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Louis-Gilles Durand

Publications and source records attributed to Louis-Gilles Durand.

15 recordsLinked to original sources

Respective impacts of aortic stenosis and systemic hypertension on left ventricular hypertrophy.

It has been reported that 30-40% of patients with aortic stenosis are hypertensive. In such patients, the left ventricle faces a double (i.e. valvular and vascular) pressure overload, which results in subsequent wall volume hypertrophy. From a clinical standpoint, it is difficult to separate the respective contributions of aortic stenosis and systemic hypertension to left ventricular burden and patient's symptoms and thus to predict whether valve replacement would be beneficial. The objective of this theoretical study was therefore to investigate the relative effects of valvular and vascular afterloads on left ventricular hypertrophy. We used a ventricular-valvular-vascular mathematical model in combination with the Arts' model describing the myofiber stress. Left ventricular wall volume was computed for different aortic blood pressure levels and different degrees of aortic stenosis severity. Our simulations show that the presence of concomitant systemic hypertension has a major influence on the development of left ventricular hypertrophy in patients with aortic stenosis. These results also suggest that mild-to-moderate aortic stenosis has a minor impact on left ventricular wall volume when compared with hypertension. On the other hand, when aortic stenosis is severe, wall volume increases exponentially with increasing aortic stenosis severity and the impact of aortic stenosis on left ventricular hypertrophy becomes highly significant.

Aortic Valve Stenosis↗

Influence of multiple stenoses on echo-Doppler functional diagnosis of peripheral arterial disease: a numerical and experimental study.

The objective of this paper was to evaluate the ability of the peak systolic velocity ratio (PSVR) and pressure drop (DeltaP) to detect and grade multiple stenoses in lower limb mimicking arteries. Numerical simulations and experiments in vascular phantoms allowing ultrasound duplex scanning and pressure measurements were used to investigate simple and double stenotic arterial segments. Inter-stenotic distance, severity of the distal stenosis, flow rate and flow profile (steady or pulsatile) were the tested parameters. The three-dimensional simulations considered the turbulent two-equation Wilcox model. Agreements were observed between the experimental and numerical results for DeltaP and PSVR. The maximum PSVR along the artery was shown to be mainly influenced by the severity of the most important stenosis. However, mutual interactions of both stenoses on hemodynamics were noted. By using the clinical PSVR threshold used to diagnose critical lesions (PSVR > or = 2), its longitudinal evolution along the artery poorly reflected the length of the lesion or the impact of surrounding stenoses. This investigation confirms the interaction between adjacent stenoses on hemodynamics and its impact on the Doppler ultrasound index PSVR.

Animals↗

Projected valve area at normal flow rate improves the assessment of stenosis severity in patients with low-flow, low-gradient aortic stenosis: the multicenter TOPAS (Truly or Pseudo-Severe Aortic Stenosis) study.

BACKGROUND: We sought to investigate the use of a new parameter, the projected effective orifice area (EOAproj) at normal transvalvular flow rate (250 mL/s), to better differentiate between truly severe (TS) and pseudo-severe (PS) aortic stenosis (AS) during dobutamine stress echocardiography (DSE). Changes in various parameters of stenosis severity have been used to differentiate between TS and PS AS during DSE. However, the magnitude of these changes lacks standardization because they are dependent on the variable magnitude of the transvalvular flow change occurring during DSE. METHODS AND RESULTS: The use of EOAproj to differentiate TS from PS AS was investigated in an in vitro model and in 23 patients with low-flow AS (indexed EOA <0.6 cm2/m2, left ventricular ejection fraction < or =40%) undergoing DSE and subsequent aortic valve replacement. For an individual valve, EOA was plotted against transvalvular flow (Q) at each dobutamine stage, and valve compliance (VC) was derived as the slope of the regression line fitted to the EOA versus Q plot; EOAproj was calculated as EOAproj=EOArest+VCx(250-Q(rest)), where EOArest and Q(rest) are the EOA and Q at rest. Classification between TS and PS was based on either response to flow increase (in vitro) or visual inspection at surgery (in vivo). EOAproj was the most accurate parameter in differentiating between TS and PS both in vitro and in vivo. In vivo, 15 of 23 patients (65%) had TS and 8 of 23 (35%) had PS. The percentage of correct classification was 83% for EOAproj and 91% for indexed EOAproj compared with percentages of 61% to 74% for the other echocardiographic parameters usually used for this purpose. CONCLUSIONS: EOAproj provides a standardized evaluation of AS severity with DSE and improves the diagnostic accuracy for distinguishing TS and PS AS in patients with low-flow, low-gradient AS.

