Louis-gilles Durand - Profile on Academia.edu (original) (raw)
Papers by Louis-gilles Durand
Classification of bioprosthetic valve closure sounds by a neural network using linear prediction coefficients
A three layers feed-forward back-propagation neural network was trained to classify bioprosthetic... more A three layers feed-forward back-propagation neural network was trained to classify bioprosthetic valve closure sounds from 47 patients with a porcine bioprosthetic valve inserted in the aortic position. Twenty-four patients had a normal valve and 23 a degenerated one. Twelve linear prediction coefficients computed from the closure sounds were used as the network input The neural network yielded 89% correct classification in an evaluation using the leave-one-out method. This study confirmed the potential of heart sound classification by using a neural network.
Mathematical and Computer Modelling, 1988
[Digital phonocardiography: a non-invasive technic for follow-up of bioprosthetic heart valves]
PubMed, Feb 25, 1988
A system for real-time cardiac acoustic mapping
This paper describes the structure of a real-time cardiac acoustic mapping system (RTCAMS) which ... more This paper describes the structure of a real-time cardiac acoustic mapping system (RTCAMS) which displays the amplitude of the phonocardiogram (PCG) recorded on the surface of the thorax with an acoustic probe composed of an array of 25 microphones. The basic components of the RTCAMS are the acoustic probe, a PCG module, and a digital signal processing (DSP) board installed
Effect of concomitant asymmetric septal hypertrophy when assessing the severity of aortic valve stenosis: an in-vitro study
PubMed, Sep 1, 2012
Background and aim of the study: Aortic valve stenosis (AS) is an important cardiovascular diseas... more Background and aim of the study: Aortic valve stenosis (AS) is an important cardiovascular disease that affects between 2% and 7% of the elderly population in industrialized countries. AS often coexists with asymmetric septal hypertrophy (ASH), which is generally caused by a protrusion of the hypertrophied left ventricular outflow tract (LVOT) just below the aortic valve. The study aim was to determine, based on measurement of the aortic valve effective orifice area (EOA), if ASH might potentially interfere with the assessment of AS severity. Methods: The effects of different levels of ASH (from normal to 90%) on the EOA measured from orifices mimicking different AS severities, and from a home-built AS model constructed from a bioprosthetic aortic valve, were examined in a pulsatile flow in-vitro model. Results: For the most severe AS, the level of ASH had no impact on the measured EOA. In contrast, for the less severe AS, beyond an ASH level of 50% the AS severity was progressively overestimated, and reached a reduction of about 60% of EOA for a ASH level of 90%. Conclusion: The presence of concomitant ASH may cause an overestimation of the hemodynamic severity of AS. The extent of overestimation is more important in less-severe AS. Hence, the presence of ASH may lead the clinician to conclude, erroneously, that the AS is severe and that aortic valve replacement is indicated. However, beyond an ASH level of 50% the AS severity can be accurately determined.
Proceedings of SPIE, Apr 12, 2002
Application of the cone-kernel distribution to study the effect of myocardial contractility in the genesis of the first heart sound in dog
In order to examine the effect of myocardial contractility in the production of the first heart s... more In order to examine the effect of myocardial contractility in the production of the first heart sound (S1), the cone-kernel distribution (CKD) was applied to the thoracic S1 in dogs under various cardiac contractile states. The results showed that the dominant components of S1 are highly concentrated in a specific frequency band between 30 and 50 Hz with a horizontal
Various methodologies have been used to estimate and map percent impervious surface area (%ISA) u... more Various methodologies have been used to estimate and map percent impervious surface area (%ISA) using moderate resolution remote sensing imagery (e.g., Landsat Thematic Mapper). There is, however, a lack of comparative analyses among these methods. This study compares three major spectral analysis techniques (regression modeling, regression tree, and normalized spectral mixture analysis (NSMA)) for continuous %ISA estimation using Landsat imagery for 1986 and 2002 for the seven-county Twin Cities Metropolitan Area of Minnesota. Our study showed that all three techniques demonstrate the capability for estimating %ISA accurately, with RMSE ranging from 7.3 percent to 11 percent and R 2 of 0.90 to 0.96 for both years. Comparatively, regression modeling and regression tree methods produced similar results; however, both of them are highly dependent on accurate masks to differentiate urban impervious surfaces from bare soil. Within the urban mask, the regression tree-based estimates were the most accurate. In terms of time and cost, the NSMA approach is most efficient, but it tends to underestimate the percent imperviousness for highly developed areas. Findings from the study provide guidance for the selection of %ISA estimation techniques using moderate resolution remote sensing data, along with information for further methodological improvements.
