Biomedical subjects

S Cerutti

Publications and source records attributed to S Cerutti.

At least 91 records · Page 5Linked to original sources

PubMed1995

An elastic computerized brain atlas for the analysis of clinical PET/SPET data.

An elastic computerized brain atlas was developed for the analysis of positron emission tomography/single-photon emission tomography (PET/SPET) data. It consists of a set of digital anatomical contours and a template of regions of interest, schematically describing the brain, derived from a currently used anatomical/functional brain atlas. A warping algorithm, matching equivalent contours, was implemented to elastically fit the atlas to individual brain images. The elastic computerized brain atlas was applied to representative magnetic resonance imaging (MRI)-PET/SPET studies, MRI providing the anatomical information used by the matching procedure. The atlas is suited for clinical use in a nuclear medicine environment.

Brain↗

PubMed1995

Reduction of ocular artefacts in source current density brain mappings by ARX2 filtering.

Sweep by sweep analysis of event-related potentials (ERP) of the human scalp represents a reliable tool for both the diagnosis of neurologic diseases and the study of the central nervous system during cognitive tasks. The off-line procedure based on stochastic parametric identification and filtering herewith described, allows an accurate analysis of single-sweep ERP and a drastic reduction of ocular artefacts variously propagating through the skull. Moreover, the spatial distribution of the recorded ERP in bidimensional form was enhanced by using the Laplacian operator in order to get an estimate of the source current density (SCD) flow from the skull into the scalp. Complete single-trial signals were filtered according to an autoregressive model of signal generation with 2 exogenous inputs (ARX2). The ARX2 procedure models the recorded signal as the sum of three signals: (a) the background EEG activity, modelled as an autoregressive process driven by a white noise; (b) a filtered version of a reference signal carrying the average information contained in each sweep; (c) a signal due to the ocular artefact propagation. The evaluation of the effect of artefact suppression on those channels close to the eyes was compared with standard ordinary least squares method (OLS) based on a linear model of the influence of EOG on ERP. Finally, the better results obtainable through ARX filtering on sweep-by-sweep brain mappings are also presented.

Adult↗

PubMed1995

Pole-tracking algorithms for the extraction of time-variant heart rate variability spectral parameters.

Various algorithms of autoregressive (AR) recursive identification make it possible to evaluate power spectral distribution in correspondence with each sample of a time series, and time-variant spectral parameters can be calculated through the evaluation of the pole positions in the complex z-plane. In traditional analysis, the poles are obtained by zeroing the denominator of the model transfer function, expressed as a function of the AR coefficients. In this paper, two algorithms for the direct updating and tracking of movements of poles of an AR time-variant model on the basis of the innovation given to the coefficients are presented and investigated. The introduced algorithms are based upon 1) the classical linearization method and 2) a recursive method to compute the roots of a polynomial, respectively. In the present paper, applications in the field of heart rate variability (HRV) signal analysis are presented and efficient tools are proposed for quantitative extraction of spectral parameters (power and frequency of the low-frequency (LF) and high-frequency (HF) components) for the monitoring of the action of the autonomic nervous system in transient patho-physiological events. These computational methods seem to be very attractive for HRV applications, as they inherit the peculiarity of recursive time-variant identification, and provide a more immediate comprehension of the spectral process characteristics when expressed in terms of poles and AR spectral components.

Algorithms↗

PubMed1994

Single-sweep analysis using an autoregressive with exogenous input (ARX) model.

Single-sweep visual evoked potential analysis would be useful in clinical electrophysiology practice because it would make possible the evaluation of transient phenomena, but recording single-sweep visual evoked potentials is difficult because of the low signal-noise ratio. To increase this ratio we used a filter based on an autoregressive with exogenous input model. We studied a group of 12 diabetic patients matched with a control group of 14 normal subjects. The model, in most cases, allowed us to extrapolate the P100 component from each single sweep of visual evoked potential. The visual evoked potential values obtained by means of averaging were not significantly different in the groups studied, but single-sweep analysis showed different distribution of the P100 component amplitude. The preliminary results of our study evidenced differences in the amplitude and latency distribution of normal and diabetic subjects, thus confirming the power of this new technique and its ability to obtain some information that is masked by the averaging method.