Aged↗

Value and limitations of peak-to-peak gradient for evaluation of aortic stenosis.

BACKGROUND AND AIM OF THE STUDY: In patients with aortic stenosis (AS), it has been reported that the transvalvular pressure gradients (APs) may be reduced or even abolished in the presence of concomitant arterial hypertension, but the mechanisms underlying this phenomenon remain unclear. The study aim was to: (i) examine the relationship between systemic arterial hemodynamics and the peak-to-peak (deltaP(PtoP)), peak deltaP and mean deltaP; and (ii) propose and validate a new formula for the non-invasive estimation of the deltaP(PtoP) and of the peak left ventricular systolic pressure (LVSP) using Doppler echocardiography. METHODS: Two fixed stenoses (geometric orifice area 1.0 and 1.35 cm2) and one bioprosthesis (effective orifice area (EOA) 1.2 cm2) were tested in a mock flow circulation model. Systemic vascular resistance (R) was increased from 1,500 to 3,300 dyne.s/cm5, and systemic arterial compliance (C) was decreased from 2.9 to 0.9 ml/mmHg, while transvalvular flow was held constant. RESULTS: Neither C nor R had any significant impact on EOA, peak deltaP and mean deltaP. deltaP(PtoP) was decreased markedly, however, when C was reduced (bioprosthesis: -15 mmHg (-69%); orifice 1.35 cm2: -24 mmHg (-30%); cm2: (-13%)). Subsequently, an equation was proposed to predict deltaP(PtoP) from EOA, mean deltaP, and C measured by Doppler echocardiography. LVSP calculated by adding the predicted deltaP(Ptop) to systolic arterial pressure (SAP) was compared with LVSP measured directly in a dataset of 24 pigs with experimentally induced AS. There was a strong agreement between the estimated and measured LVSP (r = 0.97; mean absolute error 5 +/- 5 mmHg). CONCLUSION: deltaP(Ptop) should not be used to evaluate AS severity because, as opposed to peak and mean deltaPs, it is highly influenced by C. The new non-invasive method proposed in this study to estimate the LVSP may be useful for obtaining a more accurate estimate of global LV afterload in patients with AS.

Animals↗

Flow-dependent changes in Doppler-derived aortic valve effective orifice area are real and not due to artifact.

OBJECTIVES: We sought to determine whether the flow-dependent changes in Doppler-derived valve effective orifice area (EOA) are real or due to artifact. BACKGROUND: It has frequently been reported that the EOA may vary with transvalvular flow in patients with aortic stenosis. However, the explanation of the flow dependence of EOA remains controversial and some studies have suggested that the EOA estimated by Doppler-echocardiography (EOA(Dop)) may underestimate the actual EOA at low flow rates. METHODS: One bioprosthetic valve and three rigid orifices were tested in a mock flow circulation model over a wide range of flow rates. The EOA(Dop) was compared with reference values obtained using particle image velocimetry (EOA(PIV)). RESULTS: There was excellent agreement between EOA(Dop) and EOA(PIV) (r2 = 0.94). For rigid orifices of 0.5 and 1.0 cm2, no significant change in the EOA was observed with increasing flow rate. However, substantial increases of both EOA(Dop) and EOA(PIV) were observed when stroke volume increased from 20 to 70 ml both in the 1.5 cm2 rigid orifice (+52% for EOA(Dop) and +54% for EOA(PIV)) and the bioprosthetic valve (+62% for EOA(Dop) and +63% for EOA(PIV)); such changes are explained either by the presence of unsteady effects at low flow rates and/or by an increase in valve leaflet opening. CONCLUSIONS: The flow-dependent changes in EOA(Dop) are not artifacts but represent real changes in EOA attributable either to unsteady effects at low flow rates and/or to changes in valve leaflet opening. Such changes in EOA(Dop) can be relied on for clinical judgment making.

