Short stems have been developed for some years for preservation of femoral bone stock and achieve physiological proximal loading. Shortening stem length is a merit for bone stock preservation. However, it might lead to reduction of primary stability. We investigated relationship between stem length and primary stability by patient specific finite element analysis (FEA). Thirty-one hips in 31 patients were performed total hip arthroplasty with standard length tapered wedge-shaped (TW) cementless stem (CTi-II: Corin, Cirencester, UK). There were 6 males and 25 females. The average age at operation was 69 years old. The average body mass index was 23.9 kg/m2. Primary diagnoses were secondary osteoarthritis due to developmental dysplasia of the hip in 29 hips. Femoral canal shapes were normal in 21, stovepipe in 6 and champagne-flute in 4 hips. Bone qualities were type A in 6, B in 19 and C in 6 hips. The patients underwent computed tomography (CT) preoperatively and postoperatively. We constructed preoperative three dimensional (3D) femur surface models from preoperative CT data with individual bone mineral density (BMD) mapping. The postoperative 3D femur and rough stem surface models were obtained from postoperative CT data. The coordinates of the postoperative femur were transformed to fit the preoperative femur model. A precise stem model constructed using computer-assisted design data was matched to the transformed rough stem model using the iterative closest point algorithm. We obtained a patient-specific model with the proximal bone geometry, allocation of BMD and stem alignment. We estimated the average of axial and rotational micromotion (MM) at stem-bone interface and the ratio of area (MM � 40 micrometers) on the porous surface in order to analyze primary stability of TW stem with several lengths (standard (100 %), 75 %, 50 %, 40 % and 30 % length).Introduction
Materials and Methods
To achieve 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques, which use X-ray fluoroscopic images and computer-aided design model of the knee implants, have been applied to clinical cases. In previous feature-based registration methods, only edge contours originated from knee implants are assumed to be extracted from X-ray images before 2D/3D registration. Due to the influence of bone and bone-cement close to knee implants, however, edge detection methods extract unwanted spurious edges and noises in clinical images. Thus, time-consuming and labor-intensive manual operations are often necessary to remove the unwanted edges. It has been a serious problem for clinical applications, and there is a strong demand for development of improved method. The purpose of this study was to develop a pose estimation method to perform accurate 2D/3D registration even if spurious edges and noises exist in knee images. Our 2D/3D registration technique is based on a feature-based algorithm, and contour points from X-ray images are extracted by Gaussian Laplacian filter and zero crossing methods. The basic principle of the algorithm is that the 3D pose of a model can be determined by projecting rays from contour points in an image back to the X-ray focus and noting that all of these rays are tangential to the model surface. Therefore, 3D poses are estimated by minimizing the sum of Euclidean distances between all projected rays and the model surface. Additionally, we introduce robust statistics into the 3D pose estimation method to perform accurate 2D/3D registration even if spurious edges and noises exist in knee images. The robust estimation method employs weight functions to reduce the influence of spurious edges and noises. The weight functions are defined for each contour point, and optimization is performed after the weight functions are multiplied to a cost function.Purpose
Methods
