aUniversité Paris Descartes, Assistance Publique-Hôpitaux de Paris, Hôtel-Dieu Centre de Diagnostic et de Thérapeutique, Paris, France
bUniversity of New South Wales, St. Vincent's Hospital and Clinic, Victor Chang Cardiac Research Institute, Sydney, Australia
Correspondence to Professor Michel Safar, Centre de Diagnostic et de Thérapeutique, Hôtel-Dieu 1, place du Parvis Notre-Dame, 75181 Paris Cedex 04, France Tel: +33 1 42 34 80 25; fax: +33 1 42 34 86 32; e-mail: email@example.com
In the past, the concepts of tube mechanics, first developed to better adapt the structure of conducting pipes in hydraulic networks, were adapted to the analysis of large vessels mechanical behaviour. It appeared that the mechanical behaviour of large arteries was extremely complex because these ‘tubes’ have marked anisotropy, exhibit viscoelastic nonlinear properties and have powerful adaptive mechanisms [1,2]. Moreover, no single arterial segment has identical viscoelastic properties. Even nowadays, it is difficult to integrate segmental arterial properties along the whole vascular tree. Despite these obstacles, simple parameters based on arterial wave propagation have been developed and have demonstrated their usefulness not only in representing basic mechanical behaviour but also in patient treatment and prognosis estimation.
Briefly, the heart is conceived as generating cyclical pressure and flow waves. Because of the elasticity of the aorta and the major conduit arteries, the pressure and flow waves are not transmitted instantaneously to the periphery, but propagate through the arterial tree with a certain speed, which we call wave speed or pulse wave velocity (PWV) (Fig. 1) [1,2]. A realistic model of the arterial tree is a simple tube that terminates at the peripheral resistance, but the distributed elastic properties of which permit generation of a pressure wave, which travels along the tube. This model might be regarded as an oversimplification of the arterial tree, but constitutes a vast improvement on the traditional Windkessel model, which is, by definition, nonpropagative. In the model as in life, the wave takes a finite time to travel along the tube such that there is delay in the foot of the wave at different sites between the proximal and distal part of the tube. Further, high resistance at the tube's end (which represents in life the peripheral resistance) creates wave reflection, with generation of a retrograde wave. This is responsible for the appearance of secondary fluctuations on the pulse, and difference in amplitude of the pressure wave itself between central and peripheral arteries (also as seen in life).
According to this classical description, four characteristics of good modelling may be identified to describe adequately the propagation and elasticity of a given arterial segment : a good model is not only a simplified version of reality but one which relates to a specific goal; a good model uses measurable parameters to describe (overall) system function; a good model helps to identify and define specific future experiments, which are required to more realistically describe system function and a good model allows one to use accessible measurements to predict parameters that are presently impossible or impractical to measure directly; this here represents arterial PWV, the ratio between a distance and a transit time along the vascular tree (Fig. 1).
In the present issue of this journal, an emerging measure of PWV [3,4], called brachial–ankle PWV (ba-PWV), is proposed and compared with the gold standard, which is most widely used in clinical practice, carotid–femoral PWV (CF-PWV) . For transit time measurements of ba-PWV, the time between the brachial and femoral measurement sites is used . The ba-PWV measurement is calculated as the ‘distance’ between the brachial and the tibial artery and the ‘transit time’ between these two arteries. The aortic ‘PWV’ measurement is calculated as the ‘distance’ between the carotid and the femoral artery. If carotid–femoral distance is not available, the distance is calculated from simple statistical regressions derived from body height . It should be noted that the anatomical course of ba-PWV corresponds at least to two different arterial segments, the first one from the carotid to the brachial artery and the second one from the carotid to the tibial artery through the aorta and the femoral artery. These two segments differ markedly from the CF-PWV in terms of geometry, structure and function as well as the influence of age [1,2]. CF-PWV, despite some particularities related to aortic length, is more representative of a ‘classical’ arterial segment, with a relatively homogeneous vascular tissue and a relatively simple transmission of wave reflection along a tube [1,2]. Finally, because of the complexity of the ‘brachial–ankle’ arterial system, the question is raised to determine whether the term ‘stiffness’ is appropriate to define the ratio between a virtual brachial–ankle distance and the measurement of the brachial–ankle ‘transit time’. This transit does not correspond to any anatomical arterial course. This parameter rather represents the time necessary to obtain a given value of brachial–tibial amplification of SBP in any individual patient (Fig. 1).
The major interest of the present brachial–ankle model is, in fact, to become a possible mechanical biomarker of cardiovascular risk. Japanese researchers advocated the use of the brachial–ankle device and showed the aortic PWV was the primary independent correlate of ba-PWV, followed by leg PWV [5–8]. Remarks concerning the calculation of the path length apply here consistently. However, in small cohorts of either elderly community-dwelling people or coronary heart disease patients, ba-PWV was an independent predictor for cardiovascular deaths and events [6,7].
In recent years, several available mechanical biomarkers of cardiovascular risk, such as the ankle–brachial index (ABI) , the ambulatory arterial stiffness index (AASI)  or the carotid pulse pressure (PP)/brachial PP ratio  have been proposed as significant predictors of cardiovascular risk. Frequently, the predictive value of such risk factors is clearly observed, although the mechanical role of such parameters remains yet difficult to identify. ABI is often presented as a marker of peripheral arterial disease but, in the absence of arterial occlusion, ABI is an index of wave reflections. AASI, which is derived from ambulatory blood pressure measurement, is a novel method of evaluation of brachial SBP, which is partly dependent on arterial stiffness. The carotid PP/brachial PP ratio is an index of PP propagation from central to peripheral arteries with a major impact on cardiac structure and function . Nowadays, it is the role of scientific societies to define further the pathophysiological role and to compare the predictive values of all these mechanical parameters in cardiovascular epidemiology and therapeutics .
We thank Dr Anne Safar for helpful and stimulating discussions.
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