title: To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations?
abstract: Proximal femur strength estimates from computed tomography (CT)-based finite element (FE) models are finding clinical application. Published models reached a high in-vitro accuracy, yet many of them rely on nonlinear methodologies or internal best-fitting of parameters. The aim of the present study is to verify to what extent a linear FE modelling procedure, fully based on independently determined parameters, can predict the failure characteristics of the proximal femur in stance and sideways fall loading configurations. Fourteen fresh-frozen cadaver femora were CT-scanned. Seven femora were tested to failure in stance loading conditions, and seven in fall. Fracture was monitored with high-speed videos. Linear FE models were built from CT images according to a procedure already validated in the prediction of strains. An asymmetric maximum principal strain criterion (0.73% tensile, 1.04% compressive limit) was used to define a node-based risk factor (RF). FE-predicted failure load, mode (tensile/compressive) and location were determined from the first node reaching RF=1. FE-predicted and measured failure loads were highly correlated (R(2)=0.89, SEE=814N). In all specimens, FE models correctly identified the failure mode (tensile in stance, compressive in fall) and the femoral region where fracture started (supero-lateral neck aspect). The location of failure onset was accurately predicted in eight specimens. In summary, a simple FE model, adaptable in the future to multiple loads (e.g. including muscles), was highly correlated with experimental failure in two loading conditions on specimens ranging from normal to osteoporotic. Thus, it can be suitable for use in clinical studies.
authors.affiliation: Laboratorio di Bioingegneria Computazionale, Istituto Ortopedico Rizzoli, Via di Barbiano, 1/10, 40136 Bologna, Italy. Electronic address: schileo@tecno.ior.it.
authors.forename: Enrico
authors.initials: E
authors.lastname: Schileo
authors.affiliation: Laboratorio di Tecnologia Medica, Istituto Ortopedico Rizzoli, Bologna, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Balistreri
authors.affiliation: Laboratorio di Tecnologia Medica, Istituto Ortopedico Rizzoli, Bologna, Italy.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Grassi
authors.affiliation: Department of Industrial Engineering, University of Bologna, Bologna, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Cristofolini
authors.affiliation: Laboratorio di Tecnologia Medica, Istituto Ortopedico Rizzoli, Bologna, Italy.
authors.forename: Fulvia
authors.initials: F
authors.lastname: Taddei
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001696:Biomechanical Phenomena / Q000502:physiology; D002102:Cadaver; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging / Q000502:physiology*; D020342:Finite Element Analysis; D050723:Fractures, Bone / Q000000981:diagnostic imaging / Q000209:etiology / Q000503:physiopathology; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011187:Posture / Q000502:physiology*; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods; D016474:Weight-Bearing / Q000502:physiology*
keywords: Bone biomechanics; Computed tomography; Proximal femur; Subject-specific finite element models; Validation