Purpose: Computed tomography (CT) is widely used to assess component rotation in patients with poor results after total knee arthroplasty (TKA). The purpose of this study was to simultaneously determine the accuracy and reliability of CT in measuring TKA component rotation.
Methods: TKA components were implanted in dry-bone models and assigned to two groups. The first group (n = 7) had variable femoral component rotations, and the second group (n = 6) had variable tibial tray rotations. CT images were then used to assess component rotation. Accuracy of CT rotational assessment was determined by mean difference, in degrees, between implanted component rotation and CT-measured rotation. Intraclass correlation coefficient (ICC) was applied to determine intra-observer and inter-observer reliability.
Results: Femoral component accuracy showed a mean difference of 2.5° and the tibial tray a mean difference of 3.2°. There was good intra- and inter-observer reliability for both components, with a femoral ICC of 0.8 and 0.76, and tibial ICC of 0.68 and 0.65, respectively.
Conclusions: CT rotational assessment accuracy can differ from true component rotation by approximately 3° for each component. It does, however, have good inter- and intra-observer reliability.
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http://dx.doi.org/10.1007/s00264-015-2917-1 | DOI Listing |
Foot Ankle Int
January 2025
Division of Foot and Ankle, Department of Orthopaedic Surgery, Duke University School of Medicine, Durham, NC, USA.
Background: Hallux valgus (HV) is a complex, multiplanar deformity. In this study, we examined the interrelationships between various components of this deformity using weightbearing computed tomography (WBCT). We hypothesized that the severity of traditional axial plane deformities would correlate with malpositioning of the metatarsosesamoid complex, first-ray coronal rotational deformity, and malalignment of the hindfoot and midfoot.
View Article and Find Full Text PDFPolymers (Basel)
January 2025
State Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.
Vibration sensors are integral to a multitude of engineering applications, yet the development of low-cost, easily assembled devices remains a formidable challenge. This study presents a highly sensitive flexible vibration sensor, based on the piezoresistive effect, tailored for the detection of high-dynamic-range vibrations and accelerations. The sensor's design incorporates a polylactic acid (PLA) housing with cavities and spherical recesses, a polydimethylsiloxane (PDMS) membrane, and electrodes that are positioned above.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
Department of Mechanical Engineering, École de Technologie Supérieure, 1100 Notre-Dame Ouest, Montreal, QC H3C 1K3, Canada.
Bolted joints, prevalent in industrial applications for component fastening, are susceptible to self-loosening-a critical issue resulting in a gradual reduction in clamping force. Gaining insight into the underlying mechanisms of self-loosening is crucial. While prior research has largely focused on evaluating component stiffness, limited attention has been given to its impact on the self-loosening behavior of bolted joints under transverse cyclic loading.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
Department of Mechanical Engineering (CEME), National University of Sciences and Technology (NUST), Sector H-12, Islamabad 46000, Pakistan.
Welding-induced residual stress has the capacity to significantly compromise the integrity of mechanical components. Its minimization therefore plays a critical role in the selection of process parameters during the welding process. Friction stir welding is a useful joining technique to weld many materials that are not amenable to the traditional welding techniques.
View Article and Find Full Text PDFBeijing Da Xue Xue Bao Yi Xue Ban
February 2025
Center for Digital Dentistry, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digi-tal Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Research Center of Engineering and Technology for Computerized Dentistry, Beijing 100081, China.
Objective: To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data, by utilizing a dynamic graph-based registration network model (maxillofacial dynamic graph registration network, MDGR-Net), and to provide a valuable reference for digital design and analysis in clinical dental applications.
Methods: Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022. Through data augmentation, a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm.
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