Abstract
Background To identify patients with early signs of myocardial perfusion reduction, a reference base for perfusion measures is needed. Objective To analyze perfusion parameters derived from dynamic computed tomography perfusion imaging (CTPI) in patients with suspected coronary artery disease (CAD), and relationship with risk factors. Methods In this multicenter study, coronary CT angiography (cCTA) and dynamic CTPI were performed by second-generation dual-source CT in patients suspected of CAD. Risk factors were collected from hospital records. Patients with visual perfusion defects on CTPI, previous coronary intervention, or missing risk factor details were excluded. This analysis included 98 patients (mean age ± standard deviation [SD], 59.0 ± 8.6yrs; 73 male). Global measures of left ventricular myocardial blood flow (MBF), myocardial blood volume (MBV) and volume transfer constant (K trans ) were calculated. Results Mean MBF was 139.3 ± 31.4 mL/100 mL/min, MBV 19.1 ± 2.7 mL/100 mL, and K trans 85.0 ± 17.5 mL/100 mL/min. No significant differences in perfusion parameters were found by gender or age category. Hypertension and diabetes mellitus resulted in lower perfusion parameters (hypertension vs normotension: MBV 18.5 ± 3.0 vs 19.7 ± 2.3 mL/100 mL and K trans 82.0 ± 18.0 vs 89.0 ± 16.0, p < 0.05; diabetes vs no diabetes: MBF 128.5 ± 31.5 vs 144.0 ± 30.5 mL/100 mL/min and MBV 17.9 ± 2.4 vs 19.4 ± 2.8 mL/100 mL, p < 0.05). In patients with hyperlipidemia, MBF was higher (146.8 ± 34.4 vs 130.7 ± 24.3 mL/100 mL/min, p < 0.05). Smoking and family history did not show perfusion parameter differences. Conclusions Dynamic CTPI identifies early perfusion disturbances in conditions like diabetes and hypertension. With further standardization, absolute perfusion measures may improve CAD risk stratification in patients without visual perfusion defects.
| Original language | English |
|---|---|
| Pages (from-to) | 301-308 |
| Number of pages | 8 |
| Journal | Journal of Cardiovascular Computed Tomography |
| Volume | 10 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1 Jul 2016 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cardiovascular risk factors
- Computed tomography
- Dynamic perfusion
- Myocardial blood flow
- Myocardial perfusion imaging
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