Département d’Information Médicale, Université de Rennes I
The CARDIOLAB project is dedicated to the development of Computer
Assisted Instruction (CAI) and computer aided diagnosis systems in the field of cardiology. CARDIOLAB
is a framework that incorporates different kinds computational models of the heart’s electrical activity. The goal
is to provide users with an environment capable of predicting and explaining rhythmic disorders. By prediction,
we mean computing the heart’s electrical activity when modeled physiological parameter values are given as initial
conditions. By explanation, we mean the task of deriving the possible causes of some observed data. Because of
these two aspects, CARDIOLAB’s field of
application also includes basic, clinical and pharmacological research, and ultimately, intelligent monitoring
system design.
CARDIOLAB’s first role is to simulate cardiac electrical activity.
A central concern in simulation studies is the adequation of a designed model with respect to its intended goal.
Models of cardiac electrical activity may differ in complexity, level of description and representation. Depending
on the desired level of detail, analytical, cellular automatas and qualitative models can be used. Their advantages
and shortcomings can be summarized in terms space and time complexities, ease of interpretation, and clinical relevance.
The framework incorporates all three kinds of models, allowing a spatio-temporal multi-scale approach for studying
cardiac electrical activity. Since the clinical context is of prime importance, factors relevant for studying arrhythmias
and ischemias are taken into account. They include the durations of cell phases that characterize impulse formation
and conduction (e.g., slow-diastolic depolarization), and adaptative properties such as the rate-dependent repolarization
durations, or the recovery-state dependency of conduction speed. Transmembrane potentials are also computed for
simulating the ECG.
CARDIOLAB’s second role is to explain and diagnose. Explaining an ECG
requires qualification and reasoning capabilities. This presupposes that explicit descriptions of simulated processes
can be derived from the appropriate representations and the corresponding inference engines. Heart functions and
components are made explicit in the framework’s qualitative model. On the other hand, quantitative analysis of
rhythmic disorders may require detailed numerical models. For instance, re-entry in ischemic tissue or PVB-induced
ventricular fibrillation can only be reproduced by models with a great number of individual elements. In this respect,
the system incorporates 2D and 3D cellular automata models composed of thousands of elements.
To summarize, CARDIOLAB is an intelligent framework where both qualification
and quantification interact to simulate, and explain arrhythmias in a multi-scale approach. Because of these capabilities,
it could be a part of futur developments in the design of knowledge-based CCU monitoring systems.
SIMULATION WITH THE 2D CA MODEL : VENTRICULAR TACHYCARDIA
SIMULATION WITH THE 2D CA MODEL : VENTRICULAR FIBRILLATION
SIMULATION WITH THE 3D CA MODEL
BUILDING THE ARRYTHMIA KNOWLEDGE BASE
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