Aortic Valve↗

Analytical modeling of the instantaneous maximal transvalvular pressure gradient in aortic stenosis.

In presence of aortic stenosis, a jet is produced downstream of the aortic valve annulus during systole. The vena contracta corresponds to the location where the cross-sectional area of the flow jet is minimal. The maximal transvalvular pressure gradient (TPG(max)) is the difference between the static pressure in the left ventricle and that in the vena contracta. TPG(max) is highly time-dependent over systole and is known to depend upon the transvalvular flow rate, the effective orifice area (EOA) of the aortic valve and the cross-sectional area of the left ventricular outflow tract. However, it is still unclear how these parameters modify the TPG(max) waveform. We thus derived an explicit analytical model to describe the instantaneous TPG(max) across the aortic valve during systole. This theoretical model was validated with in vivo experiments obtained in 19 pigs with supravalvular aortic stenosis. Instantaneous TPG(max) was measured by catheter and its waveform was compared with the one determined from the derived equation. Our results showed a very good concordance between the measured and predicted instantaneous TPG(max). Total relative error and mean absolute error were on average 9.4+/-4.9% and 2.1+/-1.1 mmHg, respectively. The analytical model proposed and validated in this study provides new insight into the behaviour of the TPG(max) and thus of the aortic pressure at the level of vena contracta. Because the static pressure at the coronary inlet is similar to that at the vena contracta, the proposed equation will permit to further examine the impact of aortic stenosis on coronary blood flow.

Aortic Valve↗

Analytical modeling of the instantaneous pressure gradient across the aortic valve.

Aortic stenosis is the most frequent valvular heart disease. The mean systolic value of the transvalvular pressure gradient (TPG) is commonly utilized during clinical examination to evaluate its severity and it can be determined either by cardiac catheterization or by Doppler echocardiography. TPG is highly time-dependent over systole and is known to depend upon the transvalvular flow rate, the effective orifice area (EOA) of the aortic valve and the cross-sectional area of the ascending aorta. However it is still unclear how these parameters modify the TPG waveform. We thus derived a simple analytical model from the energy loss concept to describe the instantaneous TPG across the aortic valve during systole. This theoretical model was validated with orifice plates and bioprosthetic heart valves in an in vitro aortic flow model. Instantaneous TPG was measured by catheter and its waveform was compared with the one determined from the transvalvular flow rate, the valvular EOA and the aortic cross-sectional area, using the derived equation. Our results showed a very good concordance between the measured and predicted instantaneous TPG. The analytical model proposed and validated in this study provides a comprehensive description of the aortic valve hemodynamics that can be used to accurately predict the instantaneous transvalvular pressure gradient in native and bioprosthetic aortic valves. The consideration of this model suggests that: (1) TPG waveform is exclusively dependent upon transvalvular flow rate and flow geometry, (2) the frequently applied simplified Bernoulli equation may overestimate mean TPG by more than 30% and (3) the measurement of ejection time by cardiac catheterization may underestimate the actual ejection time, especially in patients with mild/moderate aortic stenosis and low cardiac output.

Animals↗

A ventricular-vascular coupling model in presence of aortic stenosis.

In patients with aortic stenosis, the left ventricular afterload is determined by the degree of valvular obstruction and the systemic arterial system. We developed an explicit mathematical model formulated with a limited number of independent parameters that describes the interaction among the left ventricle, an aortic stenosis, and the arterial system. This ventricular-valvular-vascular (V(3)) model consists of the combination of the time-varying elastance model for the left ventricle, the instantaneous transvalvular pressure-flow relationship for the aortic valve, and the three-element windkessel representation of the vascular system. The objective of this study was to validate the V(3) model by using pressure-volume loop data obtained in six patients with severe aortic stenosis before and after aortic valve replacement. There was very good agreement between the estimated and the measured left ventricular and aortic pressure waveforms. The total relative error between estimated and measured pressures was on average (standard deviation) 7.5% (SD 2.3) and the equation of the corresponding regression line was y = 0.99x - 2.36 with a coefficient of determination r(2) = 0.98. There was also very good agreement between estimated and measured stroke volumes (y = 1.03x + 2.2, r(2) = 0.96, SEE = 2.8 ml). Hence, this mathematical V(3) model can be used to describe the hemodynamic interaction among the left ventricle, the aortic valve, and the systemic arterial system.

