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Updated: Mar 20, 2026

In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension:
Rozemarijn Vliegenthart1, Carlo N De Cecco2, Julian L Wichmann3
1Medical University of South Carolina, Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, 25 Courtenay Drive, Charleston, SC, 29425, USA; University of Groningen, University Medical Center Groningen, Center for Medical Imaging-North East Netherlands, Department of Radiology, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.
Insights
Dynamic computed tomography perfusion imaging (CTPI) reveals early myocardial perfusion reduction in patients with hypertension and diabetes. These findings suggest CTPI can aid in risk stratification for coronary artery disease (CAD).
Area of Science:
- Cardiovascular Imaging
- Radiology
- Medical Diagnostics
Background:
- Establishing reference values for myocardial perfusion is crucial for detecting early signs of reduction.
- Dynamic computed tomography perfusion imaging (CTPI) offers a potential method for assessing myocardial perfusion.
Purpose of the Study:
- To analyze perfusion parameters from dynamic CTPI in patients with suspected coronary artery disease (CAD).
- To investigate the relationship between these perfusion parameters and common cardiovascular risk factors.
Main Methods:
- A multicenter study utilized second-generation dual-source CT for coronary CT angiography (cCTA) and dynamic CTPI.
- 98 patients suspected of CAD were included, excluding those with visual perfusion defects or prior interventions.
- Global left ventricular myocardial blood flow (MBF), myocardial blood volume (MBV), and volume transfer constant (K(trans)) were calculated.
Main Results:
- No significant differences in perfusion parameters were observed based on gender or age.
- Hypertension and diabetes mellitus were associated with significantly lower MBV and K(trans) (hypertension) and lower MBF and MBV (diabetes).
- Hyperlipidemia showed a trend towards higher MBF, while smoking and family history did not impact perfusion parameters.
Conclusions:
- Dynamic CTPI effectively identifies early perfusion disturbances associated with conditions like diabetes and hypertension.
- Standardization of absolute perfusion measures derived from CTPI could enhance risk stratification for CAD in patients without apparent perfusion defects.
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 Ktrans 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.
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