, plaque burden, and perfusion abnormalities in predicting adverse cardiovascular outcomes.
Main Methods:
- An observational cohort study involving 1311 symptomatic patients with suspected CAD.
- Coronary CTA and [15O]H2O PET perfusion imaging were performed.
- Coronary plaque burden was quantified using AI-based analysis (percent atheroma volume, PAV); abnormal perfusion was defined by stress myocardial blood flow (sMBF). The composite endpoint included death, myocardial infarction (MI), or unstable angina pectoris (UAP) over 7 years.
Main Results:
- The annual event rate was 0.8% in non-diabetic patients with normal perfusion, rising with diabetes (2.3%), abnormal perfusion (2.6%), or both (3.2%) (p < 0.001).
- Diabetic patients with normal perfusion had double the PAV compared to non-diabetics (8.2% vs. 4.1%, p < 0.001).
- PAV independently predicted adverse outcomes in both groups. sMBF predicted outcomes in non-diabetics but not in diabetics.
Conclusions:
- Quantified coronary atherosclerotic plaque burden is a significant predictor of long-term cardiovascular outcomes in both diabetic and non-diabetic patients.
- In diabetic patients, normal myocardial perfusion does not negate elevated event risk, largely due to increased coronary plaque burden.
- Quantitative imaging for detailed CAD phenotyping provides crucial insights into the complex relationship between diabetes and clinical outcomes.
Background:
Coronary artery disease (CAD) is a major contributor to cardiovascular events in individuals with diabetes. Quantification of coronary atherosclerotic burden is now feasible from coronary computed tomography angiography (CTA) whereas positron emission tomography (PET) enables quantitative assessment of myocardial perfusion. We studied the prognostic implications of quantitatively measured coronary plaque burden and myocardial perfusion in diabetic vs. non-diabetic patients with suspected CAD.
Methods:
In this observational cohort study, 1311 symptomatic patients with suspected CAD underwent coronary CTA and [15O]H2O PET perfusion imaging. Coronary plaque burden was quantified using artificial intelligence-based analysis and reported as percent atheroma volume (PAV). Myocardial perfusion was assessed as regional stress myocardial blood flow (sMBF), with abnormal perfusion defined as ≥ 2 adjacent segments with sMBF < 2.3 ml/g/min. The composite endpoint was all-cause death, myocardial infarction (MI), or unstable angina pectoris (UAP) over 7 years.
Results:
Among the 1311 patients, 251 (19%) had diabetes and 134 (10%) experienced an adverse event during follow-up. The annual event rate was low (0.8% [95% CI 0.6-1.1%]) in non-diabetic patients with normal myocardial perfusion and increased significantly with the presence of either diabetes (2.3% [95% CI 1.4-3.8%]), abnormal perfusion (2.6% [95% CI 2.1-3.3%]), or both (3.2% [95% CI 2.1-4.8%]) (p < 0.001). Among patients with normal myocardial perfusion, those with diabetes had two-fold PAV as compared with non-diabetic individuals (median 8.2% vs. 4.1%, p < 0.001). In multivariable Cox regression models, both PAV (HR 1.03 [95% CI 1.01-1.05] per 1% increase, p < 0.001) and regional sMBF (HR 1.04 [95% CI 1.01-1.07] per 0.1 ml/g/min decrease, p = 0.016) were independent predictors of adverse outcome in non-diabetic patients. In diabetic patients, only PAV (HR 1.04 [95% CI 1.01-1.07], p = 0.014) was predictive, whereas sMBF was not.
Conclusions:
Coronary atherosclerotic plaque burden appears as an important predictor of long-term cardiovascular outcomes both in diabetic and non-diabetic patients. In patients with diabetes, normal myocardial perfusion does not necessarily imply low event risk, partly attributable to higher coronary plaque burden. Quantitative imaging methods for detailed CAD phenotyping shed light on the complex relationship between diabetes and clinical outcomes.
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