Modeling of Diastole

Kovács, Sándor J.; Meisner, J.; Yellin, Edward L.

doi:10.1016/s0733-8651(05)70156-9

Cited by 60 publications

(65 citation statements)

References 38 publications

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“…Additional PDF-derived indexes denote the stored elastic strain energy driving ventricular suction (1/2kx o 2 ) and the peak atrioventricular pressure gradient (kx o ) (Kovács et al 1987). PDF parameter values for x o , c, and k were determined using the Levenberg-Marquardt algorithm fit (Press et al 1992) to the maximum velocity envelope via a custom LabVIEW (National Instruments, Austin, TX) interface (Chung et al 2006,Dent et al 2001,Hall et al 1994a,Kovács et al 2000,Riordan et al 2005.…”

Section: Kinematic Modeling Of Fillingmentioning

confidence: 99%

“…Analysis of transmitral flow contours (Doppler E-waves) via the PDF formalism (Hall et al 1994a,Hall et al 1994b,Hall et al 1998,Kovács et al 1987,Kovács et al 2000,Lakshminarayan et al 1993 has shown that diabetes alters the relaxation parameter c of early rapid filling in both rats (Dent et al 2001) and humans (Riordan et al 2005). Importantly, these two studies showed that for hearts with normal LVEF, conventional E-wave indexes such as peak E-wave velocity (E peak ) or deceleration time (DT) were unable to differentiate between normal and diabetic filling patterns, whereas the relaxation/viscosity parameter c differentiated between normal (lower c) and diabetic subjects (higher c).…”

Section: Introductionmentioning

confidence: 99%

“…The initial displacement of the oscillator x o (cm) is linearly related to the E-wave VTI (i.e. related to volumetric preload) (Kovács et al 2000). Chamber stiffness (dP/dV) is linearly related to the SHO spring constant k (g/s 2 ) (Kovács et al 1997), while the oscillator's damping constant or chamber viscoelasticity/relaxation index c (g/s) characterizes the resistance (relaxation/ viscosity) of the filling process (Kovács et al 2000).…”

Section: Introductionmentioning

confidence: 99%

“…related to volumetric preload) (Kovács et al 2000). Chamber stiffness (dP/dV) is linearly related to the SHO spring constant k (g/s 2 ) (Kovács et al 1997), while the oscillator's damping constant or chamber viscoelasticity/relaxation index c (g/s) characterizes the resistance (relaxation/ viscosity) of the filling process (Kovács et al 2000). Because the formalism is kinematic and is species independent, it provides a novel, volume-based physiologic paradigm by which the efficiency of filling can be modeled and assessed.…”

Section: Introductionmentioning

confidence: 99%

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The Kinematic Filling Efficiency Index of the Left Ventricle: Contrasting Normal vs. Diabetic Physiology

Zhang

Chung

Riordan

et al. 2007

Ultrasound in Medicine & Biology

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An index of filling efficiency incorporating stiffness and relaxation (S&R) parameters has not been derived or validated although numerous studies have focused on the effects of altered relaxation or stiffness on early rapid filling and diastolic function. Previous studies show that S&R parameters can be obtained from early rapid filling (Doppler E-wave) via kinematic modeling. E-wave contours are governed by harmonic oscillatory motion, modeled via the parameterized diastolic filling (PDF) formalism. The previously validated model determines three (unique) oscillator parameters from each E-wave having established physiologic analogues: x o (load), c (relaxation/viscoelasticity), and k (chamber stiffness). We define the dimensionless, filling-volume based kinematic filling efficiency index (KFEI) as the ratio of the velocity-time integral (VTI) of the actual clinical E-wave contour fit via PDF to the VTI of the PDF model-predicted ideal E-wave contour having the same x o and k, but with no resistance to filling (c=0). To validate the new index, Doppler E-waves from 36 subjects with normal ventricular function, 17 diabetic and 19 well-matched non-diabetic controls, were analyzed. E-wave parameters x o , c, and k and KFEI were computed for each subject and compared. In concordance with prior human and animal studies in which c differentiated between normal and diabetic hearts, KFEI differentiated (p<0.001) between non-diabetics (55.8±3.3%) and diabetics (49.1±3.3%). Thus, the new index introduces and validates the concept of filling efficiency, and using diabetes as a working example, provides quantitative and mechanistic insight into how S&R affects ventricular filling efficiency.