Adult↗

PubMed1994

Model for the assessment of heart period and arterial pressure variability interactions and of respiration influences.

A model which assesses the closed-loop interaction between heart period (HP) and arterial pressure (AP) variabilities and the influence of respiration on both is applied to evaluate the sources of low frequency (LF approximately 0.1 Hz) and high frequency (HF, respiratory rate approximately 0.25 Hz) in conscious dogs (n = 18) and humans (n = 5). A resonance of AP closed-loop regulation is found to amplify LF oscillations. In dogs, the resonance gain increases slightly during baroreceptor unloading (mild hypotension obtained with nitroglycerine (NTG) i.v. infusion, n = 8) and coronary artery occlusion ((CAO), n = 6), and it is abolished by ganglionic transmission blockade ((ARF), Arfonad i.v. infusion, n = 3). In humans, this gain is considerably increased by passive tilt. Different, possibly central, sources of LF oscillations are also evaluated, finding a strong rhythmic modulation of HP during CAO. At HF, a direct respiratory arrhythmia is dominant in dogs at control, while it is considerably reduced during CAO. On the contrary, in humans, a strong influence of respiration on AP is shown which induces a reflex respiratory arrhythmia. An index of the gain of baroreceptive response, alpha cl, was decreased by NTG and CAO, and virtually abolished by chronic arterial baroreceptive denervation (TABD, n = 4) and ARF.

Animals↗

PubMed1994

Analysis of single trial movement-related brain macropotential.

A parametric method of identification of movement-related brain macropotentials on a single trial basis through an ARX (autoregressive with exogenous inputs) algorithm is presented. The basic estimation of the information contained in the single trial is taken from an average carried out on a sufficient number of trials, while the noise sources, EEG and EOG are characterized as exogenous inputs in the model. The simulations as well as the experimental results confirm the capability of the model to drastically improve the signal/noise ratio in each single trial and to satisfactorily identify the contributions of signal and noise in the overall recording. This way, using the same algorithm, a particularly efficient reduction of ocular artifacts is also achieved. The movement-related brain macropotentials recorded in three subjects show a high degree of variability from trial and this effect seems to be related to programming processes and evaluation of errors.

Adult↗

PubMed1994

Autonomic changes during hypnosis: a heart rate variability power spectrum analysis as a marker of sympatho-vagal balance.

Spectral analysis of beat-to-beat variability in electrocardiography is a simple, noninvasive method to analyze sympatho-vagal interaction. The electrocardiogram is analyzed by means of an automatic, autoregressive modeling algorithm that provides a quantitative estimate of R-R interval variability by the computation of power spectral density. Two major peaks are recognizable in this specter: a low-frequency peak (LF, -0.1 Hz), related to the overall autonomic activity (ortho+parasympathetic) and a high-frequency peak (HF, -0.25 Hz), representative of the vagal activity. The LF/HF ratio is an index of the sympatho-vagal interaction. This technique was applied, using a computer-assisted electrocardiograph, to 10 healthy volunteers (6 high and 4 low hypnotizable subjects as determined by the Stanford Hypnotic Susceptibility Scale, Form C) in randomized awake and neutral hypnosis conditions. Preliminary results indicated that hypnosis affects heart rate variability, shifting the balance of the sympatho-vagal interaction toward an enhanced parasympathetic activity, concomitant with a reduction of the sympathetic tone. A positive correlation between hypnotic susceptibility and autonomic responsiveness during hypnosis was also found, with high hypnotizable subjects showing a trend toward a greater increase of vagal efferent activity than did low hypnotizables.

Adult↗

PubMed1994

Power spectral analysis of cardiovascular variability in patients at risk for sudden cardiac death.

