Pierre-Frédéric Villard

Simulation of lung behaviour with finite elements: influence of bio-mechanical parameters

Motivated by medical needs, we propose to simulate lung deformation and motion during respiration to track tumours. This paper presents a model of lung behaviour based on a continuous media mechanics model and solved with a finite element method. The result is a simulation of a normal breathing, matching with patient customised data. Moreover, we carried out numerical experiments to evaluate our algorithms and to measure the influence and the relevance of mechanical parameters.

A Comparison Framework for Breathing Motion Estimation Methods From 4-D Imaging

Motion estimation is an important issue in radiation therapy of moving organs. In particular, motion estimates from 4-D imaging can be used to compute the distribution of an absorbed dose during the therapeutic irradiation. We propose a strategy and criteria incorporating spatiotemporal information to evaluate the accuracy of model-based methods capturing breathing motion from 4-D CT images. This evaluation relies on the identification and tracking of landmarks on the 4-D CT images by medical experts. Three different experts selected more than 500 landmarks within 4-D CT images of lungs for three patients. Landmark tracking was performed at four instants of the expiration phase. Two metrics are proposed to evaluate the tracking performance of motion-estimation models. The first metric cumulates over the four instants the errors on landmark location. The second metric integrates the error over a time interval according to an a priori breathing model for the landmark spatiotemporal trajectory. This latter metric better takes into account the dynamics of the motion. A second aim of this paper is to estimate the impact of considering several phases of the respiratory cycle as compared to using only the extreme phases (end-inspiration and end-expiration). The accuracy of three motion estimation models (two image registration-based methods and a biomechanical method) is compared through the proposed metrics and statistical tools. This paper points out the interest of taking into account more frames for reliably tracking the respiratory motion.

Tuning of Patient-Specific Deformable Models Using an Adaptive Evolutionary Optimization Strategy

We present and analyze the behavior of an evolutionary algorithm designed to estimate the parameters of a complex organ behavior model. The model is adaptable to account for patients specificities. The aim is to finely tune the model to be accurately adapted to various real patient datasets. It can then be embedded, for example, in high fidelity simulations of the human physiology. We present here an application focused on respiration modeling. The algorithm is automatic and adaptive. A compound fitness function has been designed to take into account for various quantities that have to be minimized. The algorithm efficiency is experimentally analyzed on several real test cases: 1) three patient datasets have been acquired with the “breath hold” protocol, and 2) two datasets corresponds to 4-D CT scans. Its performance is compared with two traditional methods (downhill simplex and conjugate gradient descent): a random search and a basic real-valued genetic algorithm. The results show that our evolutionary scheme provides more significantly stable and accurate results.

A prototype percutaneous transhepatic cholangiography training simulator with real-time breathing motion

PurposeWe present here a simulator for interventional radiology focusing on percutaneous transhepatic cholangiography (PTC). This procedure consists of inserting a needle into the biliary tree using fluoroscopy for guidance.MethodsThe requirements of the simulator have been driven by a task analysis. The three main components have been identified: the respiration, the real-time X-ray display (fluoroscopy) and the haptic rendering (sense of touch). The framework for modelling the respiratory motion is based on kinematics laws and on the Chainmail algorithm. The fluoroscopic simulation is performed on the graphic card and makes use of the Beer-Lambert law to compute the X-ray attenuation. Finally, the haptic rendering is integrated to the virtual environment and takes into account the soft-tissue reaction force feedback and maintenance of the initial direction of the needle during the insertion.ResultsFive training scenarios have been created using patient-specific data. Each of these provides the user with variable breathing behaviour, fluoroscopic display tuneable to any device parameters and needle force feedback.ConclusionsA detailed task analysis has been used to design and build the PTC simulator described in this paper. The simulator includes real-time respiratory motion with two independent parameters (rib kinematics and diaphragm action), on-line fluoroscopy implemented on the Graphics Processing Unit and haptic feedback to feel the soft-tissue behaviour of the organs during the needle insertion.

