Biomedical subjects

Silvia Comani

Publications and source records attributed to Silvia Comani.

12 recordsLinked to original sources

PubMed2006

Performance comparison of six independent components analysis algorithms for fetal signal extraction from real fMCG data.

In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction.

Algorithms↗

PubMed2006

Fetal cardiac time intervals estimated on fetal magnetocardiograms: single cycle analysis versus average beat inspection.

Fetal cardiac time intervals (fCTI) are dependent on fetal growth and development, and may reveal useful information for fetuses affected by growth retardation, structural cardiac defects or long QT syndrome. Fetal cardiac signals with a signal-to-noise ratio (SNR) of at least 15 dB were retrieved from fetal magnetocardiography (fMCG) datasets with a system based on independent component analysis (ICA). An automatic method was used to detect the onset and offset of the cardiac waves on single cardiac cycles of each signal, and the fCTI were quantified for each heartbeat; long rhythm strips were used to calculate average fCTI and their variability for single fetal cardiac signals. The aim of this work was to compare the outcomes of this system with the estimates of fCTI obtained with a classical method based on the visual inspection of averaged beats. No fCTI variability can be measured from averaged beats. A total of 25 fMCG datasets (fetal age from 22 to 37 weeks) were evaluated, and 1768 cardiac cycles were used to compute fCTI. The real differences between the values obtained with a single cycle analysis and visual inspection of averaged beats were very small for all fCTI. They were comparable with signal resolution (+/-1 ms) for QRS complex and QT interval, and always <5 ms for the PR interval, ST segment and T wave. The coefficients of determination between the fCTI estimated with the two methods ranged between 0.743 and 0.917. Conversely, inter-observer differences were larger, and the related coefficients of determination ranged between 0.463 and 0.807, assessing the high performance of the automated single cycle analysis, which is also rapid and unaffected by observer-dependent bias.

Adult↗

PubMed2006

Modulation of MCP-1 and iNOS by 50-Hz sinusoidal electromagnetic field.

The purpose of this study was to investigate whether overnight exposure to 1 mT-50 Hz extremely low-frequency sinusoidal electromagnetic field (EMF) affects the expression and production of inducible nitric oxide synthase (iNOS) and monocyte chemotactic protein-1 (MCP-1) in human monocytes. RT-PCR and Western blot analysis demonstrate that EMF exposure affects the expression of iNOS and MCP-1 in cultured human mononuclear cells at the mRNA level and protein synthesis. Interestingly, the effects of EMF exposure clearly differed with respect to the potentiation and inhibition of iNOS and MCP-1 expression. Whereas iNOS was down-regulated both at the mRNA level and at the protein level, MCP-1 was up-regulated. These results provide helpful information regarding the EMF-mediated modulation of the inflammatory response in vivo. However, additional studies are necessary to demonstrate that EMF acts as a nonpharmacological inhibitor of NO and inducer of MCP-1 in some diseases where the balance of MCP-1 and NO may be important.

Chemokine CCL2↗

PubMed2006

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Acoustic Stimulation↗

PubMed2005

Independent component analysis of fMRI group studies by self-organizing clustering.

Independent component analysis (ICA) is a valuable technique for the multivariate data-driven analysis of functional magnetic resonance imaging (fMRI) data sets. Applications of ICA have been developed mainly for single subject studies, although different solutions for group studies have been proposed. These approaches combine data sets from multiple subjects into a single aggregate data set before ICA estimation and, thus, require some additional assumptions about the separability across subjects of group independent components. Here, we exploit the application of similarity measures and a related visual tool to study the natural self-organizing clustering of many independent components from multiple individual data sets in the subject space. Our proposed framework flexibly enables multiple criteria for the generation of group independent components and their random-effects evaluation. We present real visual activation fMRI data from two experiments, with different spatiotemporal structures, and demonstrate the validity of this framework for a blind extraction and selection of meaningful activity and functional connectivity group patterns. Our approach is either alternative or complementary to the group ICA of aggregated data sets in that it exploits commonalities across multiple subject-specific patterns, while addressing as much as possible of the intersubject variability of the measured responses. This property is particularly of interest for a blind group and subgroup pattern extraction and selection.

Adult↗

PubMed2005

Multichannel mapping of fetal magnetocardiogram in an unshielded hospital setting.

