Physiological modelling and non invasive diagnostics
Research focus
The Peer review has evaluated this group as Excellent
In this research line, four main topics can be identified: a) Cardiovascular modelling and autonomic nervous system study. The research is focused on the studying of cardiovascular system, by using an integrative approach of mathematical modelling of the complex control mechanisms involved together with the development of original algorithms of signal processing. Particular interest is dedicated to the studying of cardiovascular variability signals (mainly heart rate variability, blood pressure variability and respiration) for both the identification of significant magnitudes in the proposed modelling and the parameter extraction phase useful for diagnostic purposes. Cardiovascular variability signals are intended as significant probe towards a more objective evaluation of Autonomic Nervous System control elicited on heart and peripheral vessels: that has important implications on physiological studies as well as on clinical practice. From this kind of integrated modelling and signal processing, important parameters can be enhanced relative to the sympatho-vagal balance, to the measurement of baroreceptive gain (in open as well as in closedloop conditions), to complexity parameters (fractal dimension, entropy, measures of deterministic chaos and non linear dynamics) which constitute a novel approach towards a better diagnosis in cardiovascular pathologies (hypertension, ischemia and myocardial infarction, heart failure, atrial fibrillation, etc) and a more objective risk stratification tool in arrhythmias as well as in ischemic events. A core topic is the modelling of interactions between systemic and peripheral activity, their changes with acute and degenerative disease (vascular and neural), ageing, extreme conditions (e.g., micro-gravity). The approach is twofold: by simulation of complex distributed regulatory systems and multivariate cardiovascular variability data analysis models. b) Cardiovascular image processing. This research deals with the development and application of advanced image processing techniques to cardiovascular images (2D and real-time 3D echocardiography, cardiac MRI, CT) for studying pathophysiological properties of heart and vessels (volumetric quantification of left ventricular and atrial dimensions, quantification of regional perfusion of the heart 55 through contrast-enhancement imaging processing, 3D detection of regional wall motion abnormalities, Doppler coronary flow analysis, 3D tracking of the mitral valve, etc). The obtained information can then be fused with other parameters detected from monodimensional signals in order to achieve a more comprehensive quantification of the cardiovascular phenomena involved in physiological studies, as well as in the clinical applications (i.e. in the investigation of clinical correlates of myocardial infarction, heart failure, arrhythmias, etc). A further and novel area of application is in the evaluation of cardiovascular system responses during parabolic flight experiments: from real-time 3D echocardiography and Tissue Doppler images, changes in morphologic and functional left ventricular indices relevant to abrupt changes in gravity can be evaluated. This information can be used both to better understand the underlying physiology in these transient altered conditions (increased or decreased preload) in normal subjects, and to evaluate possible countermeasures for space applications. c) Central nervous system signals and image processing. This research line concerns with the development of methods of signal processing (EEG, EP, ERP) and fusion among different image modalities (MRI, fMRI, NIRS) in the studying of pathophysiological conditions of central nervous system. In particular, a great deal of activity has been carried out for the local field potential treatment when recorded at the subthalamic level in Parkinsonian patients undergoing deep stimulation therapy protocol. The main objective is to obtain quantitative parameters which could provide direct information about the qualitative and quantitative responses of the brain under stimulation: spectral parameters evidence important relationships in the various stimulation sites and bispectrum and bicoherence emphasize non linear synchronisations. Further, neurological applications of MRI will be explored for connectivity studies and multimodality processing (i.e. in epilepsy, in Parkinson’s disease, etc) as well as in the investigation of structural and microstructural characteristics (diffusion tensor and fibre-tracking), chemical information in ageing and neuro-degenerative diseases. Finally, in PET imaging, statistical algorithms (OSEM) improved with resolution recovery features will be adapted to the next generation machines which enhance both 3D and time resolution features (time of flight). d) e-Health This research line concerns with the robust application of computer science, communications technologies, artificial intelligence, mathematics, and database. Attention is given to modelling of healthcare information environments, systems and patient care processes also using the Unified Modeling Language (UML); applications of biometrics system for authentication and access gain; application of healthcare standards, including Digital Image and Communication in Medicine (DICOM), Health Level Seven (HL7) Messaging Standards V2.x and V3.x, HL7 Clinical Document Architecture (CDA) 2, the Integrating of Healthcare Enterprise (IHE), and the ASTM Continuity of Care Record (CCR) standard. Healthcare information systems benchmarking and Health Technology Transfers (HTT) are considered too.
Dipartimento di afferenza
Docenti afferenti
Full Professors
Giuseppe Baselli
Sergio Cerutti
Francesco Pinciroli
Associate Professors
Gianfranco Dacquino
Maria Gabriella Signorini
Assistant Professors
Giuseppe Andreoni
Annamaria Bianchi
Enrico Caiani
Luca Mainardi