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A database of virtual healthy subjects to assess the accuracy of foot-to-foot pulse wave velocities for estimation of aortic stiffness.

Willemet M, Chowienczyk P, Alastruey J - Am. J. Physiol. Heart Circ. Physiol. (2015)

Bottom Line: Our numerical results confirm clinical observations: 1) carotid-femoral PWV is a good indicator of aortic stiffness and correlates well with aortic PWV; 2) brachial-ankle PWV overestimates aortic PWV and is related to the stiffness and geometry of both elastic and muscular arteries; and 3) muscular PWV (carotid-radial, femoral-ankle) does not capture the stiffening of the aorta and should therefore not be used as a surrogate for aortic stiffness.In addition, our analysis highlights that the foot-to-foot PWV algorithm is sensitive to the presence of reflected waves in late diastole, which introduce errors in the PWV estimates.In this study, we have created a database of virtual healthy subjects, which can be used to assess theoretically the efficiency of physiological indexes based on pulse wave analysis.

View Article: PubMed Central - PubMed

Affiliation: Division of Imaging Sciences and Biomedical Engineering, St. Thomas' Hospital, King's College London, London, United Kingdom; and marie.willemet@gmail.com.

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Our study consists of 2 parts: the development of a new methodology (i.e., the creation of a virtual population) and its clinical application [i.e., the assessment of foot-to-foot pulse wave velocity (PWV)]. By varying the cardiac and arterial parameters of the 1-dimensional (1D) model within healthy ranges, we create a set of 7,776 simulations. Rejection criteria (filter #1) are applied to eliminate nonphysiological data. Using the remaining 3,325 cases, we compute the physiological index of interest (i.e., foot-to-foot PWV) and reject 5 cases for which the PWV algorithm fails (filter #2). Peripheral and central PWV indexes are computed for each of the 3,320 cases using pressure waves measured at the dots in the Numerical model box. We also compute an index of local sensitivity analysis Īi,k that describes the effect of parameters variation on PWV values.
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Figure 1: Our study consists of 2 parts: the development of a new methodology (i.e., the creation of a virtual population) and its clinical application [i.e., the assessment of foot-to-foot pulse wave velocity (PWV)]. By varying the cardiac and arterial parameters of the 1-dimensional (1D) model within healthy ranges, we create a set of 7,776 simulations. Rejection criteria (filter #1) are applied to eliminate nonphysiological data. Using the remaining 3,325 cases, we compute the physiological index of interest (i.e., foot-to-foot PWV) and reject 5 cases for which the PWV algorithm fails (filter #2). Peripheral and central PWV indexes are computed for each of the 3,320 cases using pressure waves measured at the dots in the Numerical model box. We also compute an index of local sensitivity analysis Īi,k that describes the effect of parameters variation on PWV values.

Mentions: The methodology followed in this work is summarized in Fig. 1.


A database of virtual healthy subjects to assess the accuracy of foot-to-foot pulse wave velocities for estimation of aortic stiffness.

Willemet M, Chowienczyk P, Alastruey J - Am. J. Physiol. Heart Circ. Physiol. (2015)

Our study consists of 2 parts: the development of a new methodology (i.e., the creation of a virtual population) and its clinical application [i.e., the assessment of foot-to-foot pulse wave velocity (PWV)]. By varying the cardiac and arterial parameters of the 1-dimensional (1D) model within healthy ranges, we create a set of 7,776 simulations. Rejection criteria (filter #1) are applied to eliminate nonphysiological data. Using the remaining 3,325 cases, we compute the physiological index of interest (i.e., foot-to-foot PWV) and reject 5 cases for which the PWV algorithm fails (filter #2). Peripheral and central PWV indexes are computed for each of the 3,320 cases using pressure waves measured at the dots in the Numerical model box. We also compute an index of local sensitivity analysis Īi,k that describes the effect of parameters variation on PWV values.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4537944&req=5

Figure 1: Our study consists of 2 parts: the development of a new methodology (i.e., the creation of a virtual population) and its clinical application [i.e., the assessment of foot-to-foot pulse wave velocity (PWV)]. By varying the cardiac and arterial parameters of the 1-dimensional (1D) model within healthy ranges, we create a set of 7,776 simulations. Rejection criteria (filter #1) are applied to eliminate nonphysiological data. Using the remaining 3,325 cases, we compute the physiological index of interest (i.e., foot-to-foot PWV) and reject 5 cases for which the PWV algorithm fails (filter #2). Peripheral and central PWV indexes are computed for each of the 3,320 cases using pressure waves measured at the dots in the Numerical model box. We also compute an index of local sensitivity analysis Īi,k that describes the effect of parameters variation on PWV values.
Mentions: The methodology followed in this work is summarized in Fig. 1.

Bottom Line: Our numerical results confirm clinical observations: 1) carotid-femoral PWV is a good indicator of aortic stiffness and correlates well with aortic PWV; 2) brachial-ankle PWV overestimates aortic PWV and is related to the stiffness and geometry of both elastic and muscular arteries; and 3) muscular PWV (carotid-radial, femoral-ankle) does not capture the stiffening of the aorta and should therefore not be used as a surrogate for aortic stiffness.In addition, our analysis highlights that the foot-to-foot PWV algorithm is sensitive to the presence of reflected waves in late diastole, which introduce errors in the PWV estimates.In this study, we have created a database of virtual healthy subjects, which can be used to assess theoretically the efficiency of physiological indexes based on pulse wave analysis.

View Article: PubMed Central - PubMed

Affiliation: Division of Imaging Sciences and Biomedical Engineering, St. Thomas' Hospital, King's College London, London, United Kingdom; and marie.willemet@gmail.com.

Show MeSH
Related in: MedlinePlus