In severe cases of total knee arthroplasty which cannot be treated with off-the-shelf implants anymore custom-made knee implants may serve as one of the few remaining options to restore joint function or to prevent limb amputation. Custom-made implants are specifically designed and manufactured for one individual patient in a single-unit production, in which the surgeon is responsible for the implant design characteristics in consultation with the corresponding engineer. The mechanical performance of these custom-made implants is challenging to evaluate due to the unique design characteristics and the limited time until which the implant is needed. Nevertheless, the custom-made implant must comply with clinical and regulatory requirements. The design of custom-made implants is often based on a underlying reference implant with available biomechanical test results and well-known clinical performance. To support surgeons and engineers in their decision whether a specific implant design is suitable, a method is proposed to evaluate its mechanical performance. The method uses finite element analysis (FEA) and comprises six steps: (1) Identification of the main potential failure mechanism and its corresponding FEA quantity of interest. (2) Reproduction of the biomechanical test of the reference implant via FEA. (3) Identification of the maximum value of the corresponding FEA quantity of interest at the required load level. (4) Definition of this value as the acceptance criteria for the FEA of the custom-made implant. (5) Reproduction of the biomechanical test with the custom-made implant via FEA. (6) Conclusion whether the acceptance criteria is fulfilled or not. The method was applied to two exemplary cases of custom-made knee implants. The FEA acceptance criteria derived from the reference implants were fulfilled in both custom-made implants. Subsequent biomechanical tests verified the FEA results. This study suggests and applies a non-destructive and efficient method for pre-clinical testing of a single-unit custom-made knee implant to evaluate whether the design is mechanically suitable.
Primary stability is an important factor for long-term implant survival in total hip arthroplasty. In revision surgery, implant fixation becomes especially challenging due the acetabular bone defects, which are often present. Previous studies on primary stability of revision components often applied simplified geometrical defect shapes in a variety of sizes and locations. The objectives of this study were to (1) develop a realistic defect model in terms of defect volume and shape based on a clinically existing acetabular bone defect, (2) develop a surrogate acetabular test model, and (3) exemplarily apply the developed approach by testing the primary stability of a pressfit-cup with and without bone graft substitute (BGS). Based on clinical computed tomography data and a method previously published [1], volume and shape information of a representative defect, chosen in consultation with four senior hip revision surgeons, was derived. Volume and shape of the representative defect was approximated by nine reaming procedures with hemispherical acetabular reamers, resulting in a simplified defect with comparable volume (18.9 ml original vs. 18.8 ml simplified) and shape. From this simplified defect (Introduction
Materials & Methods
Revision total hip arthroplasty is often associated with acetabular bone defects. In most cases, assessment of such defects is still qualitative and biased by subjective interpretations. Three-dimensional imaging techniques and novel anatomical reconstructions using statistical shape models (SSM) allow a more impartial and quantitative assessment of acetabular bone defects [1]. The objectives of this study are to define five clinically relevant parameters and to assess 50 acetabular bone defects in a quantitative way. Anonymized CT-data of 50 hemi-pelvises with acetabular bone defects were included in the study. The assessment was based on solid models of the defect pelvis (i.e. pelvis with bone defect) and its anatomical reconstruction (i.e. native pelvis without bone defect) (Fig.1A). Five clinically relevant parameters were defined: (1) Bone loss, defined by subtracting defect pelvis from native pelvis. (2) Bone formation, defined by subtracting native pelvis from defect pelvis. Bone formation represents bone structures, which were not present in the native pelvis (e.g. caused by remodeling processes around a migrated implant). (3) Ovality, defined by the length to width ratio of an ellipse fitted in the defect acetabulum. A ratio of 1.0 would represent a circular acetabulum. (4) Lateral center-edge angle (LCE angle), defined by the angle between the most lateral edge of the cranial roof and the body Z-axis, and (5) implant migration, defined by the distance between center of rotation (CoR) of the existing implant and CoR of native pelvis (Fig. 1B).Introduction
Methods
Acetabular bone defects are still challenging to quantify. Numerous classification schemes have been proposed to categorize the diverse kinds of defects. However, these classification schemes are mainly descriptive and hence it remains difficult to apply them in pre-clinical testing, implant development and pre-operative planning. By reconstructing the native situation of a defect pelvis using a Statistical Shape Model (SSM), a more quantitative analysis of the bone defects could be performed. The aim of this study is to develop such a SSM and to validate its accuracy using relevant clinical scenarios and parameters. An SSM was built on the basis of segmented 66 CT dataset of the pelvis showing no orthopedic pathology. By adjusting the SSM's so called The validity of the SSM was tested by a Leave-one-out study, whereby one pelvis at a time was removed from the 66 pelvises and was reconstructed using a SSM of the remaining 65 pelvises. The reconstruction accuracy was assessed by comparing each original pelvis with its reconstruction based on the root-mean-square (RMS) surface error and five clinical parameters (center of rotation, acetabulum diameter, inclination, anteversion, and volume). The influence of six different numbers of shape variation modes (reflecting the degrees of freedom of the SSM) and four different mask sizes (reflecting different clinical scenarios) was analyzed.Introduction
Methods
