Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices al-lowed to develop new therapies for severe cardiac diseases like arrhyth-mias and heart failure. The skills required for such interventions are still very challenging to learn, and typically acquired over several years. Vir-tual reality simulators can reduce this burden by allowing to practice such procedures without consequences on patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, includ-ing pacing and ablation procedures. Our framework involves an efficient GPU-based electrophysiological model. Thanks to an innovative mul-tithreading approach, we reach high computational performances that allow to account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular poten-tial measurements, endocardial surface reconstruction, electrophysiology mapping, radio-frequency (RF) ablation, as well as electrical stimulation. This works is a step towards computerized medical learning curriculum

Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices has allowed the development of new therapies for severe cardiac diseases like arrhythmias and heart failure. The skills required for such interventions are very challenging to learn, and are typically acquired over several years. Virtual reality simulators may reduce this burden by allowing trainees to practice such procedures without risk to patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, including pacing and ablation procedures. Our framework involves the simulation of a catheter navigation that reproduces issues intrinsic to intra-cardiac catheterization, and a graphics processing unit (GPU)-based electrophysiological model. A multi-threading approach is proposed to compute both physical simulations (navigation and electrophysiology) asynchronously. With this method, we reach computational performances that account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular potential measurements, endocardial surface reconstruction, electrophysiol-ogy mapping, radio-frequency (RF) ablation, as well as electrical stimulation. A clinical evaluation assessing the different aspects of the simulation is presented. This works is a step towards computerized medical learning curriculum

Nonlinear effects in finite elements analysis of colorectal surgical clamping

Minimal Invasive Surgery (MIS) is a procedure that has increased its applications in past few years in different types of surgeries. As number of application fields are increasing day by day, new issues have been arising. In particular, instruments must be inserted through a trocar to access the abdominal cavity without capability of direct manipulation of tissues, so a loss of sensitivity occurs. Generally speaking, the student of medicine or junior surgeons need a lot of practice hours before starting any surgical procedure, since they have to difficulty in acquiring specific skills (hand–eye coordination among others) for this type of surgery. Here is what the surgical simulator present a promising training method using an approach based on Finite Element Method (FEM). The use of continuum mechanics, especially Finite Element Analysis (FEA) has gained an extensive application in medical field in order to simulate soft tissues. In particular, colorectal simulations can be used to understand the interaction between colon and the surrounding tissues and also between colon and instruments. Although several works have been introduced considering small displacements, FEA applied to colorectal surgical procedures with large displacements is a topic that asks for more investigations. This work aims to investigate how FEA can describe non-linear effects induced by material properties and different approximating geometries, focusing as test-case application colorectal surgery. More in detail, it shows a comparison between simulations that are performed using both linear and hyperelastic models. These different mechanical behaviours are applied on different geometrical models (planar, cylindrical, 3D-SS and a real model from digital acquisitions 3D-S) with the aim of evaluating the effects of geometric non-linearity. Final aim of the research is to provide a preliminary contribution to the simulation of the interaction between surgical instrument and colon tissues with multi-purpose FEA in order to help the preliminary set-up of different bioengineering tasks like force-contact evaluation or approximated modelling for virtual reality (surgical simulations). In particular, the contribution of this work is focused on the sensitivity analysis of the nonlinearities by FEA in the tissue-tool interaction through an explicit FEA solver. By doing in this way, we aim to demonstrate that the set-up of FEA computational surgical tools may be simplified in order to provide assistance to non-expert FEA engineers or medicians in more precise way of using FEA tools

Real-time simulation of soft tissue deformation for surgical simulation

Surgical simulation plays an important role in the training, planning and evaluation of many surgical procedures. It requires realistic and real-time simulation of soft tissue deformation under interaction with surgical tools. However, it is challenging to satisfy both of these conflicting requirements. On one hand, biological soft tissues are complex in terms of material compositions, structural formations, and mechanical behaviours, resulting in nonlinear deformation characteristics under an external load. Due to the involvement of both material and geometric nonlinearities, the use of nonlinear elasticity causes a highly expensive computational load, leading to the difficulty to achieve the real-time computational performance required by surgical simulation. On the other hand, in order to satisfy the real-time computational requirement, most of the existing methods are mainly based on linear elasticity under the assumptions of small deformation and homogeneity to describe deformation of soft tissues. Such simplifications allow reduced runtime computation; however, they are inadequate for modelling nonlinear material properties such as anisotropy, heterogeneity and large deformation of soft tissues. In general, the two conflicting requirements of surgical simulation raise immense complexity in modelling of soft tissue deformation. This thesis focuses on establishment of new methodologies for modelling of soft tissue deformation for surgical simulation. Due to geometric and material nonlinearities in soft tissue deformation, the existing methods have only limited capabilities in achieving nonlinear soft tissue deformation in real-time. In this thesis, the main focus is devoted to the real-time and realistic modelling of nonlinear soft tissue deformation for surgical simulation. New methodologies, namely new ChainMail algorithms, energy propagation method, and energy balance method, are proposed to address soft tissue deformation. Results demonstrate that the proposed methods can simulate the typical soft tissue mechanical properties, accommodate isotropic and homogeneous, anisotropic and heterogeneous materials, handle incompressibility and viscoelastic behaviours, conserve system energy, and achieve realistic, real-time and stable deformation. In the future, it is projected to extend the proposed methodologies to handle surgical operations, such as cutting, joining and suturing, for topology changes occurred in surgical simulation