Ultrasound in Medicine and Biology, 1991
Amplitude distributions of Doppler spectrograms were characterized in a group of 22 patients havi... more Amplitude distributions of Doppler spectrograms were characterized in a group of 22 patients having no aortic pressure gradient and another group of 26 patients having a stenotic aortic valve. Specifically, for each patient, the ratios of the mean amplitude in three normalized frequency bands (low, middle and high) to the mean amplitude of the Doppler spectrogram computed in selected portions of the systolic period were considered. Pulsed-wave Doppler spectrograms were recorded by positioning the sample volume in the left ventricular outflow tract, approximately 1 cm below the aortic valve. Statistically significant differences were found between the middle (p = 0.041) and high (p = 0.028) frequency bands of Doppler signals recorded from the two groups of patients. The differences observed are believed to be attributed to blood flow eddies generated below the stenotic aortic heart valve and to changes in blood flow orientation.
Optimization of Doppler velocity echocardiographic measurements using an automatic contour detection method
Intra- and inter-observer variability in Doppler velocity echocardiographic measurements (DVEM) i... more Intra- and inter-observer variability in Doppler velocity echocardiographic measurements (DVEM) is a significant issue. Indeed, imprecisions of DVEM can lead to diagnostic errors, particularly in the quantification of the severity of heart valve dysfunction. To minimize the variability and rapidity of DVEM, we have developed an automatic method of Doppler velocity wave contour detection, based on active contour models. To validate our new method, results obtained with this method were compared to those obtained manually by an experienced echocardiographer on Doppler echocardiographic images of left ventricular outflow tract and transvalvular flow velocity signals recorded in 30 patients, 15 with aortic stenosis and 15 with mitral stenosis. We focused on three essential variables that are measured routinely by Doppler echocardiography in the clinical setting: the maximum velocity, the mean velocity and the velocity-time integral. Comparison between the two methods has shown a very good agreement (linear correlation coefficient R(2) = 0.99 between the automatically and the manually extracted variables). Moreover, the computation time was really short, about 5s. This new method applied to DVEM could, therefore, provide a useful tool to eliminate the intra- and inter-observer variabilities associated with DVEM and thereby to improve the diagnosis of cardiovascular disease. This automatic method could also allow the echocardiographer to realize these measurements within a much shorter period of time compared to standard manual tracing method. From a practical point of view, the model developed can be easily implanted in a standard echocardiographic system.
Independent contribution of left ventricular ejection time to the mean gradient in aortic stenosis
PubMed, Sep 1, 2002
Background and aims of the study: Transvalvular mean pressure gradients (MPG) are important in th... more 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.
Experiments in Fluids, Sep 30, 2005
The effective orifice area (EOA) is the most commonly used parameter to assess the severity of ao... more The effective orifice area (EOA) is the most commonly used parameter to assess the severity of aortic valve stenosis as well as the performance of valve substitutes. Particle image velocimetry (PIV) may be used for in vitro estimation of valve EOA. In the present study, we propose a new and simple method based on Howe's developments of Lighthill's aero-acoustic theory. This method is based on an acoustical source term (AST) to estimate the EOA from the transvalvular flow velocity measurements obtained by PIV. The EOAs measured by the AST method downstream of three sharp-edged orifices were in excellent agreement with the EOAs predicted from the potential flow theory used as the reference method in this study. Moreover, the AST method was more accurate than other conventional PIV methods based on streamlines, inflexion point or vorticity to predict the theoretical EOAs. The superiority of the AST method is likely due to the nonlinear form of the AST. There was also an excellent agreement between the EOAs measured by the AST method downstream of the three sharp-edged orifices as well as downstream of a bioprosthetic valve with those obtained by the conventional clinical method based on Doppler-echocardiographic measurements of transvalvular velocity. The results of this study suggest that this new simple PIV method provides an accurate estimation of the aortic valve flow EOA. This new method may thus be used as a reference method to estimate the EOA in experimental investigation of the performance of valve substitutes and to validate Doppler-echocardiographic measurements under various physiologic and pathologic flow conditions.
