Advanced model-based control studies for the induction and maintenance of intravenous anaesthesia

This paper describes strategies toward model-based automation of intravenous anaesthesia employing advanced control techniques. In particular, based on a detailed compartmental mathematical model featuring pharmacokinetic and pharmacodynamics information, two alternative model predictive control strategies are presented: a model predictive control strategy, based on online optimization, the extended predictive self-adaptive control and a multiparametric control strategy based on offline optimization, the multiparametric model predictive control. The multiparametric features to account for the effect of nonlinearity and the impact of estimation are also described. The control strategies are tested on a set of 12 virtually generated patient models for the regulation of the depth of anaesthesia by means of the bispectral index (BIS) using Propofol as the administrated anaesthetic. The simulations show fast response, suitability of dose, and robustness to induce and maintain the desired BIS setpoint

Automatic Control of General Anesthesia: New Developments and Clinical Experiments

L’anestesia generale è uno stato di coma farmacologicamente indotto, temporaneo e reversibile. Il suo obiettivo consiste nel provocare la perdita totale della coscienza e nel sopprimere la percezione del dolore. Essa costituisce un aspetto fondamentale per la medicina moderna in quanto consente di praticare interventi chirurgici invasivi senza causare ansia e dolore al paziente. Nella pratica clinica dell’anestesia totalmente endovenosa questi effetti vengono generalmente ottenuti mediante la somministrazione simultanea del farmaco ipnotico propofol e del farmaco analgesico remifentanil. Il dosaggio di questi farmaci viene gestito dal medico anestesista basandosi su linee guida farmacologiche e monitorando la risposta clinica del paziente. Recenti sviluppi nelle tecniche di elaborazione dei segnali fisiologici hanno consentito di ottenere degli indicatori quantitativi dello stato anestetico del paziente. Tali indicatori possono essere utilizzati come segnali di retroazione per sistemi di controllo automatico dell'anestesia. Lo sviluppo di questi sistemi ha come obiettivo quello di fornire uno strumento di supporto per l'anestesista. Il lavoro presentato in questa tesi è stato svolto nell'ambito del progetto di ricerca riguardante il controllo automatico dell'anestesia attivo presso l'Università degli Studi di Brescia. Esso è denominato ACTIVA (Automatic Control of Total IntraVenous Anesthesia) ed è il risultato della collaborazione tra il Gruppo di Ricerca sui Sistemi di Controllo dell’Università degli Studi di Brescia e l’Unità Operativa Anestesia e Rianimazione 2 degli Spedali Civili di Brescia. L’obiettivo del progetto ACTIVA consiste nello sviluppo teorico, nell’implementazione e nella validazione clinica di strategie di controllo innovative per il controllo automatico dell’anestesia totalmente endovenosa. Nel dettaglio, in questa tesi vengono inizialmente presentati i risultati sperimentali ottenuti con strutture di controllo basate sull'algoritmo PID e PID ad eventi per la somministrazione di propofol e remifentanil. Viene poi presentato lo sviluppo teorico e la validazione clinica di strutture di controllo predittivo basate su modello. Successivamente vengono presentati i risultati di uno studio in simulazione riguardante una soluzione di controllo innovativa che consente all'anestesista di regolare esplicitamente il bilanciamento tra propofol e remifentanil. Infine, vengono presentati gli sviluppi teorici ed i relativi studi in simulazione riguardanti soluzioni di controllo personalizzate per le fasi di induzione e mantenimento dell'anestesia.General anesthesia is a state of pharmacologically induced, temporary and reversible coma. Its goal is to cause total loss of consciousness and suppress the perception of pain. It constitutes a fundamental aspect of modern medicine as it allows invasive surgical procedures to be performed without causing anxiety and pain to the patient. In the clinical practice of total intravenous anesthesia, these effects are generally obtained by the simultaneous administration of the hypnotic drug propofol and of the analgesic drug remifentanil. The dosing of these drugs is managed by the anesthesiologist on the basis of pharmacological guidelines and by monitoring the patient's clinical response. Recent developments in physiological signal processing techniques have introduced the possibility to obtain quantitative indicators of the patient's anesthetic state. These indicators can be used as feedback signals for automatic anesthesia control systems. The development of these systems aims to provide a support tool for the anesthesiologist. The work presented in this thesis has been carried out in the framework of the research project concerning the automatic control anesthesia at the University of Brescia. The project is called ACTIVA (Automatic Control of Total IntraVenous Anesthesia) and is the result of the collaboration between the Research Group on Control Systems of the University of Brescia and the Anesthesia and Intensive Care Unit 2 of the Spedali Civili di Brescia. The objective of the ACTIVA project consists in the theoretical development, implementation, and clinical validation of innovative control strategies for the automatic control of total intravenous anesthesia. In detail, in this thesis the experimental results obtained with control structures based on the PID and on event-based PID controllers for the administration of propofol and remifentanil are initially presented. The theoretical development and clinical validation of model predictive control strategies is then proposed. Next, the results of a simulation study regarding an innovative control solution that allows the anesthesiologist to explicitly adjust the balance between propofol and remifentanil are given. Finally, the theoretical developments and the relative simulation studies concerning personalized control solutions for induction and maintenance phases of anesthesia are explained