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Section: Kinematic Modeling Of Fillingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Kinematic Filling Efficiency Index of the Left Ventricle: Contrasting Normal vs. Diabetic Physiology

Zhang

Chung

Riordan

et al. 2007

Ultrasound in Medicine & Biology

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“…Measurement of DF during early filling is achieved by solving the "inverse problem of diastole" that uniquely determines chamber properties from E-waves via the PDF formalism (56,76). The conceptual framework reframes pressure decline during IVR as the result of elastic recoil forces being "unmasked" by relaxation.…”

Section: How To Measure Dfmentioning

confidence: 99%

What global diastolic function is, what it is not, and how to measure it

Chung

Shmuylovich

Kovács

2015

American Journal of Physiology-Heart and Circulatory Physiology

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Leonardo da Vinci's observation (circa 1511) that "the atria or filling chambers contract together while the pumping chambers or ventricles are relaxing and vice versa," the dynamics of four-chamber heart function, and of diastolic function (DF) in particular, are not generally appreciated. We view DF from a global perspective, while characterizing it in terms of causality and clinical relevance. Our models derive from the insight that global DF is ultimately a result of forces generated by elastic recoil, modulated by cross-bridge relaxation, and load. The interaction between recoil and relaxation results in physical wall motion that generates pressure gradients that drive fluid flow, while epicardial wall motion is constrained by the pericardial sac. Traditional DF indexes (, E/E=, etc.) are not derived from causal mechanisms and are interpreted as approximating either stiffness or relaxation, but not both, thereby limiting the accuracy of DF quantification. Our derived kinematic models of isovolumic relaxation and suction-initiated filling are extensively validated, quantify the balance between stiffness and relaxation, and provide novel mechanistic physiological insight. For example, causality-based modeling provides load-independent indexes of DF and reveals that both stiffness and relaxation modify traditional DF indexes. The method has revealed that the in vivo left ventricular equilibrium volume occurs at diastasis, predicted novel relationships between filling and wall motion, and quantified causal relationships between ventricular and atrial function. In summary, by using governing physiological principles as a guide, we define what global DF is, what it is not, and how to measure it. diastolic function; echocardiography; hemodynamics; mathematical modeling; suction pump LEFT VENTRICULAR (LV) DIASTOLIC dysfunction is typically reported and indexed as either an increase in myocardial stiffness or a slowing of relaxation (i.e., cross-bridge dissociation). In actuality, diastolic function (DF) is the result of the continuous interaction between the restoring force of elastic recoil and the opposing force generated by cross bridges that have yet to uncouple from the previous systole. The restoring forces seek to lengthen the muscle, while the cross-bridge forces previously acted to shorten the muscle. The simultaneous action of these two opposing forces during both isovolumic relaxation (IVR) and filling result in wall motion, constrained by pericardial sac volume, and simultaneous generation of pressure gradients. This review discusses the governing physical laws and the constraints of DF, as well as which indexes of DF are consistent with diastolic physiology. Deriving and evaluating indexes of DF using this conceptual framework both clarifies and advances our understanding of DF and diastolic dysfunction in health and disease. Physiology of DiastoleCardiovascular physiology is taught using the Wiggers diagram, which segments the cardiac cycle into systole and diastole ( Fig. 1) (49, 124). Systole begins...

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The vortex formation time to diastolic function relation: assessment of pseudonormalized versus normal filling

Ghosh

Kovács

2013

Physiol Rep

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In early diastole, the suction pump feature of the left ventricle opens the mitral valve and aspirates atrial blood. The ventricle fills via a blunt profiled cylindrical jet of blood that forms an asymmetric toroidal vortex ring inside the ventricle whose growth has been quantified by the standard (dimensionless) expression for vortex formation time, VFTstandard = {transmitral velocity time integral}/{mitral orifice diameter}. It can differentiate between hearts having distinguishable early transmitral (Doppler E-wave) filling patterns. An alternative validated expression, VFTkinematic reexpresses VFTstandard by incorporating left heart, near “constant-volume pump” physiology thereby revealing VFTkinematic's explicit dependence on maximum rate of longitudinal chamber expansion (E′). In this work, we show that VFTkinematic can differentiate between hearts having indistinguishable E-wave patterns, such as pseudonormal (PN; 0.75 < E/A < 1.5 and E/E′ > 8) versus normal. Thirteen age-matched normal and 12 PN data sets (738 total cardiac cycles), all having normal LVEF, were selected from our Cardiovascular Biophysics Laboratory database. Doppler E-, lateral annular E′-waves, and M-mode data (mitral leaflet separation, chamber dimension) was used to compute VFTstandard and VFTkinematic. VFTstandard did not differentiate between groups (normal [3.58 ± 1.06] vs. PN [4.18 ± 0.79], P = 0.13). In comparison, VFTkinematic for normal (3.15 ± 1.28) versus PN (4.75 ± 1.35) yielded P = 0.006. Hence, the applicability of VFTkinematic for diastolic function quantitation has been broadened to include analysis of PN filling patterns in age-matched groups.

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Modeling of Diastole

Cited by 60 publications

References 38 publications

The Kinematic Filling Efficiency Index of the Left Ventricle: Contrasting Normal vs. Diabetic Physiology

The Kinematic Filling Efficiency Index of the Left Ventricle: Contrasting Normal vs. Diabetic Physiology

What global diastolic function is, what it is not, and how to measure it

The vortex formation time to diastolic function relation: assessment of pseudonormalized versus normal filling

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