Tumor motion during irradiation reduces target coverage and increases dose to healthy tissues. Prediction of respiratory motion has the potential to substantially improve cancer radiation therapy. The respiratory motion is complex and its prediction is not a simple task, especially that breathing is controlled by the independent action of the diaphragm muscles and thorax. The diaphragm is the principal muscle used in the process of respiration and its modeling is essential for assessing the respiratory motion. In this context, an accurate patient-specific Finite Element (FE) based biomechanical model can be used to predict diaphragm deformation. In this paper, we have developed a FE model of the respiratory system including the diaphragm behavior and the complete thorax with musculoskeletal structure. These incorporate the ribs kinematics extracted directly from the Computed Tomography (CT) scan images. In order to demonstrate the effectiveness of our biomechanical model, a qualitative and quantitative comparison between the FE simulations and the CT scan images were performed. Upon application of linear elastic models, our results show that a linear elastic model can accurately predict diaphragm deformations. These comparisons demonstrate the effectiveness of the proposed physically-based model. The developed computational model could be a valuable tool for respiratory system deformation prediction in order to be controlled and monitored by external sensors during the treatment.

In a collaborative design environment, various software tools are utilized to enhance the product development. This entails a meaningful representation and exchange of product data semantics across these different systems. Semantic interoperability of product information refers to enabling the exchange of design intelligence, including construction history, parameters, features, and constraints. This is a crucial difference compared to current standards such as STEP that deliver "dumb" geometry, where no design intent is associated. To enable semantics data exchange, we propose an ontology-based approach, consisting in developing a "Common Design Features Ontology", called CDFO. Interoperability among ontologies is fulfilled by defining several mapping rules. We use a descriptive logic-based language, notably OWL DL to represent formally our ontology.

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 patient's 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.

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.

We describe an automatic surface reconstruction technique from a set of planar data points organised in parallel sections. The reconstruction employs skeletal implicit surfaces. Two key points in this study are: calculation of the 3D skeleton by establishing a correspondence between each paid of the 2D Voronoi skeleton of two neighbouring sections; and the use of a uniform field function necessitating the introduction of the notion of "weighted skeleton". Another key point of this work is the proposition of an animation methodology by transforming the skeleton into a deformable mass/spring system. This work has been used in the context of a medical project to simulate the dynamic behaviour of organs during the conformal radiotherapy treatment.

We describe a general methodology for reconstruction and animation of volumetric deformable objects. In the scope of a medical application, we want to simulate the motion and the form alteration of the internal anatomical organs. Multi-layer particle systems are well adapted to represent the geometry. However, several problems occur related to the structure of our model and the nature of internal forces. For this, we have introduced the necessary tools to overcome these problems and to handle the dynamic and deformable behavior of cancerous tissues and organs. Our particle system seems to be suitable to be integrated in radiation dose evaluation software, developed within the European BIOMED2-ARROW project by North Western Medical Physics team, in Manchester.

In this paper a new method, using the skeleton-based implicit model, is introduced for shape reconstruction of objects from a set of data points organized in planar sections. To reduce complexity and computation time, the objects are described by a uniform field function and a "3D weighted skeleton". The 3D skeleton is composed of planar elements and is deduced from the 2D Voronoi skeleton of each section. The weights are distances creating a non uniform offset of the skeleton.

Abstract In this paper, we propose a method of complex curves description, based on the use of standard primitives (curve arcs), inscribed in including boxes. This method simplifies the creation steps (curves are not defined with the help of control points), and the manipulation steps (using including boxes). This study constitutes an extension to our descriptive universal language, named “G”, which is used in a general desig n environment, permitting the integration of various models (solids1, polyhedrons2, surfaces3 and fractals), in order to offer the adequate tools adapted to the problems to be solved, in a unique modeller.