Aortic Valve Stenosis↗

Estimation of aortic valve effective orifice area by Doppler echocardiography: effects of valve inflow shape and flow rate.

BACKGROUND: The effective orifice area (EOA) is the standard parameter for the clinical assessment of aortic stenosis severity. It has been reported that EOA measured by Doppler echocardiography does not necessarily provide an accurate estimate of the cross-sectional area of the flow jet at the vena contracta, especially at low flow rates. The objective of this study was to test the validity of the Doppler-derived EOA. METHODS: Triangular and circular orifice plates, funnels, and bioprosthetic valves were inserted into an in vitro aortic flow model and were studied under different physiologic flow rates corresponding to cardiac outputs varying from 1.5 to 7 L/min. For each experiment, the EOA was measured by Doppler and compared with the catheter-derived EOA and with the EOA derived from a theoretic formula. In bioprostheses, the geometric orifice area (GOA) was estimated from images acquired by high-speed video recording. RESULTS: There was no significant difference between the EOA derived from the 3 methods with the rigid orifices (Doppler vs catheter: y = 0.97x +0.18 mm(2), r(2) = 0.98; Doppler vs theory: y = 1.00x -3.60 mm(2), r(2) = 0.99). Doppler EOA was not significantly influenced by the flow rate in rigid orifices. As predicted by theory, the average contraction coefficient (EOA/GOA) was around 0.6 in the orifice plates and around 1.0 in the funnels. In the bioprosthetic valves, both EOA and GOA increased with increasing flow rate whereas contraction coefficient was almost constant with an average value of 0.99. There was also a very good concordance between EOA and GOA (y = 0.94x +0.05 mm(2), r(2) = 0.88). CONCLUSIONS: In rigid aortic stenosis, the Doppler EOA is much less flow dependent than generally assumed. Indeed, it depends mainly on the GOA and the inflow shape (flat vs funnel-shaped) of the stenosis. The flow dependence of Doppler EOA observed in clinical studies is likely a result of a variation of the valve GOA or of the valve inflow shape and not an inherent flow dependence of the EOA derived by the continuity equation.

Aortic Valve↗

A multimodality vascular imaging phantom with fiducial markers visible in DSA, CTA, MRA, and ultrasound.

The objective was to design a vascular phantom compatible with digital subtraction angiography, computerized tomography angiography, ultrasound and magnetic resonance angiography (MRA). Fiducial markers were implanted at precise known locations in the phantom to facilitate identification and orientation of plane views from three-dimensional (3-D) reconstructed images. A vascular conduit connected to tubing at the extremities of the phantom ran through an agar-based gel filling it. A vessel wall in latex was included around the conduit to avoid diffusion of contrast agents. Using a lost-material casting technique based on a low melting point metal, geometries of pathological vessels were modeled. During the experimental testing, fiducial markers were detectable in all modalities without distortion. No leak of gadolinium through the vascular wall was observed on MRA after 5 hours. Moreover, no significant deformation of the vascular conduit was noted during the fabrication process (confirmed by microtome slicing along the vessel). The potential use of the phantom for calibration, rescaling, and fusion of 3-D images obtained from the different modalities as well as its use for the evaluation of intra- and inter-modality comparative studies of imaging systems are discussed. In conclusion, the vascular phantom can allow accurate calibration of radiological imaging devices based on x-ray, magnetic resonance and ultrasound and quantitative comparisons of the geometric accuracy of the vessel lumen obtained with each of these methods on a given well defined 3-D geometry.

