The Physiology of Perfusion & Permeability
Hai-Ling Margaret Cheng1

1Institute of Biomaterials & Biomedical Engineering, The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, Ted Rogers Centre for Heart Research, University of Toronto, Toronto, Canada

Synopsis

This talk provides an overview of several different parameters that are associated with microvascular physiology, such as perfusion, transit time, and capillary permeability. Their biological meaning is explored, as well as their relevance in the context of various disease settings. Finally, the three main MRI techniques for measuring microvascular physiology (DCE-MRI, DSC-MRI, and ASL) are briefly introduced in relation to the parameters they are capable of measuring.

Target audience

This course is designed for basic research scientists and clinicians.

Objectives

To understand the definition of perfusion and related microvascular parameters, their biological importance and inter-relationships, and the relevance of their measurement in the context of different disease settings.

Overview

The microvasculature is an important part of our circulatory system, as it is the main site for the transport of materials between blood and tissue. Oxygen, nutrients, and other essential solutes are delivered to tissue, while carbon dioxide and other waste products are removed. This exchange is regulated in part by the permeable endothelium of capillaries, which are the only blood vessels in the body that allow materials to cross the vessel wall. However, the transport function is also determined by the architecture of the microvessels (i.e. arterioles, capillaries, and venules). For example, the number, size, and arrangement of microvessels are an important determinant of how much blood flows through tissue, and the tone of vessels may be adjusted by passive and active mechanisms in response to changing metabolic demands.

In describing the physiology of the microvasculature, perfusion is perhaps the most frequently measured parameter. Perfusion refers to the total delivery of blood through the local capillary bed of a tissue region. It is a volumetric flow rate and is normally expressed in units of volume of blood delivered per unit time for a given mass of tissue (mL/min/100 g). A variety of techniques have been developed for the measurement of perfusion, including microspheres (invasive gold-standard) and imaging techniques based on nuclear medicine, CT, ultrasound, and MRI.

Although perfusion is an important indicator of how “well” local tissue regions are being nourished, other microvascular parameters can provide complementary insight into tissue physiology. One such parameter is blood volume, which describes the sub-volume of a tissue volume that is occupied by blood vessels (in mL/100 g) and is a particularly useful metric for the diagnosis of certain diseases, such as cancer. Another useful metric is the mean transit time (MTT), which describes the length of time a certain volume of blood spends in the capillary circulation. The MTT is determined by the ratio of the capillary blood volume to the capillary flow rate. The general relationship between perfusion (F), blood volume (BV), and mean transit time is given by the central volume theorem [1]: F = BV / MTT.

Note that although F, BV, and MTT are related through the central volume theorem, they are distinct physiological quantities. Perfusion does not explicitly depend on either blood volume or the velocity of blood. For example, an increase of blood velocity in a fixed capillary bed or an increase in the number of open capillaries but with blood moving at the same velocity in each capillary would both lead to an increase in perfusion. Furthermore, even specifying capillary velocity and capillary volume is not sufficient to determine perfusion. Imagine two idealized capillary beds, one with two sets of shorter capillaries, and one with a single set of capillaries twice as long. In both beds, the blood velocity is the same, and they have the same blood volume. However, the perfusion is twice as large in the bed with two sets of shorter capillaries, because the volume of blood delivered to the bed per minute is twice as great [2]. Why is this? Because we have failed to account for the capillary transit time, which differs between the two scenarios. In the capillary bed with longer capillaries, the transit time is twice as long, thereby leading to a perfusion value that is half as large (by the central volume theorem). This example illustrates simply how vessel architecture has a profound influence on perfusion. Figure 1 illustrates differences in microvascular patterns as found in various tissues.

Capillary permeability is another important microvascular parameter that describes the ability of capillaries to allow the exchange of small molecules (e.g. ions, water, nutrients) and even cells (e.g. lymphocytes) between the vessel lumen and surrounding tissue spaces. This exchange occurs via gaps between endothelial cells (EC junctions) that are strictly regulated depending on the type of tissue and the physiological state. The higher the permeability, the “leakier” the vessel. Note that vessel wall permeability is organ-specific and contrast agent-specific (depends on the molecular weight, hydrodynamic diameter, charge, hydrophilicity, etc.) [3]. Note also that permeability is measurable only if the imaging contrast agent can cross the endothelial wall and into surrounding tissue spaces. It is for this reason that permeability is measurable using only a small subset of perfusion techniques. If permeability can be measured, however, then it is possible to measure also the interstitial space if an appropriate contrast agent is employed. For example, gadolinium-based extracellular chelates, which distribute strictly outside of cells once they leave capillaries, are often used to estimate the interstitial tissue volume in certain applications.