Ultrasound in Medicine and Biology, 1994
A pattern recognition system was used to classify Doppler blood flow signals for the determinatio... more A pattern recognition system was used to classify Doppler blood flow signals for the determination of lower fimb arterial stenoses. The diagnostic features were extracted from time-frequency representations of Doppler signals. Three techniques were tested to estimate time-frequency representations: the short-time Fourier transform, the autoregressive (AR) modeling, and the Bessel distribution. A boundary tracking algorithm was proposed to extract the frequency contour of the Doppler time-frequency representations. Based on the characteristics of the Doppler frequency contour, shape descriptors from an autoregressive analysis were proposed as diagnostic features. Simple algorithms were proposed to normalize these autoregressive shape descriptors. Amplitude distribution of the Doppler time-frequency representation was also found useful for stenosis classification. A total of 379 arterial segments from the aorta to the popliteal artery were classified by the pattern recognition system into three categories of diameter reduction (0-19%, 20-49%, and 50-99%). The short-time Fourier transform provided an overall accuracy of 80% (kappa = 0.38); AR modeling, 81% (kappa = 0.42); and the Bessel distribution, 82% (kappa = 0.43). All these results are better than those based on visual interpretation (accuracy = 76%, kappa = 0.29) performed by a trained technologist. The AR modeling and the Bessel distribution improved the performance of the pattern recognition system in comparison with the short-time Fourier transform. It is likely that with further improvement, the pattern recognition approach will be a useful clinical tool to quantify stenoses and to follow the disease progression with more reliability and less bias than visual interpretation as done currently in clinical practice.
Journal of Biomechanics, 2006
In presence of aortic stenosis, a jet is produced downstream of the aortic valve annulus during s... more 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 timedependent 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 9.474.9% and 2.171.1 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.
Medical & Biological Engineering & Computing, Jul 1, 1997
used as a reference signal to evaluate the accuracy of time-frequency representation techniques f... more used as a reference signal to evaluate the accuracy of time-frequency representation techniques for studying multicomponent signals. The composition of this simulated 1isbasedonthehypothesisthatan1 is based on the hypothesis that an 1isbasedonthehypothesisthatan1 recorded on the thorax over the epic, a/area of the heart is composed of constant frequency vibrations from the mitral valve and a frequency modulated vibration from the myocardium. Essentially, the simulated 1consistsofavalvularcomponentandamyocardialcomponent.Thevalvularcomponentismodelledastwoexponentiallydecayingsinusoidsof50Hzand150Hzandthemyocardialcomponentismodet/edbyafrequencymodulatedwavebetween20Hzand100Hz.Thestudyshowsthatthesimulated1 consists of a valvular component and a myocardial component. The valvular component is modelled as two exponentially decaying sinusoids of 50 Hz and 150 Hz and the myocardial component is modet/ed by a frequency modulated wave between 20 Hz and 100 Hz. The study shows that the simulated 1consistsofavalvularcomponentandamyocardialcomponent.Thevalvularcomponentismodelledastwoexponentiallydecayingsinusoidsof50Hzand150Hzandthemyocardialcomponentismodet/edbyafrequencymodulatedwavebetween20Hzand100Hz.Thestudyshowsthatthesimulated1 has temporal and spectral characteristics similar to 1recordedinhumansanddogs.Italsoshowsthatthespectrogramcannotresolvethethreecomponentsofthesimulated1 recorded in humans and dogs. It also shows that the spectrogram cannot resolve the three components of the simulated 1recordedinhumansanddogs.Italsoshowsthatthespectrogramcannotresolvethethreecomponentsofthesimulated1. It is concluded that it is necessary to search for a better timefrequency representation technique for studying the time-frequency distribution of multicomponent signals such as the simulated $1.
IEEE Transactions on Medical Imaging, Apr 1, 2003
Journal of Applied Physiology, 2009
Discrepancies between catheter and Doppler estimates of valve effective orifice area can be predicted from the pressure recovery phenomenon. Practical implications with regards to quantification of aortic stenosis severity
HAL (Le Centre pour la Communication Scientifique Directe), 2003
We sought to obtain more coherent evaluations of aortic stenosis severity. The valve effective or... more We sought to obtain more coherent evaluations of aortic stenosis severity. 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. 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. 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. 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.