Agar↗

Non-Gaussian statistics and temporal variations of the ultrasound signal backscattered by blood at frequencies between 10 and 58 MHz.

Very little is known about the blood backscattering behavior and signal statistics following flow stoppage at frequencies higher than 10 MHz. Measurements of the radio frequency (rf) signals backscattered by normal human blood (hematocrit = 40%, temperature = 37 degrees C) were performed in a tube flow model at mean frequencies varying between 10 and 58 MHz. The range of increase of the backscattered power during red blood cell (RBC) rouleau formation was close to 15 dB at 10 and 36 MHz, and dropped, for the same blood samples, below 8 dB at 58 MHz. Increasing the frequency from 10 to 58 MHz raised the slope of the power changes at the beginning of the kinetics of aggregation, and could emphasize the non-Gaussian behavior of the rf signals interpreted in terms of the K and Nakagami statistical models. At 36 and 58 MHz, significant increases of the kurtosis coefficient, and significant reductions of the Nakagami parameter were noted during the first 30 s of flow stoppage. In conclusion, increasing the transducer frequency reduced the magnitude of the backscattered power changes attributed to the phenomenon of RBC aggregation, but improved the detection of rapid growth in aggregate sizes and non-Gaussian statistical behavior.

Acoustics↗

Discrepancies between catheter and Doppler estimates of valve effective orifice area can be predicted from the pressure recovery phenomenon: practical implications with regard to quantification of aortic stenosis severity.

OBJECTIVES: We sought to obtain more coherent evaluations of aortic stenosis severity. BACKGROUND: The valve effective orifice area (EOA) is routinely used to assess aortic stenosis severity. However, there are often discrepancies between measurements of EOA by Doppler echocardiography (EOA(Dop)) and those by a catheter (EOA(cath)). We hypothesized that these discrepancies might be due to the influence of pressure recovery. METHODS: The relationship between EOA(cath) and EOA(Dop) was studied as follows: 1) in an in vitro model measuring the effects of different flow rates and aortic diameters on two fixed stenoses and seven bioprostheses; 2) in an animal model of supravalvular aortic stenosis (14 pigs); and 3) based on catheterization data from 37 patients studied by Schöbel et al. RESULTS: Pooling of in vitro, animal, and patient data showed a good correlation (r = 0.97) between EOA(cath) (range 0.3 to 2.3 cm(2)) and EOA(Dop) (range 0.2 to 1.7 cm(2)), but EOA(cath) systematically overestimated EOA(Dop) (24 +/- 17% [mean +/- SD]). However, when the energy loss coefficient (ELCo) was calculated from EOA(Dop) and aortic cross-sectional area (A(A)) to account for pressure recovery, a similar correlation (r = 0.97) with EOA(cath) was observed, but the previously noted overestimation was no longer present. CONCLUSIONS: Discrepancies between EOA(cath) and EOA(Dop) are largely due to the pressure recovery phenomenon and can be reconciled by calculating ELCo from the echocardiogram. Thus, ELCo and EOA(cath) are equivalent indexes representing the net energy loss due to stenosis and probably are the most appropriate for quantifying aortic stenosis severity.

Animals↗

A new clutter rejection algorithm for Doppler ultrasound.

Several strategies, known as clutter or wall Doppler filtering, were proposed to remove the strong echoes produced by stationary or slow moving tissue structures from the Doppler blood flow signal. In this study, the matching pursuit (MP) method is proposed to remove clutter components. The MP method decomposes the Doppler signal into wavelet atoms that are selected in a decreasing energy order. Thus, the high-energy clutter components are extracted first. In the present study, the pulsatile Doppler signal s(n) was simulated by a sum of random-phase sinusoids. Two types of high-amplitude clutter signals were then superimposed on s(n): time-varying low-frequency components, covering systole and early diastole, and short transient clutter signals, distributed within the whole cardiac cycle. The Doppler signals were modeled with the MP method and the most dominant atoms were subtracted from the time-domain signal s(n) until the signal-to-clutter (S/C) ratio reached a maximum. For the low-frequency clutter signal, the improvement in S/C ratio was 19.0 +/- 0.6 dB, and 72.0 +/- 4.5 atoms were required to reach this performance. For the transient clutter signal, ten atoms were required and the maximum improvement in S/C ratio was 5.5 +/- 0.5 dB. The performance of the MP method was also tested on real data recorded over the common carotid artery of a normal subject. Removing 15 atoms significantly improved the appearance of the Doppler sonogram contaminated with low-frequency clutter. Many more atoms (over 200) were required to remove transient clutter components. These results suggest the possibility of using this signal processing approach to implement clutter rejection filters on ultrasound commercial instruments.

