RESUMEN
The risk of aseptic loosening in cementless hip stems can be reduced by improving osseointegration with osteoinductive coatings favoring long-term implant stability. Osseointegration is usually evaluated in vivo studies, which, however, do not reproduce the mechanically driven adaptation process. This study aims to develop an in silico model to predict implant osseointegration and the effect of induced micromotion on long-term stability, including a calibration of the material osteoinductivity with conventional in vivo studies. A Finite Element model of the tibia implanted with pins was generated, exploiting bone-to-implant contact measures of cylindrical titanium alloys implanted in rabbits' tibiae. The evolution of the contact status between bone and implant was modeled using a finite state machine, which updated the contact state at each iteration based on relative micromotion, shear and tensile stresses, and bone-to-implant distance. The model was calibrated with in vivo data by identifying the maximum bridgeable gap. Afterward, a push-out test was simulated to predict the axial load that caused the macroscopic mobilization of the pin. The bone-implant bridgeable gap ranged between 50 µm and 80 µm. Predicted push-out strength ranged from 19 N to 21 N (5.4 MPa-3.4 MPa) depending on final bone-to-implant contact. Push-out strength agrees with experimental measurements from a previous animal study (4 ± 1 MPa), carried out using the same implant material, coated, or uncoated. This method can partially replace in vivo studies and predict the long-term stability of cementless hip stems.
RESUMEN
Little is known about dynamic changes of femoral anatomy after total hip arthroplasty (THA), in particular about sagittal femoral bowing (SFB). A 3D CT study was designed to evaluate the chronological changes of SFB after cementless femoral stem implantation for primary THA. Ten patients who underwent unilateral primary THA with a cementless femoral stem, with 2 consecutive CT scans (extending from the fourth lumbar vertebra to the tibial plateaus), performed before THA and at least 3 years after THA, were enrolled. The 3D models of femurs were created using image segmentation software. Using the two CT scans, SFB values of the proximal and middle thirds were calculated on the replaced and untreated sides by two different observers. Eight anatomical stems and two conical stems were involved. The post-operative CT was performed at an average follow-up of 6.5 years after THA (range: 3-12.5). The measurements performed by the two observers did not differ in the proximal and middle regions. A significant difference between the pre-operative and post-operative SFB compared to the untreated side was found in the proximal femur segment (p = 0.004). Use of a cementless stem in THA induced chronological changes in SFB of the proximal femur, after a minimum timespan of 3 years.
RESUMEN
BACKGROUND AND OBJECTIVE: When a computational model aims to be adopted beyond research purposes, e.g. to inform a clinical or regulatory decision, trust must be placed in its predictive accuracy. This practically translates into the need to demonstrate its credibility. In fact, prior to its adoption for regulatory purposes, an in silico methodology should be proven credible enough for the scope. This has become especially relevant as, although evidence of the safety and efficacy of new medical products or interventions has been traditionally provided to the regulator experimentally, i.e., in vivo or ex vivo, recently the idea to inform a regulatory decision in silico has made its way in the regulatory scenario. While a harmonised technical standard is currently missing in the EU regulatory system, in 2018 the ASME issued V&V40-2018, where a risk-based framework to assess the credibility of a computational model through the performance of predefined credibility activities is provided. The credibility framework is here applied to Bologna Biomechanical Computed Tomography (BBCT) solution, which predicts the absolute risk of fracture at the femur for a subject. BBCT has recently been the object of a qualification advice request to the European Medicine Agency. METHODS: The full implementation of ASME V&V40-2018 framework on BBCT is shown. Starting from BBCT proposed context of use the whole credibility plan is presented and the credibility activities (Verification, Validation, Applicability) described together with the achieved credibility levels. RESULTS: BBCT risk is judged medium, and the credibility levels achieved considered acceptable. The uncertainties intrinsically present in the material properties assignment affected BBCT predictions to the highest extent. CONCLUSIONS: This work provides the practical application of the ASME V&V40-2018 risk-based credibility assessment framework, which could be applied to demonstrate model credibility in any field and support future regulatory submissions and foster the adoption of In Silico Trials.