BACKGROUND AND AIM OF THE STUDY: Because the hemodynamic basis of aortic valve area (AVA) has never been validated in vivo, several alternative indices have been proposed to quantify the severity of aortic stenosis (AS). This study was designed to assess the fluid-dynamics of aortic valve stenosis in order to clarify which index best accounts for disease severity. The diagnostic implications of reversed deltaP during ejection were also investigated. METHODS: Chronic valvular AS characterized by stiff leaflets without commissural fusion was created surgically in eight adult mongrel dogs; three additional animals were used as controls. At two-week intervals (three studies per dog), simultaneous micromanometer pressure and transit-time Q measurements were collected under different hemodynamic conditions. Instantaneous deltaP and Q signals were processed digitally and fitted to a modified form of the unsteady Bernoulli equation in which AS is characterized by effective valve area. RESULTS: An unsteady Bernoulli equation accurately predicted measured instantaneous AP values (R = 0.97+/-0.06), and a quadratic correlation was observed between instantaneously fitted and Gorlin-derived AVA. Additionally, deltaP < 0 mmHg during late ejection was observed in the majority of AS datasets, with a normalized time to deltaP reversal of 93+/-13% for AS animals versus 69+/-36% for controls (p <0.0005). Time to deltaP reversal inversely correlated with the Strouhal number (R = -0.77), and was responsible for an overestimation of mean systolic transvalvular deltaP and Q that resulted in a significant bias in the Gorlin method. Error was highest in moderate stenosis with low transvalvular output. CONCLUSION: Unsteady fluid-dynamics supports AVA over other measures of AS such as aortic valve resistance. However importantly, late-ejection reversal of deltaP precludes estimating the systolic ejection period from pressure tracings, and accounts for an additional source of error when AS is quantified invasively.
BACKGROUND AND AIM OF THE STUDY: Because the hemodynamic basis of aortic valve area (AVA) has never been validated in vivo, several alternative indices have been proposed to quantify the severity of aortic stenosis (AS). This study was designed to assess the fluid-dynamics of aortic valve stenosis in order to clarify which index best accounts for disease severity. The diagnostic implications of reversed deltaP during ejection were also investigated. METHODS: Chronic valvular AS characterized by stiff leaflets without commissural fusion was created surgically in eight adult mongrel dogs; three additional animals were used as controls. At two-week intervals (three studies per dog), simultaneous micromanometer pressure and transit-time Q measurements were collected under different hemodynamic conditions. Instantaneous deltaP and Q signals were processed digitally and fitted to a modified form of the unsteady Bernoulli equation in which AS is characterized by effective valve area. RESULTS: An unsteady Bernoulli equation accurately predicted measured instantaneous AP values (R = 0.97+/-0.06), and a quadratic correlation was observed between instantaneously fitted and Gorlin-derived AVA. Additionally, deltaP < 0 mmHg during late ejection was observed in the majority of AS datasets, with a normalized time to deltaP reversal of 93+/-13% for AS animals versus 69+/-36% for controls (p <0.0005). Time to deltaP reversal inversely correlated with the Strouhal number (R = -0.77), and was responsible for an overestimation of mean systolic transvalvular deltaP and Q that resulted in a significant bias in the Gorlin method. Error was highest in moderate stenosis with low transvalvular output. CONCLUSION: Unsteady fluid-dynamics supports AVA over other measures of AS such as aortic valve resistance. However importantly, late-ejection reversal of deltaP precludes estimating the systolic ejection period from pressure tracings, and accounts for an additional source of error when AS is quantified invasively.
Authors: Ana González-Mansilla; Pablo Martinez-Legazpi; Andrea Prieto; Elena Gomá; Pilar Haurigot; Candelas Pérez Del Villar; Victor Cuadrado; Antonia Delgado-Montero; Raquel Prieto; Teresa Mombiela; Esther Pérez-David; Elena Rodríguez González; Yolanda Benito; Raquel Yotti; Manuel Pérez-Vallina; Francisco Fernández-Avilés; Javier Bermejo Journal: Heart Date: 2019-02-16 Impact factor: 5.994