OBJECTIVES: To evaluate the feasibility of unshielded in-hospital multichannel mapping of fetal magnetocardiogram (FMCG), with a 36-channel system for standard adult magnetocardiographic (MCG) recordings, and its reliability according to the recommended standards for FMCG. METHODS: FMCG was ambulatory mapped with a 36-channel MCG system, in six normal pregnancies at different gestational ages. MCG analysis included adaptive digital filtering of 50 Hz, signal averaging, reconstruction of magnetic field distribution (MFD) and source localization. Fixed Point Independent Component Analysis algorithm (FastICA) was used to reconstruct the FMCG, separating them from maternal contamination and noise. RESULTS: The quality of FMCG recorded after the 32nd gestational week and reconstructed with FastICA was close to FMCG obtained in shielded rooms, and good enough to measure cardiac intervals and heart rate variability parameters. In two cases, reconstruction of the MFD during the QRS allowed three-dimensional localization of ventricular sources. CONCLUSIONS: A first demonstration has been given that multichannel mapping of FMCG can be performed in unshielded clinical environments, with resolution good enough for contactless assessment of fetal cardiac electrophysiology. FastICA processing on unshielded FMCG, recorded after the 32nd week, provided beat-to-beat analysis and heart rate variability assessment. Further work is needed to improve signal reconstruction in early pregnancy.

Adult↗

PubMed2005

Beat-to-beat estimate of fetal cardiac time intervals using magnetocardiography: longitudinal charts of normality ranges and individual trends.

BACKGROUND: Fetal magnetocardiography (fMCG) records fetal cardiac electro-physiological activity during the second half of gestation. We aimed at assessing normality values, related variability, and trends of fetal cardiac time intervals (fCTI) evaluated longitudinally from beat-to-beat fMCG analysis in uncomplicated pregnancies. MATERIALS AND METHODS: The fMCG were recorded with multi-channel system in shielded room. FCTI were estimated on more than 2600 fetal cardiac cycles from 51 fMCG data sets of uncomplicated pregnancies. Independent component analysis (ICA) allowed reconstructing reliable fetal signals for beat-to-beat identification of fCTI (RR, P wave, PQ, PR, QT, QTc, QRS, ST, and T wave); intra-individual variability analysis and trends were calculated; reference longitudinal charts accounted for intra- and inter-individual variations and were compared with figures estimated on averaged signals. RESULTS: For each data set, fCTI were calculated beat-to-beat on rhythm strips of more than 50 beats (95% overall detection rate). FCTI values, variability, and trends were in good agreement with available reference figures; intervals related to P and T waves were, respectively, underestimated and overestimated with respect to those estimated on averaged signals or obtained by other research groups. Errors were reduced and individual trends could be drawn. CONCLUSIONS: ICA permitted the reconstruction of reliable time course of fetal cardiac signals and the beat-to-beat calculation of time intervals, and normality ranges, with smaller errors with respect to previous studies. The retrieval of fetal traces with clear morphology and the longitudinal character of the study allowed estimating individual trends and beat-to-beat characterization, impossible with cross-sectional studies on averaged beats.

Adult↗

PubMed2004

Independent component analysis: fetal signal reconstruction from magnetocardiographic recordings.

Independent component analysis (ICA) was used for the processing of cardiological signals obtained by means of fetal magnetocardiography (fMCG), a technique allowing the non-invasive recording of the weak magnetic field variations associated to the electrical activity of the fetal heart. Purpose of the present work was to verify whether a computational-light ICA algorithm (FastICA), tailored to the characteristics of fMCG, could reconstruct reliable signals of the fetal cardiac activity during the last gestational trimester, when good electrophysiological traces are difficult to obtain although being extremely important for clinical diagnosis of severe fetal dysrhythmias. Several combinations of input recordings and output components were examined in order to assess the best configuration to successfully use FastICA. The reconstructed traces were compared with those obtained with deterministic techniques already used for this purpose, and they showed to be stable and reliable, unaffected by overlapped maternal and fetal beats and suitable for clinical applications.

Algorithms↗

PubMed2004

Concentric remodeling detection by magnetocardiography in patients with recent onset arterial hypertension.

