Evaluation of the generality and accuracy of a new mesh morphing procedure for the human femur

Abstract

Various papers described mesh morphing techniques for computational biomechanics, but none of them provided a quantitative assessment of generality, robustness, automation, and accuracy in predicting strains. This study aims to quantitatively evaluate the performance of a novel mesh-morphing algorithm. A mesh-morphing algorithm based on radial-basis functions and on manual selection of corresponding landmarks on template and target was developed. The periosteal geometries of 100 femurs were derived from a computed tomography scan database and used to test the algorithm generality in producing finite element (FE) morphed meshes. A published benchmark, consisting of eight femurs for which in vitro strain measurements and standard FE model strain prediction accuracy were available, was used to assess the accuracy of morphed FE models in predicting strains. Relevant parameters were identified to test the algorithm robustness to operative conditions. Time and effort needed were evaluated to define the algorithm degree of automation. Morphing was successful for 95% of the specimens, with mesh quality indicators comparable to those of standard FE meshes. Accuracy of the morphed meshes in predicting strains was good (R(2)>0.9, RMSE%<10%) and not statistically different from the standard meshes (p-value=0.1083). The algorithm was robust to inter- and intra-operator variability, target geometry refinement (p-value>0.05) and partially to the number of landmark used. Producing a morphed mesh starting from the triangularized geometry of the specimen requires on average 10 min. The proposed method is general, robust, automated, and accurate enough to be used in bone FE modelling from diagnostic data, and prospectively in applications such as statistical shape modelling.

Statistical estimation of femur micro-architecture using optimal shape and density predictors

“…A single mesh template, representing an average shape, was mapped to each bone using a morphing procedure and eight anatomical markers as a reference (Grassi et al, 2011). The obtained meshes consist of n ¼ 70776 second-order tetrahedral elements with a typical edge length of 2 mm.…”

Are spontaneous fractures possible? An example of clinical application for personalised, multiscale neuro-musculo-skeletal modelling

“…The muscle and joint forces predicted by the body-level model were applied to a finite element (FE) model of the right femur of the donor, built from the CT dataset using a validated procedure, described in detail in Grassi et al (2011). CT images were segmented; a template mesh of 10-node tetrahedral isoparametric elements was morphed on the resulting surface.…”

“…The femurs were instrumented with 15 triaxial strain-gages, mainly in the femoral head-neck region, and tested non-destructively (Cristofolini et al, 2009). The strain prediction accuracy of the proposed numerical method in the elastic range is good (determination coefficient (R 2 ) of 95%, Root Mean Squared Error (RMSE) of 7%, maximum error of less than 45%) and is not significantly worsened when using morphing to mesh the FE models (Grassi et al, 2011). In eight femurs that were tested to failure under a loading condition that realistically replicated the fracture patterns for spontaneous fractures of proximal femurs Juszczyk et al, 2011), the failure load was predicted with an average error lower than 15% .…”

European Society of Biomechanics S.M. Perren Award 2014: Safety factor of the proximal femur during gait: A population-based finite element study

“…Personalised FE models were built according to a validated procedure (Grassi et al, 2011). In summary: from the segmented bone surface an iso-topological FE mesh (10-noded tetrahedra, 2 mm average element edge size) was obtained from a single femoral template mesh (307,487 elements) using a morphing procedure Fig.…”