Characterization of spectral broadening of Doppler signals recorded in the left ventricular outflow tract of patients with a valvular aortic stenosis
Ultrasonic Doppler signals were recorded in the left ventricular outflow tract of 48 patients to ... more Ultrasonic Doppler signals were recorded in the left ventricular outflow tract of 48 patients to detect aortic valve stenosis. Extraction of Doppler spectral parameters was based on the characterization of spectral broadening. Results showed that the spectral envelope area is the best parameter among those tested for discriminating between patients with and without aortic pressure gradient, and also between patients
Ultrasound in Medicine and Biology, 1996
Classification of bioprosthetic valve closure sounds by a neural network using linear prediction coefficients
A three layers feed-forward back-propagation neural network was trained to classify bioprosthetic... more A three layers feed-forward back-propagation neural network was trained to classify bioprosthetic valve closure sounds from 47 patients with a porcine bioprosthetic valve inserted in the aortic position. Twenty-four patients had a normal valve and 23 a degenerated one. Twelve linear prediction coefficients computed from the closure sounds were used as the network input The neural network yielded 89% correct classification in an evaluation using the leave-one-out method. This study confirmed the potential of heart sound classification by using a neural network.
Mathematical and Computer Modelling, 1988
[Digital phonocardiography: a non-invasive technic for follow-up of bioprosthetic heart valves]
PubMed, Feb 25, 1988
A system for real-time cardiac acoustic mapping
This paper describes the structure of a real-time cardiac acoustic mapping system (RTCAMS) which ... more This paper describes the structure of a real-time cardiac acoustic mapping system (RTCAMS) which displays the amplitude of the phonocardiogram (PCG) recorded on the surface of the thorax with an acoustic probe composed of an array of 25 microphones. The basic components of the RTCAMS are the acoustic probe, a PCG module, and a digital signal processing (DSP) board installed
Effect of concomitant asymmetric septal hypertrophy when assessing the severity of aortic valve stenosis: an in-vitro study
PubMed, Sep 1, 2012
Background and aim of the study: Aortic valve stenosis (AS) is an important cardiovascular diseas... more Background and aim of the study: Aortic valve stenosis (AS) is an important cardiovascular disease that affects between 2% and 7% of the elderly population in industrialized countries. AS often coexists with asymmetric septal hypertrophy (ASH), which is generally caused by a protrusion of the hypertrophied left ventricular outflow tract (LVOT) just below the aortic valve. The study aim was to determine, based on measurement of the aortic valve effective orifice area (EOA), if ASH might potentially interfere with the assessment of AS severity. Methods: The effects of different levels of ASH (from normal to 90%) on the EOA measured from orifices mimicking different AS severities, and from a home-built AS model constructed from a bioprosthetic aortic valve, were examined in a pulsatile flow in-vitro model. Results: For the most severe AS, the level of ASH had no impact on the measured EOA. In contrast, for the less severe AS, beyond an ASH level of 50% the AS severity was progressively overestimated, and reached a reduction of about 60% of EOA for a ASH level of 90%. Conclusion: The presence of concomitant ASH may cause an overestimation of the hemodynamic severity of AS. The extent of overestimation is more important in less-severe AS. Hence, the presence of ASH may lead the clinician to conclude, erroneously, that the AS is severe and that aortic valve replacement is indicated. However, beyond an ASH level of 50% the AS severity can be accurately determined.
Proceedings of SPIE, Apr 12, 2002
Application of the cone-kernel distribution to study the effect of myocardial contractility in the genesis of the first heart sound in dog
In order to examine the effect of myocardial contractility in the production of the first heart s... more In order to examine the effect of myocardial contractility in the production of the first heart sound (S1), the cone-kernel distribution (CKD) was applied to the thoracic S1 in dogs under various cardiac contractile states. The results showed that the dominant components of S1 are highly concentrated in a specific frequency band between 30 and 50 Hz with a horizontal
Various methodologies have been used to estimate and map percent impervious surface area (%ISA) u... more Various methodologies have been used to estimate and map percent impervious surface area (%ISA) using moderate resolution remote sensing imagery (e.g., Landsat Thematic Mapper). There is, however, a lack of comparative analyses among these methods. This study compares three major spectral analysis techniques (regression modeling, regression tree, and normalized spectral mixture analysis (NSMA)) for continuous %ISA estimation using Landsat imagery for 1986 and 2002 for the seven-county Twin Cities Metropolitan Area of Minnesota. Our study showed that all three techniques demonstrate the capability for estimating %ISA accurately, with RMSE ranging from 7.3 percent to 11 percent and R 2 of 0.90 to 0.96 for both years. Comparatively, regression modeling and regression tree methods produced similar results; however, both of them are highly dependent on accurate masks to differentiate urban impervious surfaces from bare soil. Within the urban mask, the regression tree-based estimates were the most accurate. In terms of time and cost, the NSMA approach is most efficient, but it tends to underestimate the percent imperviousness for highly developed areas. Findings from the study provide guidance for the selection of %ISA estimation techniques using moderate resolution remote sensing data, along with information for further methodological improvements.