The aim of this work was to evaluate a number of magnetocardiographic (MCG) indices in their predictive ability for left ventricular (LV) concentric remodeling. Twenty-five male patients affected by essential hypertension for no longer than 15 months and presenting signs of LV remodeling participated in the study; 25 normal men volunteers of comparable age were evaluated as controls. All participants underwent echocardiography (ECHO), electrocardiography (ECG), and magnetocardiography (MCG). Several MCG based indices were evaluated, namely the QRS Integral, T Integral, QRS-T Integral, T/QRS Integral, RS Index, and the variations of the electrical cardiac axis (ECA) orientation. MCG indices were compared with ECHO parameters, i.e., left ventricular mass index (LVMI) and relative wall thickness (RWT), and with ECG parameters, i.e., 12-lead standard ECG LVH Sokolow-Lyon and Cornell voltages. QRS Integral values for patients and controls were significantly different (P = 0.03), whereas T Integral values showed only a tendency to differentiate between patients and controls (P = 0.15). No significant correlation between MCG and echocardiographic indices in patients was found; RWT showed a tendency to correlate with QRS Integral (r = 0.34, P = 0.17) and with RS Index (r = 0.49, P = 0.15), and LVMI showed a tendency to correlate with the variations of the ECA orientation (r = 0.38, P = 0.10). Our findings, also supported by preliminary results on patients affected by hypertension induced LV hypertrophy, suggest a potential role of MCG in the evaluation of early electrophysiological alterations due to LV concentric remodeling.

Adult↗

PubMed2004

Characterization of fetal arrhythmias by means of fetal magnetocardiography in three cases of difficult ultrasonographic imaging.

Characterization of ultrasound detected fetal arrhythmias is generally performed by means of M-mode and pulsed Doppler echocardiography (fECHO), sonographic techniques that allow only indirect and approximate reconstruction of the true electrophysiological events that occur in the fetal heart. Several studies demonstrated the ability of fetal magnetocardiography (fMCG) to identify fetal arrhythmias. We report on three women, studied after the 32nd gestational week, who were referred for fMCG because of unsatisfying fetal cardiac visualization with fECHO due to maternal obesity, fetus in constant dorsal position hiding the fetal heart, intrauterine growth retardation, and oligohydramnios. Minor pericardial effusion was present in the third patient and digoxin therapy was given. FMCG were recorded with a 77-channel MCG system working in a shielded room. Independent Component Analysis (FastICA algorithm) was used to reconstruct fetal signals. The good quality of the retrieved fetal signals allowed real-time detection of arrhythmias and their classification as supraventricular extrasystoles (SVE), with/without aberrant ventricular conduction and/or atrioventricular block. The time course of the fetal cardiac rhythm was reconstructed for the entire recording duration; hence, fetal heart rate variability could be studied in time and frequency. Since isolated extrasystoles may progress to more hazardous supraventricular tachycardias, the noninvasive antenatal characterization of, even transient, fetal arrhythmias and their monitoring during pregnancy can be of great clinical impact.

Adult↗

PubMed2002

Magnetocardiography: current status and perspectives. Part I: Physical principles and instrumentation.

Magnetocardiography (MCG) is a non-invasive and risk-free technique allowing body surface recording of the magnetic fields generated by the electrical activity of the heart. The MCG recording system allows spatially and temporally accurate measurements of the very weak magnetic fields produced by currents flowing within myocardial fibers during cardiac activity. MCG has now been around for over 30 years, but only recently has progress in instrumentation put the technique on the verge of clinical applicability. This review summarizes the physical principles, instrumentation, main clinical applications and perspectives for the clinical use of MCG. This first part is devoted to the description of the physical principles and instrumentation.

Body Surface Potential Mapping↗

PubMed2002

Magnetocardiography: current status and perspectives. Part II: Clinical applications.

Magnetocardiography (MCG) is a non-invasive and risk-free technique allowing body surface recording of the magnetic fields generated by the electrical activity of the heart. The MCG recording system allows spatially and temporally accurate measurements of the very weak magnetic fields produced by currents flowing within myocardial fibers during cardiac activity. MCG has now been around for over 30 years, but only recently has progress in instrumentation put the technique on the verge of clinical applicability. This review summarizes the physical principles, instrumentation, main clinical applications and perspectives for the clinical use of MCG. This second part is devoted to the description of the main current clinical applications and perspectives.

Arrhythmias, Cardiac↗