Real-time measurement corrected prediction of soft tissue response for medical simulations

Medical simulators, such as in palpation and disease diagnosis, require an efficient model of the biological soft tissue deformation. Hence, a computationally fast and accurate algorithm is required to support and enhance user interactions in near real-time simulations. The visual accuracy of such simulators is dependent on the user¿s reaction time. Static visual images that update at a rate of 25 Hz are perceived as real-time moving images. Hence, visualizing software requires fast algorithms to compute the deformation of soft tissue to facilitate a meaningful simulation. Furthermore, soft tissue behaviour should be modelled accurately while compatible with real-time computation. This work proposes a fast solver for the linearized finite element method (FEM) and validates the proposed algorithm with experimental results. The novelty of the method lies in the utilization of real-time force/displacement measurements that are embedded in the solution via the Kalman filter. A novel computational algorithm that utilizes the strength of the FEM in terms of accuracy and employs direct measurements from the manipulated tissue to overcome the slow computational process of the FEM is proposed in the first part of the thesis. As the behaviour of the mechanically loaded tissue can be regarded as linearly responding at each time step, a constant acceleration temporal discretization method, i.e., the Newmark-ß is employed. In real-time applications, the accuracy of the target variable highly depends on the accuracy of the inputs while differentiating noise from the signal is hardly ever possible. To address this problem, a Kalman filter-based method is developed. The proposed algorithm not only filters the noise from the measurements but also adapts the filter gain to the estimates of the target variable, i.e., the resulting tissue deformation. For a simulated tension test of a cubic model, the proposed algorithm achieves the update frequency of 63.3 Hz. This rate is a significant improvement in computational speed compared to the 5.8 Hz update rate by the classic FEM. Besides, this novel combination of the KF and the FEM makes it possible to expand the displacement estimates in the spatial domain when the measurements are only partially available at certain points. The performance of the above method is validated experimentally through a comparison with indentation tests on artificial human tissue-like material and with the FEM result under identical simulation conditions. The test is repeated on several samples, and the displacement variation from the FEM outcome is considered as the model error. Simulation results show that the proposed method achieves the deformation update frequency of 145.7 Hz compared to the 2.7 Hz from the reference FEM. The proposed method shows the same predictive ability, only 0.47% difference from FEM on average. Experimental validation of the proposed KF-FEM confirms that by consideration of both the measurement noise and the model error, the proposed method is capable of achieving high-frequency response without sacrificing the accuracy. Further to this, the experiments confirmed the linearized model response is reliable within the applied displacement range and therefore proving that KF can be employed. The developed KF-FEM was modified in the next study to address the problem resulting from inaccurate external loads measurements by the force sensors. In the modified version, both the external force, i.e., driving variable, and the displacement, i.e., driven variable, are taken as system states. It is considered that the uncertainty of the model input influences the accuracy of the system estimates. The modified model is calibrated to differentiate the system noise from the input noise. Numerical simulations were conducted on a liver shape geometrical model, and the simulation results demonstrate that more than 90% of the measurement noise is removed. The computational speed is also increased, delivering up to 89 Hz update rate. While the uncertainty of the external load is replicated in the displacements in an FEM solution, the developed algorithm can differentiate the measurement noise, including the displacement and external forces, from the system error, i.e., the FE model error. In the last study, the proposed model was developed to reflect the nonlinear behaviour of the manipulated tissue. The Central Difference time discretization method was used to model large deformations. A novel feature is that the Equation of motion is formulated within the element level rather than in the global spatial domain. This approach helped to improve the computational speed. Indentation with strains of slightly over 10% was simulated to assess the performance of the proposed model. The developed algorithm achieved the 33.85 Hz update frequency on a standard-issue PC and confirmed its suitability for real-time applications. Also, the proposed model achieved estimates with a maximum 5.75% mean absolute error (MAE) concerning the measurements while the classic FEM showed 6.20% MAE under identical simulation condition. Results confirm that deformation estimates for noisy boundary loads of the FEM can be improved with the help of direct measurements and yet be realistic in terms of real-time visual update. This study proposed a novel computational algorithm that achieved update frequencies of higher than 25 Hz to be perceived as real-time in human eyes. The developed KF-FEM model has also shown the potential of improving the FEM accuracy with the help of direct measurements. The proposed algorithm used partially available measurements and expanded its estimates in the spatial domain. The method was experimentally validated, and the model input uncertainty, as well as the nonlinear behaviour of the soft tissue, were assessed and verified