To see the relevance of measuring microvascular parameters for diagnosis and treatment monitoring, we will review briefly several diseases and conditions where the microvasculature is affected. Cancer is a disease that involves extensive alterations to blood vessels. For example, increased permeability [4], heterogeneity, and compromised blood flow (i.e. increased MTT) are all hallmarks of tumors. In the brain, stroke is associated with reduced perfusion and blood volume and increased MTT. Disruption of the blood-brain-barrier (increased permeability) is found in dementia, acute ischemic stroke [5], and multiple sclerosis [6]. More subtle and chronic disruptions are found in cerebral small vessel disease [7], diabetes [8], and Alzheimer’s [9]. Evidently, MRI methods that allow us to measure these physiological changes in the microvasculature are critical to early detection, diagnosis, and evaluating treatment efficacy.

Finally, in choosing the imaging technique for measuring microvascular physiology, it is important to appreciate the advantages and limitations associated with the three main methods that exist in MRI: dynamic contrast-enhanced (DCE)-MRI, dynamic susceptibility contrast (DSC)-MRI, and arterial spin labeling (ASL). The first two rely on the use of exogenous contrast agents to generate contrast, while ASL uses arterial water as an endogenous tracer and is, therefore, considered “contrast-free”. ASL is an attractive alternative for patients who cannot be administered contrast agents, such as those with acute kidney injury. It is ideally suited to perfusion measurement in high-flow organs, such as the brain and kidney. However, a broader range of parameters can be assessed using the other methods. DSC-MRI relies on the contrast agent remaining inside blood vessels for accurate measurement of perfusion and blood volume. This technique is particularly useful in the brain, where the integrity of the blood-brain barrier (BBB) ensures the condition on the contrast remaining intra-vascular. DCE-MRI, on the other hand, relies on the diffusion of contrast agent across the endothelium into the interstitial space to achieve significant enhancement. Many parameters are accessible using DCE-MRI, including capillary permeability and interstitial volume.

Acknowledgements

Funding support from The Heart & Stroke Foundation of Canada and the Natural Sciences and Engineering Research Council of Canada.

References

[1] Stewart GN. Researches on the circulation time in organs and on the influences which affect it. Parts I-III. J Physiol 15, 1-89 (1893).

[2] Richard Buxton. “Introduction to Functional Magnetic Resonance Imaging: Principles and Techniques” (2009).

[3] Lemasson B et al. Monitoring blood-brain barrier status in a rat model of glioma receiving therapy: dual injection of low-molecular-weight and macromolecular MR contrast media. Radiology 257, 342-52 (2010).

[4] Jain RK. Molecular regulation of vessel maturation. Nat Med 9, 685-93 (2003).

[5] Kassner A et al. Recombinant tissue plasminogen activator increases blood-brain barrier disruption in acute ischemic stroke: an MR imaging permeability study. AJNR Am J Neuroradiol 30, 1864-9 (2009).

[6] Jelescu IO et al. Dual-temporal resolution dynamic contrast-enhanced MRI protocol for blood-brain barrier permeability measurement in enhancing multiple sclerosis lesions. J Magn Reson Imaging 33, 1291-300 (2011).

[7] Wardlaw JM et al. Changes in background blood-brain barrier integrity between lacunar and cortical ischemic stroke subtypes. Stroke 39, 1327-32 (2008).

[8] Starr JM et al. Increased blood-brain barrier permeability in type II diabetes demonstrated by gadolinium magnetic resonance imaging. J Neurol Neurosurg Psychiatry 74, 70-6 (2003).

[9] Starr JM et al. Blood-brain barrier permeability in Alzheimer’s disease: a case-control MRI study. Psychiatry Res 171, 232-41 (2009).

Figures

Figure 1. Microvascular networks in different tissues as visualized by scanning electron microscopy. Scale bars indicate a length of 40 μm. From: Axel R. Pries, Timothy W. Secomb. “Blood flow in microvascular networks,” Supplement 9: Handbook of Physiology, The Cardiovascular System, Microcirculation (2008).



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)