Advanced multiparametric optimization and control studies for anaesthesia

Anaesthesia is a reversible pharmacological state of the patient where hypnosis, analgesia and muscle relaxation are guaranteed and maintained throughout the surgery. Analgesics block the sensation of pain; hypnotics produce unconsciousness, while muscle relaxants prevent unwanted movement of muscle tone. Controlling the depth of anaesthesia is a very challenging task, as one has to deal with nonlinearity, inter- and intra-patient variability, multivariable characteristics, variable time delays, dynamics dependent on the hypnotic agent, model analysis variability, agent and stability issues. The modelling and automatic control of anaesthesia is believed to (i) benefit the safety of the patient undergoing surgery as side-effects may be reduced by optimizing the drug infusion rates, and (ii) support anaesthetists during critical situations by automating the drug delivery systems. In this work we have developed several advanced explicit/multi-parametric model predictive (mp-MPC) control strategies for the control of depth of anaesthesia. State estimation techniques are developed and used simultaneously with mp-MPC strategies to estimate the state of each individual patient, in an attempt to overcome the challenges of inter- and intra- patient variability, and deal with possible unmeasurable noisy outputs. Strategies to deal with the nonlinearity have been also developed including local linearization, exact linearization as well as a piece-wise linearization of the Hill curve leading to a hybrid formulation of the patient model and thereby the development of multiparametric hybrid model predictive control methodology. To deal with the inter- and intra- patient variability, as well as the noise on the process output, several robust techniques and a multiparametric moving horizon estimation technique have been design and implemented. All the studies described in the thesis are performed on clinical data for a set of 12 patients who underwent general anaesthesia.Open Acces

CLOSED-LOOP CONTROLLED TOTAL INTRA VENOUS ANAESTHESIA

Anaesthesia is important for both surgery and intensive care and intravenous anaesthetics are widely used to provide rapid onset, stable maintenance, and rapid recovery compared with inhaled anaesthetics. The aim of the project on which this thesis is based was to investigate a reliable and safe methodology for delivering total intravenous anaesthesia using closed-loop control technology and bispectral analysis of human electroencephalogram (EEG) waveform. In comparison with Target Controlled Infusion (TCI), drug effect is measured during drug infusion in closed loop anaesthesia (CLAN). This may provide superior safety, better patient care, and better quality of anaesthesia whilst relieving the clinician of the need to make recurrent and minor alterations to drug administration. However, the development of a CLAN system has been hindered by the Jack of a 'gold standard' for anaesthetic states and difficulties with patient variability in pharmacokinetic and pharmacodynamic modelling, and a new and generic mathematical model of a closed-loop anaesthesia system was developed for this investigation. By using this CLAN model, investigations on pharmacokinetic and pharmacodynamic variability existing in patients were carried out. A new control strategy that combines a Proportional, Integral, Derivative (PID) controller, bispectral analysis of EEG waveform and pharmacokinetic/ pharmacodynamic models was investigated. Based on the mathematical model, a prototype CLAN system, the first CLAN system capable of delivering both hypnotics and analgesics simultaneously for total intravenous anaesthesia, was developed. A Bispectral Index (BIS), derived from power spectral and bispectral analysis on EEG waveform, is used to measure depth of anaesthesia. A supervision system with built-in digital signal processing techniques was developed to compensate the non-linear characteristics inherent in the system while providing a comprehensive protection mechanism for patient safety. The CLAN system was tested in 78125 virtual patients modelled using published data. Investigations on intravenous anaesthesia induction and maintenance with the CLAN system were carried out in various clinical settings on 21 healthy volunteers and 15 patients undergoing surgery. Anaesthesia targets were achieved quickly and well maintained in all volunteers/patients except for 2 patients with clinically satisfactory anaesthesia quality.Derriford Hospita