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Abstract Background Developmental dysplasia of the hip (DDH) is a condition in which bone growth irregularities subject articular cartilage to higher mechanical stresses, increase susceptibility to subluxation, and elevate the risk of early osteoarthritis. Study objectives were to calculate three-dimensional cartilage contact stresses and to examine increases of accumulated pressure exposure over a gait cycle that may initiate the osteoarthritic process in the human hip, in the absence of trauma or surgical intervention. Methods Patient-specific, non-linear, contact finite element models, constructed from computed tomography arthrograms using a custom-built meshing program, were subjected to normal gait cycle loads. Results Peak contact pressures for dysplastic and asymptomatic hips ranged from 3.56 – 9.88 MPa. Spatially discriminatory cumulative contact pressures ranged from 2.45 – 6.62 MPa per gait cycle. Chronic over-pressure doses, for 2 million cycles per year over 20 years, ranged from 0.463 – 5.85 MPa-years using a 2-MPa damage threshold. Conclusion There were significant differences between the normal control and the asymptomatic hips, and a trend towards significance between the asymptomatic and symptomatic hips of patients afflicted with developmental dysplasia of the hip. The magnitudes of peak cumulative contact pressure differed between apposed articular surfaces. Bone irregularities caused localized pressure elevations and an upward trend between chronic over-pressure exposure and increasing Severin classification.

Musculoskeletal finite element analysis (FEA) has been essential to research in orthopaedic biomechanics. The generation of a volumetric mesh is often the most challenging step in a FEA. Hexahedral meshing tools that are based on a multi-block approach rely on the manual placement of building blocks for their mesh generation scheme. We hypothesise that Gaussian curvature analysis could be used to automatically develop a building block structure for multi-block hexahedral mesh generation. The Automated Building Block Algorithm incorporates principles from differential geometry, combinatorics, statistical analysis and computer science to automatically generate a building block structure to represent a given surface without prior information. We have applied this algorithm to 29 bones of varying geometries and successfully generated a usable mesh in all cases. This work represents a significant advancement in automating the definition of building blocks. [ABSTRACT FROM PUBLISHER]

Computational models of joint anatomy and function provide a means for biomechanists, physicians, and physical therapists to understand the effects of repetitive motion, acute injury, and degenerative diseases. Finite element models, for example, may be used to predict the outcome of a surgical intervention or to improve the design of prosthetic implants. Countless models have been developed over the years to address a myriad of orthopaedic procedures. Unfortunately, few studies have incorporated patientspecific models. Historically, baseline anatomic models have been used due to the demands associated with model development. Moreover, surgical simulations impose additional modeling challenges. Current meshing practices do not readily accommodate the inclusion of implants. Our goal is to develop a suite of tools (virtual instruments and guides) which enable surgical procedures to be readily simulated and to facilitate the development of all-hexahedral finite element mesh definitions. [ABSTRACT FROM AUTHOR]

Musculoskeletal finite element (FE) analysis is an invaluable tool in orthopaedic research. Unfortunately, the demands that accompany anatomic mesh development often limit its utility. To ease the burden of mesh development and to address the need for subject-specific analysis, we developed IA-FEMesh, a user-friendly toolkit for generating hexahedral FE models. This study compared our multiblock meshing technique to widely accepted meshing methods. Herein, the meshes under consideration consisted of the phalanx bones of the index finger. Both accuracy and validity of the models were addressed. Generating a hexahedral mesh using IA-FEMesh was found to be comparable to automated tetrahedral mesh generation in terms of preprocessing time. A convergence study suggested that the optimal number of hexahedral elements needed to mesh the distal, middle, and proximal phalanx bones were 3402, 4950, and 4550 respectively. Moreover, experimental studies were used to validate the mesh definitions. The contact areas predicted by the models compared favorably with the experimental findings (percent error < 13.2%). With the accuracy and validity of the models confirmed, accompanied by the relative ease with which the models can be generated, we believe IA-FEMesh holds the potential to contribute to multi-subject analyses, which are pertinent for clinical studies.