Stiffening of the human aorta is associated with a number of factors, particularly aging, sedentary lifestyle and cardiovascular disease. The physiological consequences of aortic stiffening can be severe, including increased cardiac afterload, reduced coronary perfusion and isolated systolic hypertension. Moreover, aortic wave velocity, an accepted metric of central arterial stiffening, has been reported to be the single best predictor of cardiovascular risk among ten variables studied. However, widespread clinical assessment of aortic stiffness and related therapeutic interventions has been impeded by the lack of a robust, noninvasive measurement method. All techniques currently employed to noninvasively assess central arterial stiffness suffer significant methodological weaknesses, which limit their accuracy and/or pertinance to the elastic aorta. The applicant has recently proposed a novel and rapid means to determine aortic stiffness using magnetic resonance (MR) methodology. The technique employs a one-dimensional time-of-flight sequence to measure flow wave velocity (WV) in the thoracic aorta with an acquisition time of one cardiac cycle. Extensive testing, in both compliant tubes and in vivo, has established the validity of the proposed MR method, thereby laying the groundwork for larger-scale studies of aortic stiffness in clinically relevant subject cohorts. In this project, we will correlate aortic WV with age in a cross-sectional MR study of 280 adult men and women, representing seven decades of age. Screening criteria will be imposed in order to exclude persons with cardiovascular disease. In addition to a normal, sedentary cohort (112 subjects) we will also recruit endurance-trained athletes (56 subjects) and patients with isolated systolic hypertension (112 subjects). These groups respectively represent normal, successful and accelerated arterial aging, which we hypothesize will be differentiated on the basis of absolute WV and rate of increase of WV with age. We further hypothesize that in the hypertensive group, systolic blood pressure may be a strong predictor of WV. All enrolled participants will undergo a health and fitness assessment within the Virginia Commonwealth University General Clinical Research Center, in order to permit correlation of measured wave velocity with key clinical indicators (blood pressure, maximum oxygen consumption, plasma lipoprotein, glucose and insulin levels). Secondary statistical analysis will introduce such clinical indicators as covariables, by which the WV versus age regressions will be adjusted. Tertiary analysis will seek the combination of all variables that yields the best predictive model of WV. Lastly, the potential value of WV alone, as well as the ratio of WV to peak blood velocity, as a predictor of cardiovascular risk will be explored using Framingham risk scores as a correlate.