Algorithms↗

Phonospirometry for noninvasive measurement of ventilation: methodology and preliminary results.

We measured tracheal flow from tracheal sounds to estimate tidal volume, minute ventilation (VI), respiratory frequency, mean inspiratory flow (VT/TI), and duty cycle (TI/Ttot). In 11 normal subjects, 3 patients with unstable airway obstruction, and 3 stable asthmatic patients, we measured tracheal sounds and flow twice: first to derive flow-sound relationships and second to obtain flow-volume relationships from the sound signal. The flow-volume relationship was compared with pneumotach-derived volume. When subjects were seated, facing forward and with neck rotation, flexion, and standing, flow-volume relationship was within 15% of pneumotach-derived volume. Error increased with neck extension and while supine. We then measured ventilation without mouthpiece or nose clip from tracheal sounds during quiet breathing for up to 30 min. Normal results +/- SD revealed tidal volume = 0.37 +/- 0.065 liter, respiratory frequency = 19.3 +/- 3.5 breaths/min, VI = 6.9 +/- 1.2 l/min, VT/TI = 0.31 +/- 0.06 l/s, and TI/Ttot = 0.37 +/- 0.04. Unstable airway obstruction had large VI due to increased VT/TI. With the exception of TI/Ttot, variations in ventilatory parameters were closer to log normal than normal distributions and tended to be greater in patients. We conclude that phonospirometry measures ventilation reasonably accurately without mouthpiece, nose clip, or rigid postural constraints.

Airway Obstruction↗

Independent contribution of left ventricular ejection time to the mean gradient in aortic stenosis.

BACKGROUND AND AIMS OF THE STUDY: Transvalvular mean pressure gradients (MPG) are important in the evaluation of aortic stenosis, but surprisingly they often differ in patients having similar valve effective orifice area (EOA) and stroke volume (SV). The study aim was to determine if these differences could be explained by variations in left ventricular ejection time (LVET). METHODS: A pulse duplicator system with a constant SV of 75 ml and incremental increases of LVET from 250 to 450 ms was used to measure MPG by Doppler echocardiography in three fixed stenoses (0.5, 1.0 and 1.5 cm2). The same variables were also measured at rest in 192 patients with isolated aortic stenosis (EOA <1.5 cm2) as well as during stress in a subgroup of 24 patients. RESULTS: In vitro, the increase in LVET produced marked decreases of MPG ranging from -40 mmHg (-45%) for the 0.5-cm2 stenosis to -22 mmHg (-61%) for the 1.5-cm2 stenosis. In vivo, MPG measured by Doppler correlated strongly (R2 = 0.83) with the MPG predicted by the formula: MPGpred [SV/(50xEOAxLVET)]2, and on this basis the relative contributions of EOA, SV and LVET to the variance of MPG were found to be 36, 34 and 13%, respectively. During stress, the contribution of LVET to the increase in MPG was variable, but was sometimes as important as that of SV. CONCLUSION: LVET may significantly and independently influence MPG in aortic stenosis. Clinically, variations of up to 15 mmHg in MPG may be observed uniquely on the basis of a change in duration of LVET, and hence the MPG cannot be used as a stand-alone parameter for serial evaluations or for comparisons of aortic stenosis severity between patients. A correction of MPG for LVET (in ms) such as MPGc = MPGx(LVET/300)2 might be helpful for rendering comparisons of MPG more meaningful in patients with aortic stenosis.

Adolescent↗