Aortic valve disease (AVD) occurs when aortic valve leaflets become thickened and stiff due to fibrotic remodeling and formation of calcific nodules. Consequently, aortic stenosis develops when blood distribution to the body is compromised due to the valve not being able open properly. Underdiagnosis of patients remains a problem because?even when severe?AVD can be asymptomatic. Asymptomatic patients are not referred to specialists for advanced imaging procedures that can diagnose AVD. Delayed intervention of aortic stenosis leads to cardiac remodeling and eventually cardiac failure. In order to address problems associated with underdiagnosis, screening strategies that can be implemented into routine physical examinations are needed to detect AVD in asymptomatic patients. The vibrations of aortic valve leaflets during valve closure produce the audible frequencies (S2 sound) heard through a doctor's stethoscope. We hypothesize that microstructural differences in aortic valve remodeling and related alterations in biomechanics can be identified by changes in the valvular acoustic characteristics (S2 sound) in early AVD. Structural and composition changes in the extracellular matrix (ECM) lead to the biomechanical alterations that cause AVD. The goals of the proposed study, tested through two aims, is to identify how changes in aortic valve biomechanics influence heart sound characteristics.
Aim 1 will identify whether ECM structural alterations induce changes in S2 sound frequency and time characteristics in a mouse model of aortic stenosis.
Aim 2 will further develop a new technique to analyze mouse aortic valve biomechanics, providing new insight into the microstructural and functional leaflet alterations during various AVD stages. The outcomes of the proposed research can contribute to the future development of a non-invasive diagnostic tool to identify patients who are at risk of developing or have severe but asymptomatic AVD. This work could have a major impact in AVD management in two ways: 1) enable identification of patients in early, reversible disease stages, enabling opportunities to explore new non-invasive treatments, and 2) diagnose asymptomatic patients with late-stage AVD, leading to lifesaving valve replacement surgery.
Aortic valve disease (AVD), a disease with poor prognosis if left untreated, is often underdiagnosed due to a lack of screening strategies and symptoms to identify patients, even for late disease stages. In this proposal, we hypothesize that the changes in aortic valve structure that occur during AVD can be identified by alterations in sounds recorded from a doctor?s stethoscope. The outcomes of the proposed research can contribute to the development of a non- invasive diagnostic tool to identify patients with AVD.