Ultrasound in Medicine and Biology, 1991
Amplitude distributions of Doppler spectrograms were characterized in a group of 22 patients havi... more Amplitude distributions of Doppler spectrograms were characterized in a group of 22 patients having no aortic pressure gradient and another group of 26 patients having a stenotic aortic valve. Specifically, for each patient, the ratios of the mean amplitude in three normalized frequency bands (low, middle and high) to the mean amplitude of the Doppler spectrogram computed in selected portions of the systolic period were considered. Pulsed-wave Doppler spectrograms were recorded by positioning the sample volume in the left ventricular outflow tract, approximately 1 cm below the aortic valve. Statistically significant differences were found between the middle (p = 0.041) and high (p = 0.028) frequency bands of Doppler signals recorded from the two groups of patients. The differences observed are believed to be attributed to blood flow eddies generated below the stenotic aortic heart valve and to changes in blood flow orientation.
Optimization of Doppler velocity echocardiographic measurements using an automatic contour detection method
Intra- and inter-observer variability in Doppler velocity echocardiographic measurements (DVEM) i... more Intra- and inter-observer variability in Doppler velocity echocardiographic measurements (DVEM) is a significant issue. Indeed, imprecisions of DVEM can lead to diagnostic errors, particularly in the quantification of the severity of heart valve dysfunction. To minimize the variability and rapidity of DVEM, we have developed an automatic method of Doppler velocity wave contour detection, based on active contour models. To validate our new method, results obtained with this method were compared to those obtained manually by an experienced echocardiographer on Doppler echocardiographic images of left ventricular outflow tract and transvalvular flow velocity signals recorded in 30 patients, 15 with aortic stenosis and 15 with mitral stenosis. We focused on three essential variables that are measured routinely by Doppler echocardiography in the clinical setting: the maximum velocity, the mean velocity and the velocity-time integral. Comparison between the two methods has shown a very good agreement (linear correlation coefficient R(2) = 0.99 between the automatically and the manually extracted variables). Moreover, the computation time was really short, about 5s. This new method applied to DVEM could, therefore, provide a useful tool to eliminate the intra- and inter-observer variabilities associated with DVEM and thereby to improve the diagnosis of cardiovascular disease. This automatic method could also allow the echocardiographer to realize these measurements within a much shorter period of time compared to standard manual tracing method. From a practical point of view, the model developed can be easily implanted in a standard echocardiographic system.
Independent contribution of left ventricular ejection time to the mean gradient in aortic stenosis
PubMed, Sep 1, 2002
Background and aims of the study: Transvalvular mean pressure gradients (MPG) are important in th... more 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.
Experiments in Fluids, Sep 30, 2005
The effective orifice area (EOA) is the most commonly used parameter to assess the severity of ao... more The effective orifice area (EOA) is the most commonly used parameter to assess the severity of aortic valve stenosis as well as the performance of valve substitutes. Particle image velocimetry (PIV) may be used for in vitro estimation of valve EOA. In the present study, we propose a new and simple method based on Howe's developments of Lighthill's aero-acoustic theory. This method is based on an acoustical source term (AST) to estimate the EOA from the transvalvular flow velocity measurements obtained by PIV. The EOAs measured by the AST method downstream of three sharp-edged orifices were in excellent agreement with the EOAs predicted from the potential flow theory used as the reference method in this study. Moreover, the AST method was more accurate than other conventional PIV methods based on streamlines, inflexion point or vorticity to predict the theoretical EOAs. The superiority of the AST method is likely due to the nonlinear form of the AST. There was also an excellent agreement between the EOAs measured by the AST method downstream of the three sharp-edged orifices as well as downstream of a bioprosthetic valve with those obtained by the conventional clinical method based on Doppler-echocardiographic measurements of transvalvular velocity. The results of this study suggest that this new simple PIV method provides an accurate estimation of the aortic valve flow EOA. This new method may thus be used as a reference method to estimate the EOA in experimental investigation of the performance of valve substitutes and to validate Doppler-echocardiographic measurements under various physiologic and pathologic flow conditions.
