Evaluation of respiratory influences on left ventricular function by means of echocardiographic approach

Porta, Alberto; Baselli, Giuseppe; Turiel, M.; Crema, C.; Vecchia, L. Dalla; Lucini, Daniela; Caiani, E.G.; Malliani, Alberto; Pagani, Massimo; Cerutti, S.

doi:10.1109/cic.1997.647918

Cited by 6 publications

(9 citation statements)

References 3 publications

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“…To evaluate the ability of the dynamic TW algorithm to reduce the interbeat variability, for each NY subject the same sequence of 64 consecutive beats utilised in protocol 2 was analysed as follows: the indices ESV, EDV, SV, EF%, PFR, PAFR, PER and tpVR were automatically obtained on a beat-to-beat basis (PORTA et al, 1997;CAIANI et al, 2000b), and their mean value, SD and var% were calculated.…”

Section: Protocol 4: Comparison Of Awl6 Variability With Beat-to-beatmentioning

confidence: 99%

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Analysis of cardiac left-ventricular volume based on time warping averaging

et al. 2002

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The cardiac left-ventricular (LV) volume signal, obtained by acoustic quantification, is affected by noise and respiratory modulation, resulting in a large beat-to-beat variability that affects the computation of LV function indices. A new method is proposed to improve the evaluation of LV indices by applying a signal averaging technique based on dynamic time warping to consecutive LV volume waveforms. Volume signals obtained from ten normal young (NY) subjects (mean age +/- SD: 25+/-5 years) were used to evaluate the performance of this algorithm. To evaluate its clinical utility, the effects of ageing and pharmacologically induced changes on LV function were assessed by studying, respectively, ten normal (N) adult subjects (age 64+/-8 years) and ten patients with dilated cardiomyopathy during a control and low-dose dobutamine (10 microg kg(-1) min(-1)) study. Indices of LV function were highly consistent, with a variability of less than 8%, even when only 16 beats were averaged, independently of their selection inside the whole recording. When compared with beat-to-beat measures, the averaging of 16 beats significantly reduced (by more than 50%) the interbeat variability of all indexes. Expected alterations in both diastolic and systolic function were evidenced both with ageing (peak filling atrial contraction and ejection rates: from 275+/-77 mls(-1), 76+/-30 ml s(-1) 230+/-70 mls(-1), respectively, in NY, to 160+/-33 mls(-1), 125+/-39 mls(-1), 163+/-54 mls(-1) in N) and with dobutamine (peak filling and ejection rates from 160+/-72 mls(-1) and 183+/-86 mls(-1) respectively, in control, to 253+/-75 mls(-1) and 251+/-105 mls(-1) with dobutamine). Signal averaging with time warping allows fast and improved assessment of LV function.

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Section: Protocol 4: Comparison Of Awl6 Variability With Beat-to-beatmentioning

confidence: 99%

“…The detection of the ESV was based on the detection of the R-wave on the ECG (PORTA et al, 1997). The minimum of the LV volume signal was searched inside a time window lasting a user-defined percentage of the mean heart period and starting from the R peak.…”

Section: Data Acquisitionmentioning

confidence: 99%

Analysis of cardiac left-ventricular volume based on time warping averaging

et al. 2002

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“…The beat-to-beat variability series were extracted (figure 1) as follows (Porta et al 1997). The RR interval was obtained as the time interval between two consecutive R peaks, detected by a traditional derivative threshold procedure.…”

Section: Extraction Of the Left Ventricular Function Parametersmentioning

confidence: 99%

“…In this perspective, an automated algorithm (Porta et al 1997) for the beat-to-beat extraction of LV function parameters from a few minutes continuous acquisition of LV volume waveforms was developed and the high-frequency (HF) respiratory spectral component (Akselrod et al 1981, Pagani et al 1986, Malliani et al 1991 was extracted by means of autoregressive spectral analysis. The study has been carried out on a group of normal young subjects and a group of normal older subjects, to evaluate the effects of ageing on respiratoryrelated power evaluated on the extracted beat-to-beat series of LV function parameters.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Hydrogen-Treated Pentacene Organic Thin Film Transistors

Yang

Suen

Whang

2004

Jpn. J. Appl. Phys.

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This study was designed to assess, using the echocardiographic acoustic quantification technique, the influence of respiration on left ventricular (LV) function and its modifications connected with the ageing process, quantifying in a non-invasive way the respiratory contribution to the LV volume variability. An automated algorithm is applied to extract the beat-to-beat measurements of LV function parameters from the LV volume signal, obtained from recordings lasting a few minutes. Mean values, amount of variability and spectral content were studied in a population of 17 normal young (mean age 25 ± 1 years) and 12 normal old (mean age 64 ± 2 years) subjects. Mean values of the beat-to-beat measurements of LV function parameters were able to point out alterations connected with the ageing process in peak filling rate, peak atrial filling rate and peak ejection rate. Spectral analysis, applied to the extracted variability series, displayed a predominance of the high-frequency (HF) component corresponding to respiration in all LV function parameters; moreover, age related changes of HF variability were observed in peak ejection rate. The HF power spectrum component of beat-to-beat series extracted from the LV signal can provide a non-invasive assessment of the fluctuations in ventricular parameters associated with respiration.

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“…For example, the 2-dimensional automated border detection (ABD) system used in the Hewlett Packard SONOS 2500 provides a detection of the LV endocardial border from the ultrasound scan plane which is highly operator-dependent 19 . In fact, the process of manual outlining and gain setting necessary in most ABD systems is time consuming, tedious, and very subjective 5,12,15 , as is indicated by the general lack of reproducibility between inter-and intra-observers. The objective of the work reported in this paper is to fully automate the procedure of extracting the LV boundary in 2-D echo sequences.…”

Section: Introductionmentioning

confidence: 99%

<title>Template and active contour matching for automated left ventricular boundary detection</title>

et al. 2001

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This paper presents an algorithm that extracts accurate left ventricular (LV) boundaries from a two-dimensional (2-D) echocardiographic (echo) sequence covering a cardiac cycle. Unlike user-dependent, manual or semi-automatic techniques, the key feature of this algorithm is its truly automated processing for estimation. First, the algorithm performs smoothing of the image in the LV target area, followed by enhancement of intensity differences and edge detection. In order to best localize the position of the LV boundary, the algorithm uses a deformable template model derived from prior knowledge of LV shape and an edge map obtained from boundary estimation. The deformable template model is matched to the target by minimizing an energy function induced by the difference between edge locations and tangents of the template and those of the current frame edge map. Since the shape of the endocardial boundary will vary between temporally distinct frames, a controlled continuity spline, a "snake", is then used to implement refined active contour matching to the current frame LV boundary. Frame-to-frame tracking of the LV boundary is incorporated by using the boundary estimate from one frame to initialize and help with the estimation in the subsequent frame, which leads to faster and more accurate LV estimation throughout the image sequence. Test results of this algorithm show that the combination of approximate template matching with smoothness constraints in snakes produces good LV boundary extraction even with significant false and/or missing edge information caused by poor contrast and noise.

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Evaluation of respiratory influences on left ventricular function by means of echocardiographic approach

Cited by 6 publications

References 3 publications

Analysis of cardiac left-ventricular volume based on time warping averaging

Analysis of cardiac left-ventricular volume based on time warping averaging

Characterization of Hydrogen-Treated Pentacene Organic Thin Film Transistors

<title>Template and active contour matching for automated left ventricular boundary detection</title>

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