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One mechanism for the onset of arrhythmias is abnormal impulse initiation such as ventricular ectopic beats. These may be caused by abnormal calcium (Ca) cycling. The Luo-Rudy model was used to simulate the dynamics of intracellular Ca ([Ca]) handling and the initiation of ectopic beats in virtual ventricular myocytes and tissues. [Ca] in the reduced Ca handling equations settles to a steady state at low levels of intracellular sodium ([Na]), but oscillates when [Na] is increased. These oscillations emerge through a homoclinic bifurcation. In the whole cell, Ca overload, brought about by inhibition of the sodium-potassium pump and elevated [Na], can cause autorhythmic depolarisations. These oscillations interact with membrane currents to cause action potentials that propagate through one dimensional virtual tissue strands and two dimensional anisotropic virtual tissue sheets.

Mathematical modeling of cardiac mechanics could be a useful clinical tool, both in translating measured abnormalities in cardiac deformation into the underlying pathology, and in selecting a proper treatment. We investigated to what extent a previously published model of cardiac mechanics [6] could predict deformation in the healthy left ventricle, as measured using MR tagging. The model adequately predicts circumferential strain, but fails to accurately predict shear strain. However, the time course of shear strain proves to be that sensitive to myofiber orientation, that agreement between model predictions and experiment may be expected if fiber orientation is changed by only a few degrees.

In this article, we present a framework to estimate local myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is deformed to fit a clinical MRI, using a semi-automatic fuzzy segmentation, an affine registration method and a local deformable biomechanical model. An electromechanical model of the heart is then presented and simulated. Data assimilation makes it possible to estimate local contractility from given displacements. Presented results on adjustment to clinical data and on assimilation with simulated data are very promising. Current work on model calibration and estimation of patient parameters open up possibilities to apply this framework in a clinical environment.

We evaluated applicability of ICA (Independent Component Analysis) for the separation of functional components from PET (Positron Emission Tomography) cardiac images. The effects of varying myocardial perfusion to the separation results were investigated using a dynamic 2D numerical phantom. The effects of motion in cardiac region were studied using a dynamic 3D phantom. In this 3D phantom, the anatomy and the motion of the heart were simulated based on the MCAT (Mathematical Cardiac Torso) phantom and the image acquisition process was simulated with the PET SORTEO Monte Carlo simulator. With ICA, it was possible to separate the right and left ventricles in the all tests, even with large motion of the heart. In addition, we extracted the ventricle volumes from the ICA component images using the Deformable Surface Model based on Dual Surface Minimization (DM-DSM). In the future our aim is to use the extracted volumes for movement correction.

Radio-frequency (RF) ablation uses electrode-catheters to destroy abnormally conducting myocardial areas that lead to potentially lethal tachyarrhythmias. The procedure is normally guided with x-rays (2D), leading to errors in location and excessive radiation exposure. One of our goals is to provide pre- and intra-operative 3D MR guidance in XMR systems (combined X-ray and MRI room) by locating myocardial regions with abnormal electrical conduction patterns. We address the inverse electro-mechanical relation by using motion in order to infer electrical propagation. For this purpose we define a probabilistic measure of the onset of regional myocardial activation derived from motion fields. The 3D motion fields are obtained using non-rigid registration of tagged MR sequences to track the heart. The myocardium is subdivided in segments and the derived activation isochrones maps compared. We also compare regional motion between two different image acquisitions, thus assisting in diagnosing arrhythmia, in follow up of treatment, and particularly in determining whether the electro-physiological intervention succeeded. We validate our methods using an electro-mechanical model of the heart, synthetic data from a cardiac motion simulator for tagged MRI, a cardiac MRI atlas of motion and geometry, MRI data from 6 healthy volunteers (one of them subjected to stress), and an MRI study on one patient with tachyarrhythmia, before and after RF ablation. Results seem to corroborate that the ablation had the desired effect of regularising cardiac contraction.

IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.

Heart ventricular mechanics has been investigated intensively in the last four decades. The passive material properties, the ventricular geometry and muscular architecture, and the myocardial activation are among the most important determinants of cardiac mechanics. The heart muscle is anisotropic, inhomogeneous, and highly nonlinear. The heart ventricular geometry is irregular and object dependent. The muscular architecture includes the organization of the fiber and the connective tissues. Studies of the myocardial activation have been carried out at both cell and tissue levels. Previous work from our research group has successfully estimated the in-vivo motion and deformation of both the left and the right ventricles. In this paper, we present an iterative model to estimate the in-vivo myocardium material properties, the active forces generated along fiber orientation, and strain and stress distribution in both ventricles. Compared to the strain energy function approach, our model is more intuitively understandable. Using the model, we have simulated the mechanical events of a few different heart diseases. Noticeable strain and stress differences are found between normal and diseased hearts.

A realistic anthropomorphic numerical model of the beating heart is presented. It includes the main cardiac anatomical structures, vessels junctions and part of the coronary network. Its main feature is that it is based on an imaging study on the same human subject from which both structural and motion information are retrieved. This confers to the model a remarkable consistency. Heart’s deformation is assessed through successive 3D non rigid registrations in cine MR sequences. The resulting model can be used for the evaluation of cardiac image processing algorithms such as myocardium segmentation and cardiac image registration.

Many models of the cardiovascular system (e.g. cardiac electrical activity, autonomous nervous system, ...) have been proposed for the last decades. Research is now focusing on the integration of these different models, in order to study more complicated physiopathological states in clinical applications context. To get round the practical limitations of existing models, multi-formalism modelling appears as a way to ease the integration of these different models together.

This paper presents an original methodology allowing to combine different types of description formalisms. This method has been applied to define a multi-formalism model of cardiac action potential propagation on a 2D grid of endocardial cells, combining cellular automata and a set of cells defined by the Beeler-Reuter model. Results, obtained under physiologic and ischemic conditions, highlight the improvements in term of computing compared with mono-formalism systems, while keeping the necessary explanatory strength for a practical clinical use.

The non invasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Tagged cardiac MRI allows the measurement of anatomical and functional myocardial parameters. This protocol generates a dark grid which is deformed with the myocardium displacement on both Short-Axis (SA) and Long-Axis (LA) frames in a time sequence. Tracking the grid allows the estimation of the displacement inside the myocardium. The work described in this paper aims to make the automatic tracking of the grid of tags on cardiac MRI sequences robust and reliable, thanks to an informational formalism based on Extreme Physical Informational (EPI). This approach leads to the development of an original diffusion pre-processing allowing us to increase significantly the robustness of the detection and the follow-up of the grid of tags.