Virtual reality, ultrasound-guided liver biopsy simulator: Development and performance discrimination

OBJECTIVES The aim of this article was to identify and prospectively investigate simulated ultrasound-guided targeted liver biopsy performance metrics as differentiators between levels of expertise in interventional radiology. METHODS Task analysis produced detailed procedural step documentation allowing identification of critical procedure steps and performance metrics for use in a virtual reality ultrasound-guided targeted liver biopsy procedure. Consultant (n=14; male=11, female=3) and trainee (n=26; male=19, female=7) scores on the performance metrics were compared. Ethical approval was granted by the Liverpool Research Ethics Committee (UK). Independent t-tests and analysis of variance (ANOVA) investigated differences between groups. RESULTS Independent t-tests revealed significant differences between trainees and consultants on three performance metrics: targeting, p=0.018, t=-2.487 (-2.040 to -0.207); probe usage time, p = 0.040, t=2.132 (11.064 to 427.983); mean needle length in beam, p=0.029, t=-2.272 (-0.028 to -0.002). ANOVA reported significant differences across years of experience (0-1, 1-2, 3+ years) on seven performance metrics: no-go area touched, p=0.012; targeting, p=0.025; length of session, p=0.024; probe usage time, p=0.025; total needle distance moved, p=0.038; number of skin contacts, p<0.001; total time in no-go area, p=0.008. More experienced participants consistently received better performance scores on all 19 performance metrics. CONCLUSION It is possible to measure and monitor performance using simulation, with performance metrics providing feedback on skill level and differentiating levels of expertise. However, a transfer of training study is required.

Lung mesh generation to simulate breathing motion with a finite element method

Numerical modelling of lung behaviour during the respiration cycle is a difficult challenge due to its complex geometry and surrounding environment constraints. This paper presents an approach to simulate a patients lung motion during inhaling and exhaling based on a continuous media mechanics model and solved with a finite element method. One of the key problems is an adequate lung mesh generation, which is specifically developed in this paper.

Breathing Thorax Simulation based on Pleura Physiology and Rib Kinematics

To monitor a lung mechanical model and then predict tumour motion we proposed a approach based on the pleura physiology. By comparing the predictions to landmarks set by medical experts, we observed better results with regards to the one obtained with approaches found in the literature. Beside, we focus on the rib cage kinematics, which play a significant role in the pleura outer-surface motion and therefore in the lung motion. We proposed a kinematic model of the rib cage based on the finite helical axis method and we show out interesting results.

Virtual Reality Simulation of Liver Biopsy with a Respiratory Component

The field of computer-based simulators has grown exponentially in the last few decades, especially in Medicine. Advantages of medical simulators include: (1) provision of a platform where trainees can practice procedures without risk of harm to patients; (2) anatomical fidelity; (3) the ability to train in an environment wherein physiological behaviour is observed, something that is not permitted where in-vitro phantoms are used; (4) flexibility regarding anatomical and pathological variation of test cases that is valuable in the acquisition of experience; (5) quantification of metrics relating to task performance that can be used to monitor trainee performance throughout the learning curve; and (6) cost effectiveness. In this chapter, we will focus on the current state of the art of medical simulators, the relevant parameters required to design a medical simulator, the basic framework of the simulator, methods to produce a computer-based model of patient respiration and finally a description of a simulator for ultrasound guided for liver biopsy. The model that is discussed presents a framework that accurately simulates respiratory motion, allowing for the fine tuning of relevant parameters in order to produce a patient-specific breathing pattern that can then be incorporated into a simulation with real-rime haptic interaction. Thus work was conducted as part CRaIVE collaboration [1], whose aim is to develop simulators specific to interventional radiology.

A Chest Wall Model Based on Rib Kinematics

The success of radiotherapy treatment could be compromised by motion. Lung tumours are particularly concerned by this problem because their positions are subject to breathing motion. To reduce the uncertainty on the position of pulmonary tumours during breathing cycle, we propose to develop a complete thoracic biomechanical model. This model will be monitored through the measurement of external parameters (thorax outer-surface motion, air flow...) and should predict in real-time the location of lung tumour. In this paper, we expose a biomechanical model of the lung environment, based on anatomical and physiological knowledge. The model includes the skin, the ribs, the pleura and the soft tissue between the skin and the ribcage. Motions and deformations are computed with the Finite Element Method. The ribcage direct kinematics model, permits to compute the skin position from the ribs motion. Conversely, the inverse kinematics provides rib motion and consequently lung motion. It can be computed from the outer-surface motion.With regards to available clinical data the results are promising. In particular, the average error is lower than the resolution of the CT-scan images used as input data.

Towards accurate tumour tracking in lungs

Motivated by radiotherapy and hadrontherapy improvement, we consider in a first step the potential of a simple elastic mechanical modelling to simulate lung deformations and motions during respiration, towards tumour tracking. Two approaches are presented: one is the finite-element based method and the other is the mass-spring system. For these approaches, we suggest a personalisation based on the measurement of physical and geometrical data for each patient.