Appendix 1: Physical Quantities for Selected Arteries
9.2 Measurements and Applications
9.2.5 Functional Imaging in Cardiovascular Disease
This section briefly describes applications of functional imaging systems in car- diovascular disease. Some of these techniques are still at the research stage and are yet to enter clinical practice. This is necessarily a brief and selective overview:
readers are referred to more specialist literature for more information on these areas.
Perfusion. Quantitative measurement of local perfusion in units of ml min−1g−1 may be performed by PET using O-15 incorporated into water. Other imaging modalities provide images related to perfusion. The method most widely adopted in clinical practice is gamma camera imaging using Tl-201 whose uptake in the myocardium is proportional to local perfusion. Typically imaging is performed after some form of cardiac stress (e.g. exercise) and then again at rest, with the two patterns of uptake compared. As noted above contrast agents for MRI and ultra- sound can also be used to image perfusion.
Myocardial architecture. Specialised MRI techniques provide unique windows on aspects of myocardial microstructure and mechanical function. Diffusion tensor imaging (DTI) permits non-invasive investigation of the musclefibre architecture of the myocardium, which promises to be a useful clinical tool.
Inflammation. It is known that inflammation is a key component of cardiovas- cular disease. Inflammation is associated with high concentrations of macrophages;
Fig. 9.17 PET FDG image of the carotid arteries.aCT angiogram.b18F-FDG uptake (arrow) in the right carotid artery on fused 18F-FDG PET–CT images. From; Tarkin et al. (2014),©2014 Macmillan Publishers Limited, with permission from Walters Kluwer Health, Inc.
these are a type of white cell that engulf and digest damaged or dead cells.
Both PET and MRI have been used to image inflammation. PET imaging involves the use of F-18 in Fluorodeoxyglucose (FDG). FDG contains glucose which is taken up in higher concentration by highly metabolic pathologies such as inflam- mation or tumours. Increased uptake in atherosclerotic plaque is indicative of metabolic activity of macrophages (Tarkin et al.2014) (Fig.9.17). MR imaging of inflammation involves the use of USPIOs (ultrasmall paramagnetic iron oxide particles). In abdominal aortic aneurysms these are taken up by macrophages (Richards et al.2011) (Fig.9.18).
Micro-calcification. In the early stages of atherosclerosis, micro-calcifications occur in response to inflammation. This is thought to be a defensive response in an attempt to seal off the affected area. PET imaging of micro-calcification involves the Fig. 9.18 USPIO uptake in patients with abdominal aortic aneurysm.a: UPSIO uptake around the lumen.bDiffuse patchy uptake throughout the intraluminal thrombus.cDiscrete focal area of USPIO involving the wall of the AAA that is distinct from the periluminal region. d, e;
corresponding MRI T2 weighted anatomic images. The focal uptake seen in c is thought to represent focal inflammation and to be an indicator of increased risk of rupture. Reprinted by permission from Macmillan Publishers Ltd: Richards et al. (2011); copyright (2011)
use of F-18 sodiumfluoride where it has been used in the coronary arteries to detect early disease (Dweck et al.2012).
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Chapter 10
Modelling of the Cardiovascular System
D. Rodney Hose and Barry J. Doyle
Learning outcomes
1. Describe the purpose of a cardiovascular computational model.
2. Understand the complexity of such a model.
3. Understand the difference between zero, one, three and multi-dimensional models.
4. Understand the role of rigid and compliant-wall models of the cardiovascular system.
5. Understand how to apply a computational model to represent a specific region of the cardiovascular system.
This chapter introduces the process of modelling of the cardiovascular system.
Modelling incorporates the representation of the fundamental mechanics of the cardiovascular system, as well as the determination of important features needed to ensure that the model captures the essential information relevant to the problem.