Cinzia Zannoni

Material properties assignment to finite element models of bone structures: a new method

Finite element analysis (FEA) is widely adopted to investigate the mechanical behaviour of bone structures. Computed tomography (CT) data are frequently used to generate FE models of bone. If properly calibrated, CT images are capable of providing accurate information about the bone morphology and tissue density. The aim of this work was to develop a special program able to read a CT data set as well as the FEA mesh generated from it, and to assign to each element of the mesh the material properties derived from the bone tissue density at the element location. The program was tested on phantom data sets and was adopted to evaluate the effects of the discrete description of the bone material properties. A three-dimensional FE model was generated automatically from a 16 bit CT data set of a distal femur acquired in vivo. The strain energy density (SED) was evaluated for each model element for increasing model complexity (number of different material cards assigned to the model). The computed SED were strongly dependent on the material mapping strategy.

Border-tracing algorithm implementation for the femoral geometry reconstruction.

In some orthopaedic applications such as the design of custom-made hip prostheses, reconstruction of the bone morphology is a fundamental step. Different methods are available to extract the geometry of the femoral medullary canal from computed tomography (CT) images. In this research, an automatic procedure (border-tracing method) for the extraction of bone contours was implemented and validated. A composite replica of the human femur was scanned and the CT images processed using three different methods, a manual procedure; the border-tracing algorithm; and a threshold-based method. The resulting contours were used to estimate the accuracy of the implemented procedure. The two software techniques were more accurate than the manual procedure. Then, these two procedures were applied to an in vivo CT data set in order to determine to most critical region for repeatability. Only for the images located in this region, the repeatability measurement was carried out for six in vivo CT data sets to evaluate the inter-femur repeatability. The border-tracing method was found to achieve the highest repeatability.

The multimod application framework: A rapid application development tool for computer aided medicine

This paper describes a new application framework (OpenMAF) for rapid development of multimodal applications in computer-aided medicine. MAF applications are multimodal in data, in representation, and in interaction. The framework supports almost any type of biomedical data, including DICOM datasets, motion-capture recordings, or data from computer simulations (e.g. finite element modeling). The interactive visualization approach (multimodal display) helps the user interpret complex datasets, providing multiple representations of the same data. In addition, the framework allows multimodal interaction by supporting the simultaneous use of different input-output devices like 3D trackers, stereoscopic displays, haptics hardware and speech recognition/synthesis systems. The Framework has been designed to run smoothly even on limited power computers, but it can take advantage of all hardware capabilities. The Framework is based on a collection of portable libraries and it can be compiled on any platform that supports OpenGL, including Windows, MacOS X and any flavor of Unix/linux.

TRI2SOLID: an application of reverse engineering methods to the creation of CAD models of bone segments

For many biomechanical engineering activities it would be useful to have the three dimensional (3D) geometry of bone segments available in form of vectorial models within computer aided design (CAD) environments. In this paper a new method for the semi-automatic conversion of a stack of CT images of a femur into a CAD solid model is described. This method is relatively simple, accurate, and requires only a 3D CAD plus a few additional programs available in the public domain. The proposed method was used to convert the CT scan data set of a human femur into a valid CAD model; the resulting solid was two times more accurate than that obtained using the commonly used procedure based on 2D segmentation.

CT data sets surface extraction for biomechanical modeling of long bones

In modelling applications such as custom-made implants design is useful to have a surface representation of the anatomy of bones rather than the voxel-based representation generated by tomography systems. A voxel-to-surface conversion process is usually done by a 2D segmentation of the images stack. However, other methods allow a direct 3D segmentation of the CT or MRI data set. In the present work, two of these methods, namely the Standard Marching Cube (SMC) and the Discretized Marching Cube (DMC) algorithms, were compared in terms of local accuracy when used to reconstruct the geometry of a human femur. The SMC method was found to be more accurate than the DMC method. The SMC method was capable of reconstructing the inner and outer geometry of a human femur with a peak error lower than 0.9 mm and an average error comparable to the pixel size (0.3 mm). However, the large number of triangles generated by the algorithm may limit its adoption in many modelling applications. The peak error of the DMC algorithm was 1.6 mm but it produced approximately 70% less triangles than the SMC method. From the results of this study, it may be concluded that three dimensional segmentation algorithms are useful not only in visualisation applications but also in the creation of geometry models.