Ultrasound in Medicine and Biology, 1994
A pattern recognition system was used to classify Doppler blood flow signals for the determinatio... more A pattern recognition system was used to classify Doppler blood flow signals for the determination of lower fimb arterial stenoses. The diagnostic features were extracted from time-frequency representations of Doppler signals. Three techniques were tested to estimate time-frequency representations: the short-time Fourier transform, the autoregressive (AR) modeling, and the Bessel distribution. A boundary tracking algorithm was proposed to extract the frequency contour of the Doppler time-frequency representations. Based on the characteristics of the Doppler frequency contour, shape descriptors from an autoregressive analysis were proposed as diagnostic features. Simple algorithms were proposed to normalize these autoregressive shape descriptors. Amplitude distribution of the Doppler time-frequency representation was also found useful for stenosis classification. A total of 379 arterial segments from the aorta to the popliteal artery were classified by the pattern recognition system into three categories of diameter reduction (0-19%, 20-49%, and 50-99%). The short-time Fourier transform provided an overall accuracy of 80% (kappa = 0.38); AR modeling, 81% (kappa = 0.42); and the Bessel distribution, 82% (kappa = 0.43). All these results are better than those based on visual interpretation (accuracy = 76%, kappa = 0.29) performed by a trained technologist. The AR modeling and the Bessel distribution improved the performance of the pattern recognition system in comparison with the short-time Fourier transform. It is likely that with further improvement, the pattern recognition approach will be a useful clinical tool to quantify stenoses and to follow the disease progression with more reliability and less bias than visual interpretation as done currently in clinical practice.
Journal of Biomechanics, 2006
In presence of aortic stenosis, a jet is produced downstream of the aortic valve annulus during s... more 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 timedependent 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 9.474.9% and 2.171.1 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.
Medical & Biological Engineering & Computing, Jul 1, 1997
used as a reference signal to evaluate the accuracy of time-frequency representation techniques f... more used as a reference signal to evaluate the accuracy of time-frequency representation techniques for studying multicomponent signals. The composition of this simulated 1isbasedonthehypothesisthatan1 is based on the hypothesis that an 1isbasedonthehypothesisthatan1 recorded on the thorax over the epic, a/area of the heart is composed of constant frequency vibrations from the mitral valve and a frequency modulated vibration from the myocardium. Essentially, the simulated 1consistsofavalvularcomponentandamyocardialcomponent.Thevalvularcomponentismodelledastwoexponentiallydecayingsinusoidsof50Hzand150Hzandthemyocardialcomponentismodet/edbyafrequencymodulatedwavebetween20Hzand100Hz.Thestudyshowsthatthesimulated1 consists of a valvular component and a myocardial component. The valvular component is modelled as two exponentially decaying sinusoids of 50 Hz and 150 Hz and the myocardial component is modet/ed by a frequency modulated wave between 20 Hz and 100 Hz. The study shows that the simulated 1consistsofavalvularcomponentandamyocardialcomponent.Thevalvularcomponentismodelledastwoexponentiallydecayingsinusoidsof50Hzand150Hzandthemyocardialcomponentismodet/edbyafrequencymodulatedwavebetween20Hzand100Hz.Thestudyshowsthatthesimulated1 has temporal and spectral characteristics similar to 1recordedinhumansanddogs.Italsoshowsthatthespectrogramcannotresolvethethreecomponentsofthesimulated1 recorded in humans and dogs. It also shows that the spectrogram cannot resolve the three components of the simulated 1recordedinhumansanddogs.Italsoshowsthatthespectrogramcannotresolvethethreecomponentsofthesimulated1. It is concluded that it is necessary to search for a better timefrequency representation technique for studying the time-frequency distribution of multicomponent signals such as the simulated $1.
IEEE Transactions on Medical Imaging, Apr 1, 2003
Journal of Applied Physiology, 2009
Discrepancies between catheter and Doppler estimates of valve effective orifice area can be predicted from the pressure recovery phenomenon. Practical implications with regards to quantification of aortic stenosis severity
HAL (Le Centre pour la Communication Scientifique Directe), 2003
We sought to obtain more coherent evaluations of aortic stenosis severity. The valve effective or... more We sought to obtain more coherent evaluations of aortic stenosis severity. 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. 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. 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. 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.
Characterization of spectral broadening of Doppler signals recorded in the left ventricular outflow tract of patients with a valvular aortic stenosis
Ultrasonic Doppler signals were recorded in the left ventricular outflow tract of 48 patients to ... more Ultrasonic Doppler signals were recorded in the left ventricular outflow tract of 48 patients to detect aortic valve stenosis. Extraction of Doppler spectral parameters was based on the characterization of spectral broadening. Results showed that the spectral envelope area is the best parameter among those tested for discriminating between patients with and without aortic pressure gradient, and also between patients
Ultrasound in Medicine and Biology, 1996