Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension: Insights from a multicenter registry

Rozemarijn Vliegenthart; Carlo N De Cecco; Julian L Wichmann; Felix G Meinel; Gert Jan Pelgrim; Christian Tesche; Ullrich Ebersberger; Francesca Pugliese; Fabian Bamberg; Yeon Hyeon Choe; Yining Wang; U Joseph Schoepf

doi:10.1016/j.jcct.2016.05.005

Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension: Insights from a multicenter registry

J Cardiovasc Comput Tomogr. 2016 Jul-Aug;10(4):301-8. doi: 10.1016/j.jcct.2016.05.005. Epub 2016 May 24.

Authors

Affiliations

¹ Medical 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. Electronic address: r.vliegenthart@umcg.nl.
² Medical University of South Carolina, Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, 25 Courtenay Drive, Charleston, SC, 29425, USA. Electronic address: carlodececco@gmail.com.
³ Medical University of South Carolina, Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, 25 Courtenay Drive, Charleston, SC, 29425, USA; University Hospital Frankfurt, Department of Diagnostic and Interventional Radiology, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. Electronic address: docwichmann@gmail.com.
⁴ Medical University of South Carolina, Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, 25 Courtenay Drive, Charleston, SC, 29425, USA; Ludwig-Maximilians-University Hospital, Institute for Clinical Radiology, Marchioninistr. 15, 81377, Munich, Germany. Electronic address: fmeinel@med.lmu.de.
⁵ University of Groningen, University Medical Center Groningen, Center for Medical Imaging-North East Netherlands, Department of Radiology, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands. Electronic address: g.j.pelgrim@umcg.nl.
⁶ Medical University of South Carolina, Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, 25 Courtenay Drive, Charleston, SC, 29425, USA; Heart Center Munich-Bogenhausen, Department of Cardiology and Intensive Care Medicine, Munich Municipal Hospital Group, Englschalkinger Str. 77, 81925, Munich, Germany. Electronic address: tesche@musc.edu.
⁷ Heart Center Munich-Bogenhausen, Department of Cardiology and Intensive Care Medicine, Munich Municipal Hospital Group, Englschalkinger Str. 77, 81925, Munich, Germany. Electronic address: ebersberger@gmx.net.
⁸ Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Centre for Advanced Cardiovascular Imaging, NIHR Cardiovascular Biomedical Research Unit at Barts, UK William Harvey Research Institute, Barts Heart Centre, 2nd Floor Cardiac Imaging, West Smithfield, London, EC1A 7BE, UK. Electronic address: f.pugliese@qmul.ac.uk.
⁹ University of Tuebingen, Department of Radiology, Hoppe-Seyler-Straße 3, 72076, Tuebingen, Germany. Electronic address: fabian.bamberg@uni-tuebingen.de.
¹⁰ Samsung Medical Center, Sungkyunkwan University School of Medicine, Department of Radiology, 81 Ilwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. Electronic address: ychoe11@gmail.com.
¹¹ Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Department of Radiology, No.1 Shuaifuyuan, Wangfujing, DongCheng District, Beijing, 100730, China. Electronic address: wangyining@pumch.cn.
¹² Medical University of South Carolina, Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, 25 Courtenay Drive, Charleston, SC, 29425, USA; Medical University of South Carolina, Division of Cardiology, Department of Medicine, 25 Courtenay Drive, Charleston, SC, 29425, USA. Electronic address: schoepf@musc.edu.

PMID: 27255411
DOI: 10.1016/j.jcct.2016.05.005

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 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.

Keywords: Cardiovascular risk factors; Computed tomography; Dynamic perfusion; Myocardial blood flow; Myocardial perfusion imaging.

Publication types

Multicenter Study

MeSH terms

Aged
Asia
Blood Flow Velocity
Computed Tomography Angiography*
Coronary Angiography / methods*
Coronary Artery Disease / diagnostic imaging*
Coronary Artery Disease / etiology
Coronary Artery Disease / physiopathology
Coronary Circulation*
Coronary Vessels / diagnostic imaging*
Coronary Vessels / physiopathology
Diabetic Angiopathies / diagnostic imaging*
Diabetic Angiopathies / etiology
Diabetic Angiopathies / physiopathology
Early Diagnosis
Europe
Female
Humans
Hypertension / complications*
Hypertension / diagnosis
Male
Middle Aged
Myocardial Perfusion Imaging / methods*
Predictive Value of Tests
Prognosis
Registries
Retrospective Studies
Risk Assessment
Risk Factors
United States