A new method for the automatic mesh generation of bone segments from CT data

A new procedure for the automatic generation of finite element meshes of bone segments from computed tomography (CT) data sets is described. The new method allows a direct automatic generation from the CT data and produces a very accurate unstructured hexahedral mesh. The accuracy of the method was established using the CT images of an artificial femur showing range of attenuation values comparable to those of a human femur. To establish the optimal values for the parameters controlling the mesh a sensitivity analysis was carried out using mesh-conditioning indicators. Some of the best meshes, with increasing levels of refinement, were used to analyse the stresses induced in the proximal femur by single leg stance posture. The accuracy of the meshes was evaluated using an implicit a posteriori residual-based error estimates. The number of elements with stress residuals larger than 10% of the peak stress was 7.8% using the coarsest mesh and only 1.8% with the finest mesh. The proposed method has been proved able to conjugate full automation with high-quality finite element meshes. The stress predictions obtained using these hexahedral-only meshes have been more accurate than those obtained by any other automatic mesh generation algorithm. Once properly integrated in an easy-to-use application, the described method could finally make feasible many clinical applications of finite element analysis.

The Multimod Application Framework

This paper presents the Multimod Application Framework, a software framework for the rapid development of computer-aided medicine applications. This framework, distributed under an open source licence, is being developed as part of the Multimod Project, a multi-national research endeavour partially supported by the European Commission through the Fifth Framework Programme. This application framework provides an effective re-use model for visualisation and data-processing algorithms that may be incorporated into the framework with moderate overhead and then made available to the biomedical research community as part of a complete set of applications.

Analysis of titanium induced CT artifacts in the development of biomechanical finite element models

X-ray computerized tomography (CT) is capable of providing detailed information about the geometry and mineral density of skeletal structures. Such accurate data are of great interest in studying the effects of orthopaedic implants on bone adaptive behaviour in vivo. Metallic implants, however, generate artifacts, typically seen as starburst streaking. These artifacts can degrade the capabilities of CT images to provide accurate information about the geometry and mineral density of bone structures. The aim of this work was to investigate the possibility of developing finite element models (FEM) of the human femur after hip joint arthroplasty using CT images acquired directly after surgery. The capability of modern CT scanners to accurately reconstruct the cross-section geometry of titanium alloy hip joint prosthetic stems was primarily investigated. A new measuring procedure dealing with the geometry of real stems was developed and its accuracy assessed. Secondly, the artifacts generated by a prosthetic stem on the radiological density of the bone were analysed, and their effects on the assessment of FEM material properties were evaluated. Results showed that CT images provide accurate information on metal stem geometry. An average error of 0.45 mm was estimated in the reconstruction of stem cross-section geometry. Concerning bone density estimation around the implant, it was observed that the effect of metal artifacts on tissue density becomes zero at a distance of 2 mm from the implant.

High-resolution 3D scaffold model for engineered tissue fabrication using a rapid prototyping technique.

Rapid prototyping, automatic image processing (computer-aided design (CAD)) and computer-aided manufacturing techniques are opening new and interesting prospects for medical devices and tissue engineering, especially for hard tissues such as bone. The development of a bone high-resolution scaffold prototype using these techniques is described. The results testify to the fidelity existing between microtomographic reconstruction and CAD. Furthermore, stereolithographic manufacturing of this scaffold, which possesses a high degree of similarity to the starting model as monitored by morphological evaluations (mean diameter 569±147 μm), represents a promising result for regenerative medicine applications.

An automated method to position prosthetic components within multiple anatomical spaces

The level of fit and fill of a stem in the host femur is the most critical factor for the mechanical stability and success of the prosthesis. It would be useful to have a simulation tool able to investigate the anatomical compatibility of a new implant in a large library of femoral anatomies in the early phases of the design process. In order to realise this tool, it is necessary to develop an automatic method for the positioning of the stem in a database of anatomies. The aim of this study was to develop and evaluate a method for the automatic positioning of the stem geometry in the anatomical CT dataset. Two different strategies were considered: a completely automatic registration technique and a semi-automatic method based on an anatomical referencing. The two procedures were compared to the manual positioning obtained by an expert surgeon in a set of nine CT datasets. For both methods in each femur the positioning and the orientation of the stem were good. The results showed a better level of fitting for the automatic method, while the shift of the hip joint centre was lower for the anatomical referencing technique. However, the anatomical referencing method requires a higher computational effort without being significantly better than the automatic method. For this reason, the automatic method should be chosen to develop the automatic positioning of a stem in a database of anatomies.