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

• Published in: Medical engineering & physics Vol. 33; no. 1; pp. 112 - 120
• Main Authors: Grassi, Lorenzo, Hraiech, Najah, Schileo, Enrico, Ansaloni, Mauro, Rochette, Michel, Viceconti, Marco
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.01.2011; Elsevier
• Subjects: Algorithms; Biological and medical sciences; Biomechanical Phenomena; Biomechanics. Biorheology; Bone biomechanics; Computer Graphics; Databases, Factual; Femur; Femur - anatomy & histology; Femur - diagnostic imaging; Finite Element Analysis; Fundamental and applied biological sciences. Psychology; Humans; Mesh morphing; Models, Anatomic; Radial basis function; Radiology; Reproducibility of Results; Skeleton and joints; Stress, Mechanical; Subject-specific finite element model; Tissues, organs and organisms biophysics; Tomography, X-Ray Computed; Vertebrates: osteoarticular system, musculoskeletal system; Radial basis function; Femur; Mesh morphing; Bone biomechanics; Subject-specific finite element model; Human; Algorithm; Modeling; Osteoarticular system; Biomechanics; Finite element method; Bone; Mesh method; Biomedical engineering
• ISSN: 1350-4533; 1873-4030; 1873-4030
• DOI: 10.1016/j.medengphy.2010.09.014

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.