The time series of successive heart periods present important variations around its mean value, determining the phenomenon of heart rate variability (HRV), assessed with both time and frequency domain approaches. A low standard deviation of the heart period (a time domain index of HRV) is a powerful prognostic indicator of sudden coronary death in patients recovering from acute myocardial infarction. Spectral analysis of HRV usually demonstrates two major components: indicated as LF (low frequency, approximately 0.1 Hz) and HF (high frequency, approximately 0.25 Hz). They are defined by center frequency and associated power, which is expressed in msec2 or normalized units. When assessed in normalized units, LF and HF provide quantitative indicators of neural control of the sinoatrial node. Numerous experimental and clinical studies have consistently indicated that the LF component is a marker of sympathetic modulation and HF a marker of vagal modulation; the LF/HF ratio is a synthetic index of sympathovagal balance. In the analysis of 24-hour Holter recordings of normal subjects, a circadian rhythmicity of spectral markers of sympathetic and vagal modulation is clearly present, with a sympathetic predominance during the day and a vagal predominance during the night. In patients recovering from an acute myocardial infarction, spectral analysis of HRV revealed an increased sympathetic and decreased vagal activity during early convalescence, and a return to their normal balance by 6 to 12 months. A clear increase of LF was also evident in patients studied within a few hours of the onset of symptoms related to an acute myocardial infarction, independent of its location. Similarly, LF increased during transient myocardial ischemia. An increase in markers of sympathetic activity has also been observed prior to episodes of malignant arrhythmias. Spectral analysis of HRV could help in the understanding of the role of abnormal neural mechanisms in sudden coronary death, thus contributing to its prevention.

Death, Sudden, Cardiac↗

PubMed1994

Can power spectral analysis of heart rate variability identify a high risk subgroup of congestive heart failure patients with excessive sympathetic activation? A pilot study before and after heart transplantation.

BACKGROUND AND OBJECTIVES: Autonomic dysfunction seems to be involved in the progression and prognosis of severe congestive heart failure. Parasympathetic activity can still be abnormal 4-8 weeks after haemodynamic improvement by heart transplantation. To identify patients in heart failure with a more pronounced neural derangement and to analyse the changes in sympathetic and parasympathetic activity soon after heart transplantation, spectral indices of heart rate variability were assessed in 30 patients in severe heart failure and in 13 patients after heart transplantation; a group of 15 age-matched subjects served as controls. METHODS AND RESULTS: Heart rate variability was assessed by standard electrocardiography (ECG) in patients in heart failure and by oesophageal ECG in patients after heart transplantation. Compared with controls, the mean RR interval and total power were reduced in heart failure. The 30 patients showed two different patterns of heart rate variability: in 14 no power was detected in the low frequency band (0.03-0.15 Hz) (LF) and total power was mainly concentrated in the high frequency band (0.15-0.45 Hz) (HF), whereas in the remaining 16 patients power in the LF band was increased and power in HF band was reduced compared with the controls. Patients with undetectable LF had a lower mean RR interval and total power (745(25) v 864(36) ms, p < 0.05; 118(16) v 902(202) ms2, p < 0.001), higher concentration of plasma noradrenaline (635(75) v 329(54) pg/ml, p < 0.05), and worse clinical status and prognosis (4 deaths v no deaths at 6 month follow up) than patients with a dominant LF band. In the post-transplant patients both the mean PP interval of the remnant atrium and total power resembled results in the patients with heart failure; in 7 of the 13 post-transplant patients no power was detectable in the LF band: when both HF and LF power were present the results resembled those in the 16 patients in heart failure. CONCLUSIONS: These data suggest that in more advanced stages of congestive heart failure, power spectral analysis of heart rate variability allows identification of a subgroup of patients with higher sympathetic activation and poorer clinical status who are at major risk of adverse events. In the short term after cardiac transplantation the spectral profile of the rhythm variability of the remnant atrium was not improved, suggesting that parasympathetic withdrawal and sympathetic hyperactivity persist, despite the restoration of ventricular function.

Echocardiography, Transesophageal↗

PubMed1994

A bioimaging integration system implemented for neurological applications.

A system aimed at the management and fusion of multimodal biomedical images, including X-ray computed tomography, magnetic resonance imaging, positron emission tomography, and single photon emission computed tomography, has been implemented for neurological applications. This bioimaging integration system (BIS) consists of a network for image transmission from acquisition machines to dedicated image processing workstations, a software library for image standardization, and an image registration technique to project multimodal volumetric images into a common reference space. The registration procedure was evaluated in MRI/PET correlation studies, in which misalignment errors of 2.6 mm in the xy transaxial plane and 3.4 mm along the z axis were found. BIS has been validated for the anatomical-functional correlation analysis of MRI and PET images in neurological research protocols and clinical studies.

