2 research outputs found
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Finite element analysis of sagittal angles of unicompartmental knee arthroplasty
BackgroundUnicompartmental knee arthroplasty is an effective treatment for knee osteoarthritis, but it has the risk of failure, and the installation position of the prosthesis is one of the factors affecting the failure. There are few biomechanical studies on the installation angle of unicompartmental knee prosthesis.MethodsConstructed a finite element model of a normal human knee joint, and the validity of the model was verified by stress and front anterior methods. The mobile-bearing unicompartmental knee arthroplasty femoral prosthesis was placed at 3° intervals from 0° sagittal plane to 15° flexion, and − 2° and 17°were established, and observing the biomechanical changes of components.FindingsMaximum peak stresses occurred at a sagittal mounting angle of −2° for the insert and the contralateral meniscus, with the tibia showing a maximum at 17° sagittal and the tibial prosthesis stress maximum occurring at 6° sagittal. As the sagittal plane angle of the femoral prosthesis increases and the osteotomy distance extends posteriorly, more bone is amputated during the osteotomy. The ratio of the distance from the tip of the anterior intramedullary nail to the anterior end of the osteotomy to the total anteroposterior length of the sagittal osteotomy ranged from 43.2% to 44.6%.InterpretationIn this paper, the more appropriate sagittal mounting position for the femoral prosthesis is between 9 and 12°, based on the amount of osteotomy and the peak stress of each component in a standing position.</p
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Dual output feature fusion networks for femoral segmentation and quantitative analysis of the knee joint
BackgroundMagnetic resonance imaging (MRI) is the preferred imaging modality for diagnosing knee disease. Segmentation of the knee MRI images is essential for subsequent quantification of clinical parameters and treatment planning for knee prosthesis replacement. However, the segmentation remains difficult due to individual differences in anatomy, the difficulty of obtaining accurate edges at lower resolutions, and the presence of speckle noise and artifacts in the images. In addition, radiologists must manually measure the knee's parameters which is a laborious and time-consuming process.PurposeAutomatic quantification of femoral morphological parameters can be of fundamental help in the design of prosthetic implants for the repair of the knee and the femur. Knowledge of knee femoral parameters can provide a basis for femoral repair of the knee, the design of fixation materials for femoral prostheses, and the replacement of prostheses.MethodsThis paper proposes a new deep network architecture to comprehensively address these challenges. A dual output model structure is proposed, with a high and low layer fusion extraction feature module designed to extract rich features through the cross-fusion mechanism. A multi-scale edge information extraction spatial feature module is also developed to address the boundary-blurring problem.ResultsBased on the precise automated segmentation results, 10 key clinical parameters were automatically measured for a knee femoral prosthesis replacement program. The correlation coefficients of the quantitative results of these parameters compared to manual results all achieved at least 0.92. The proposed method was extensively evaluated with MRIs of 78 patients’ knees, and it consistently outperformed other methods used for segmentation.ConclusionsThe automated quantization process produced comparable measurements to those manually obtained by radiologists. This paper demonstrates the viability of automatic knee MRI image segmentation and quantitative analysis with the proposed method. This provides data to support the accuracy of assessing the progression and biomechanical changes of osteoarthritis of the knee using an automated process, thus saving valuable time for the radiologists and surgeons.</p