Nicolò Malagutti

Computational finite element model of cardiac torsion.

Purpose A novel finite-element model of ventricular torsion for the analysis of the twisting behavior of the left human ventricle was developed, in order to investigate the influence of various biomechanical parameters on cardiac kinematics. Methods The ventricle was simulated as a thick-walled ellipsoid composed of nine concentric layers. Arrays of reinforcement bars were embedded in each layer to mimic physiological myocardial anisotropy. The reinforcement bars were activated through an artificial combination of thermal and mechanical effects in order to obtain a contractile behavior which is similar to that of myocardial fibers. The presence of an incompressible fluid inside the ventricular cavity was also simulated and the ventricle was combined with simple lumped-parameter hydraulic circuits reproducing preload and afterload. Changes to a number of cardiac parameters, such as preload, afterload and fiber angle orientation were introduced, in order to study the effects of these changes on cardiac torsion. Results The model is able to reproduce a similar torsional behavior to that of a physiological heart. The results of the simulations showed that there was sound correspondence between the model outcomes and available data from the literature. Results confirmed the importance of symmetric transmural patterns for fiber orientation. Conclusions This model represents an important step on the path towards unveiling the complexity of cardiac torsion. It proves to be a practical and versatile tool which could assist clinicians and researchers by providing them with easily-accessible, detailed data on cardiac kinematics for future diagnostic and surgical purposes.

Particle filter-based robust adaptive control for closed-loop administration of sodium nitroprusside

AbstractAutomatic closed-loop administration of medicinal drugs has been the subject of intense research for decades due to its undisputed potential benefits in terms of cost savings and improved patient outcomes. However, concerns still exist about the ultimate safety of engineered feedback controllers. Manual methods remain dominant in clinical practice. In this context, we present a novel feedback control architecture, which combines multiple robust controllers with a particle filter-based method for real-time tracking of a patient’s dose-response characteristic. The proposed method is applied to the case of the drug sodium nitroprusside, a vasodepressor used in the treatment of acute hypertension in intensive care and surgery, which is modelled as having a linear-time-varying dose-response characteristic. Our design takes into account the uncertainty in the patient response parameters, as well as potential nonzero-mean disturbances in the baseline arterial pressure and several possible time trends in the variation of the dose-response model. The performance and safety of the new approach are evaluated through an extensive computational simulation campaign. The results show that the proposed system can achieve adequate and safe feedback control of mean arterial pressure, thus validating our analysis and design. Our findings also highlight the fundamental - and possibly clinically overlooked - role of system excitation in ensuring that successful simultaneous identification and control of time-varying drug administration systems can be achieved.

A Robust Multiple-Model Adaptive Control System for Automatic Delivery of a Vasoactive Drug

Automatic closed-loop administration of sodium nitroprusside for the regulation of blood pressure in patients experiencing acute hypertension has been the subject of intense research over the last three decades. Yet, to date, manual administration of vasoactive drugs by a human operator remains the standard of care in the clinical setting. This manuscript describes a novel control approach for this application based on Robust Multiple-Model Adaptive Control (RMMAC). The RMMAC architecture features robust controllers designed with μ synthesis and Kalman filtering for system estimation. The new system was coupled with a mathematical model of a patient’s response to drug infusion and tested in computational simulations. The results indicate that the RMMAC approach has the potential to deliver robust performance even in challenging operating conditions, with mean arterial pressure remaining within the specified target range over 99% of the time.

Safety issues in adaptive control systems for automatic administration of vasoactive drugs

Abstract Automatic administration of drugs to control cardiovascular function during and after surgery has received considerable attention. Although the potential benefits associated with such a technology remain unquestioned, the several adaptive control strategies proposed thus far have had very limited success in practice. In developing robust adaptive control methodologies for drug dosing in cardiovascular applications, we have analysed a well-known multiple-model adaptive control strategy for blood pressure control. The results reveal that no guarantee of protection against actually inserting a destabilising controller into the closed-loop is given and one cannot even put a global upper bound on the time during which the destabilising controller is attached. We advocate caution towards issues which in the past may have been either disregarded or not subjected to a systematic analysis as instability could be fatal in the context of a clinical application.

Assessment of cardiac apex kinematics using a real-time 3D magnetic tracking system

The assessment of left ventricular apex (LVA) kinematics throughout the cardiac cycle could be useful for evaluating cardiac performance and efficiency. We proposed and evaluated in a sheep the use of a real-time 3D magnetic tracking system for the analysis of LVA kinematics. LVA kinematics was assessed using a real-time 3D magnetic tracking system, whose sensor was epicardially glued on the exposed LVA. Two indexes were calculated from the 3-Dimensional apex path traced by the magnetic sensor: the 3D Apex Path Length (3DAPL, length of 3D apex path) and the 3D Apex Path Volume (3DAPV, volume containing 3D apex path). Hemodynamic index of cardiac contractility (LVdP/dtMAX) was derived from Left Ventricular Pressure (LVP) measurement and evaluated against LVA kinematics parameters, at baseline and after acute ischemia, experimentally induced by coronary ligation. Results showed an opposite trend between LV hemodynamics and LVA kinematics: in the ischemic heart an increase of both 3DAPL (+24.5%) and 3DAPV (+151.7%) occurred compared with baseline, while LVdP/dtMAX decreased (-36.9%).