Brain Diseases↗

PubMed1994

ARX filtering of single-sweep movement-related brain macropotentials in mono- and multi-channel recordings.

A technique of stochastic parametric identification and filtering is applied to the analysis of single-sweep event-related potentials. This procedure, called AutoRegressive with n eXogenous inputs (ARXn), models the recorded signal as the sum of n+1 signals: the background EEG activity, modeled as an autoregressive process driven by white noise, and n signals, one of which represents a filtered version of a reference signal carrying the average information contained in each sweep. The other (n-1) signals could represent various sources of noise (i.e., artifacts, EOG, etc.). An evaluation of the effects of both artifact suppression and accurate selection of the average signal on mono- or multi-channel scalp recordings is presented.

Brain Mapping↗

PubMed1994

Non-linear dynamics of cardiovascular variability signals.

Long-term regulation of beat-to-beat variability involves several different kinds of controls. A linear approach performed by parametric models enhances the short-term regulation of the autonomic nervous system. Some non-linear long-term regulation can be assessed by the chaotic deterministic approach applied to the beat-to-beat variability of the discrete RR-interval series, extracted from the ECG. For chaotic deterministic systems, trajectories of the state vector describe a strange attractor characterized by a fractal of dimension D. Signals are supposed to be generated by a deterministic and finite dimensional but non-linear dynamic system with trajectories in a multi-dimensional space-state. We estimated the fractal dimension through the Grassberger and Procaccia algorithm and Self-Similarity approaches of the 24-h heart-rate variability (HRV) signal in different physiological and pathological conditions such as severe heat failure, or after heart transplantation. State-space representations through Return Maps are also obtained. Differences between physiological and pathological cases have been assessed and generally a decrease in the system complexity is correlated to pathological conditions.

Algorithms↗

PubMed1994

On-line beat-to-beat monitoring of spectral parameters of heart rate variability signal using a pole-tracking algorithm.

Spectral parameters extracted from the heart rate variability (HRV) signal are obtained on a beat-to-beat basis, following a procedure which uses two recursive algorithms. In the first step of the procedure the set of the AR model coefficients is updated each time a new RR value is available. Then from the estimated AR model parameters, the new position of the poles of the model transfer function in the complex z-plane is evaluated and, finally, through a residual calculation, it is possible to calculate the spectral parameters which quantify the control of the autonomic nervous system in assessing the cardiac frequency (i.e., power and frequency of LF and HF components). The whole procedure has first been tested on a simulated time series, in order to evaluate its performance in tracking the dynamic changes during different conditions; next the algorithms were employed in the study of the HRV signal for continuous monitoring of non-stationary conditions.

Algorithms↗

PubMed1994

Non-linear dynamics in the beat-to-beat variability of sympathetic activity in decerebrate cats.

Non-linear interactions between low-frequency rhythms (0.1 Hz) of beat-to-beat variability series of sympathetic discharge and respiratory rhythm (0.3 Hz) are observed in decerebrate artificially ventilated cats. Simple graphical tools as Poincaré and recurrence maps are used to detect, in a qualitative way, phase-locking phenomena. Non-parametric bispectral analysis is also carried out to quantify the degree of second-order coupling between oscillations at different frequencies.

Animals↗

PubMed1993

Power spectrum analysis of the fetal heart rate during noradrenaline infusion and acute hypoxemia in the chronic fetal lamb preparation.

In a chronically instrumented fetal lamb the effect on heart rate variability of noradrenaline as well as hypoxemia is studied by the use of power spectral analysis. Subsequent to both noradrenaline infusion and hypoxemia the very low frequency components of the variability are markedly decreased as compared with control conditions. After hypoxemia also a high frequency peak appears in the spectrum.

Acute Disease↗

PubMed1993

Power spectrum analysis of cardiovascular variability monitored by telemetry in conscious unrestrained rats.

