3D Printed polyether-ether-ketone (PEEK) has gained widespread use in clinical practice due to its excellent biocompatibility, biomechanical compatibility, and personalization. However, pre-printed PEEK implants are not without their flaws, including bioinert, optimization distortion of 3D printing digital model and prosthetic mismatching. Recent advancements in mechanical processing technology have made it possible to print bone implants with PEEK fused deposition, allowing for the construction of mechanically adaptable implants. In this study, we aimed to synthesize silanized polycitrate (PCS) via thermal polymerization and in situ graft it to PEEK surface to construct an elastomer coating for 3D printed PEEK implants (PEEK-PCS). This incorporation of PCS allows the implant to exhibit adaptive space filling ability and stress dispersal. In vivo and in vitro results, PEEK-PCS exhibited exceptional osseointegration and osteogenesis properties along with macrophage M2 phenotypic polarization, inflammatory factors reducing, promotion of osteogenic differentiation in bone marrow mesenchymal stem cells (BMSCs). Additionally, PEEK-PCS displays good autofluorescence properties in vitro and in vivo, with stable fluorescence for 14 days, suggesting potential bioimaging applications. The study confirms that PEEK in situ grafting with thermo-polymerized PCS elastomers is a viable approach for creating multifunctional (bone defect adaptation, bioimaging, immune regulation, and osseointegration) implants for bone tissue engineering.
Quantitative ultrasound (QUS) is a promising tool to estimate bone structure characteristics and predict fragile fracture. The aim of this pilot cross-sectional study was to evaluate the performance of a multi-channel residual network (MResNet) based on ultrasonic radiofrequency (RF) signal to discriminate fragile fractures retrospectively in postmenopausal women. RF signal and speed of sound (SOS) were obtained using an axial transmission QUS at one‐third distal radius for 246 postmenopausal women. Based on the involved RF signal, we conducted a MResNet, which combines multi-channel training with original ResNet, to classify the high risk of fragility fractures patients from all subjects. The bone mineral density (BMD) at lumber, hip and femoral neck acquired with DXA was recorded on the same day. The fracture history of all subjects in adulthood were collected. To assess the ability of the different methods in the discrimination of fragile fracture, the odds ratios (OR) calculated using binomial logistic regression analysis and the area under the receiver operator characteristic curves (AUC) were analyzed. Among the 246 postmenopausal women, 170 belonged to the non-fracture group, 50 to the vertebral group, and 26 to the non-vertebral fracture group. MResNet was discriminant for all fragile fractures (OR = 2.64; AUC = 0.74), for Vertebral fracture (OR = 3.02; AUC = 0.77), for non-vertebral fracture (OR = 2.01; AUC = 0.69). MResNet showed comparable performance to that of BMD of hip and lumbar with all types of fractures, and significantly better performance than SOS all types of fractures.Methods
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