Biomedical subjects

J F Lerallut

Publications and source records attributed to J F Lerallut.

5 recordsLinked to original sources

PubMed1991

[Properties of arteries, cardiac function and structure in chronic hypertension].

Hypertension is a condition which demonstrates the relationship between the properties of the left ventricle and arterial system. The spectrum of aortic impedence expresses the principal factors which oppose LV ejection into the initial aorta: 1) capacitive forces related to the viscoelastic properties of the arterial wall, directly proportional to its rigidity, 2) forces of inertia which increase with the acceleration of the blood and which are inversely proportional to the aortic cross sectional area, 3) reflection. With respect to a stroke volume which is usually normal, hypertension is characterised by: 1) an increase in mean aortic pressure (MAP), 2) with respect to the increase in MAP, an increase in systolic, late systolic and differential pressures. These changes in the level and morphology of aortic pressure are due to: a) the increase in systemic arterial resistances, a continuous expression of the spectrum of the module, b) an increase in the elastic forces (increased rigidity of the aorta related to increased pressure and structural wall changes) usually insufficiently compensated by a decrease in the inertial forces (aortic dilatation), c) an earlier return of the reflected pulse wave, well before the end of the anterograde wave. Overall, there is a relationship between the mass, the geometry (concentric hypertrophy) and pump function of the left ventricle and the properties of the arterial system expressed in terms of pulse wave velocity, characteristic impedence or the late systolic pressure/stroke volume ratio. The relationship is much closer than that of the properties of the LV and aortic pressure.(ABSTRACT TRUNCATED AT 250 WORDS)

Aging↗

PubMed1985

Application of image processing techniques to gamma-angiography.

Different image processing techniques have been tested and compared on data derived from gamma-angiography images to detect the boundary of the left ventricle. The method involves a preprocessing step, followed by the edge detection itself. The best preprocessing is a nonlinear "variant" filtering, where each pixel is replaced by the average of the 3 X 3 neighborhood having the smallest variance. The edge detector giving the best contour is a Sobel operator. A second-order high-pass Butterworth filter also provides a good segmentation.

Computers↗

PubMed1984

Aortic input impedance in heart failure: comparison with normal subjects and its changes during vasodilator therapy.

This study was aimed at the evaluation of aortic impedance in patients with congestive heart failure. Aortic impedance (simultaneous measurements of aortic pressure and blood flow), mean (Wm) and pulsatile (Wp) powers were compared in 11 normal subjects and in 12 patients with heart failure. Pulse wave velocity (C: modified Moëns-Korteweg equation, simultaneous measurements of aortic pressure and radius) was determined under control conditions in all normal subjects and in 7 patients with heart failure. Impedance curves in patients with heart failure were characterized by increased values of the impedance modulus at 0 Hz (peripheral resistance) and at low frequencies. The characteristic impedance, C, and phase were not different from normal subjects. In six patients with heart failure, impedance curves were studied during nitroprusside infusion. During the infusion of the vasodilator, the impedance modulus at 0 Hz and at low frequencies decreased. The characteristic impedance was unchanged. The zero intercept of the phase was shifted towards lower frequencies. These results show that the changes in impedance curves in patients with heart failure are due to greater peripheral resistance and wave reflection. During nitroprusside infusion the stroke volume increased and the aortic blood flow became more pulsatile (greater values of low frequency components). This modification accounts for the increased values of Wm and Wp, and is related to decreased peripheral resistance and wave reflection.

Adult↗

PubMed1983

Forward and backward waves in the arterial system, their relationship to pressure waves form.

The purpose of this work was to analyze, in human subjects, the shape of the aortic pressure wave from its forward and backward components calculated by use of Westerhof's model. Twenty-nine patients were studied: 11 normal subjects, 11 hypertensive patients and 7 patients with congestive heart failure. The following measurements and calculations were performed both under control conditions and during either angiotensin infusion in 5 normal subjects or nitroprusside infusion in 6 hypertensive patients: cardiac output, aortic blood pressure (catheter tip micromanometer), blood flow velocity (electromagnetic catheter-tip velocity transducer) in the ascending aorta, aortic impedance and reflection coefficients allowing the calculation of the aortic forward and backward pressure waves. The results show that the shape of aortic pressure wave in hypertensive patients is related to increased arterial wall stiffness which determines greater values and overlap of the forward and backward waves. This result is corroborated by the changes observed during angiotensin infusion in normal subjects. The shape of pressure wave in heart failure patients is dicrotic. This shape is related to smaller values and overlap of forward and backward waves. This appears related to a reduced stroke volume. During peripheral vasodilation the shape of pressure wave in hypertensive patients becomes dicrotic. However, this was mainly related to later backward waves. These results confirm that the shape of pressure waves depends both on the arterial wall stiffness and on the left ventricular performance: mainly on the stroke volume. The calculation of forward and backward waves allows a quantitative analysis of pressure waves.

Adult↗

PubMedDate not supplied

Semi-automatic medical image processing.

During the last few years a number of systems for graphics generation and image processing have been developed by the authors. Depending on the application, one can consider many kinds of systems; for example for simple analysis of cellular images, a system that realizes the video mixing between a camera and graphics data from a microcomputer would be adequate. For a more elaborate analysis, such as angiographic and echographic images requiring a high level of interactivity, a semi-automatic acquisition system linked to a host computer would be necessary. Limits in precision and execution time of these semi-automatic systems leads to independent work-stations that realize digital acquisition, processing, and display of images.

Computers↗