Beat-to-beat variability of arterial pressure and heart period (R-R) was studied in eight conscious freely-moving adult male rats in which telemetric recordings of arterial pressure, ECG and respiratory movements were obtained under unrestrained and unstressed conditions. The beat-to-beat time series of these signals (systolic arterial pressure, diastolic arterial pressure and R-R) were analyzed, in the frequency domain, using autoregressive spectral analysis in order to detect and quantify the rhythmic components. In basal conditions, the systolic arterial pressure variability spectrum was characterized by three major spectral components which had central frequencies respectively of 0.08 +/- 0.03 Hz (very low frequency), 0.43 +/- 0.02 Hz (low frequency) and 1.36 +/- 0.19 Hz (high frequency). Similar rhythmic components were found in R-R signal variability. The very low frequency component included a higher percentage of total power in R-R variability spectrum (75.3%) than in systolic arterial pressure variability spectrum (58.4%). The low frequency component was more pronounced in both systolic and diastolic arterial pressure variability spectra. The high frequency component of R-R, systolic and diastolic arterial pressure was synchronous with respiration. Cross-spectral analysis revealed a high statistical coherence between R-R and arterial pressure variabilities in all the three frequency bands. An alpha-adrenergic blocker (phentolamine) specifically abolished the low frequency components of systolic and diastolic arterial pressure variability spectra, thus suggesting that low frequency is a marker of sympathetic modulation of vasomotor activity. The low frequency component of R-R variability spectrum was also markedly blunted. We suggest that cardiovascular variability signals, (R-R, systolic and diastolic arterial pressure) are composed almost of two main rhythms linked to respiration and vasomotor activity. These rhythms can be quantified in conscious unrestrained rats by using telemetry and spectral analysis. This approach seems to offer a new powerful tool for pharmacological studies in conscious small animals.

Animals↗

PubMed1993

Early and late effects of exercise and athletic training on neural mechanisms controlling heart rate.

OBJECTIVE: This study addresses the long term and short term effects of heavy dynamic exercise on neural control of heart rate. METHODS: A group of healthy controls was compared with (1) a group of trained athletes during a period of yearly rest (detrained) and (2) a group of trained athletes at the peak of their training routine. Additionally, a group of 10 controls was studied 1, 24, and 48 h after a single bout of maximal dynamic exercise. Spectral analysis of RR interval variability provided markers of sympathetic (low frequency, LF, 0.10 Hz) and vagal (high frequency, HF, 0.25 Hz) modulation of the sinoatrial node. RESULTS: (1) In detrained athletes resting bradycardia was accompanied by a predominant HF rhythmic component suggestive of a prevailing vagal tone. (2) Trained athletes showed a resting bradycardia together with high LF values, thus suggesting a more complex neural interaction modulating heart rate. An additional longitudinal part of the study, performed on a group of detrained athletes who were examined for the second time after resuming training, confirmed the finding of a prevailing LF component in resting conditions. (3) In the 10 control subjects maximal dynamic exercise induced an increase in LF which outlasted the cessation of exercise up to 24 h, suggesting a persistent sympathetic activation. (4) Passive tilt, a manoeuvre which enhances sympathetic drive, produced a greater enhancement of the LF component in trained athletes than in control subjects. CONCLUSIONS: The cardiac sympathetic excitation outlasting heavy dynamic exercise may explain the coexistence of training bradycardia with signs of enhanced sympathetic activity in trained champion athletes.

Adolescent↗

PubMed1993

Time-variant power spectrum analysis for the detection of transient episodes in HRV signal.

A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the heart rate variability (HRV) signal. The power spectrum is calculated from the AR coefficients derived from each single RR interval considered. Time-variant AR coefficients are determined through adaptive parametric identification with a forgetting factor which obtains weighed values on a running temporal window of 50 preceding measurements. Power spectrum density (PSD) is hence obtained at each cardiac cycle, making it possible to follow the dynamics of the spectral parameters on a beat-by-beat basis. These parameters are mainly the LF (low frequency) and the HF (high frequency) powers, and their ratio LF/HF. These together account for the balanced sympatho-vagal control mechanism affecting the heart rate. This method is applied to subjects suffering from transient ischemic attacks. The time variant spectral parameters suggest an early activation of LF component in the HRV power spectrum. It precedes by approximately 1.5-2 min the tachycardia and the ST displacement, generally indicative of the onset of an ischemic episode. The results suggest an arousal of sympathetic system before the acute attack.

Algorithms↗