Current Issue : January-March Volume : 2025 Issue Number : 1 Articles : 5 Articles
Background and Objectives: The advent of augmented reality (AR) in spinal surgery represents a key technological evolution, enhancing precision and safety in procedures such as pedicle screw instrumentation. This review assesses the current applications, benefits, and challenges of AR technology in spinal surgery, focusing on its effects on surgical accuracy and patient outcomes. Materials and Methods: A comprehensive review of the literature published between January 2023 and December 2024 was conducted, focusing on AR and navigational technologies in spinal surgery. Key outcomes such as accuracy, efficiency, and complications were emphasized. Results: Thirteen studies were included, highlighting substantial improvements in surgical accuracy, efficiency, and safety with AR and navigational systems. AR technology was found to significantly reduce the learning curve for spinal surgeons, improve procedural efficiency, and potentially reduce surgical complications. The challenges identified include high system costs, the complexity of training requirements, the integration with existing workflows, and limited clinical evidence. Conclusions: AR technology holds promise for advancements in spinal surgery, particularly in improving the accuracy and safety of pedicle screw instrumentation. Despite existing challenges such as cost, training needs, and regulatory hurdles, AR has the potential to transform spinal surgical practices. Ongoing research, technological refinements, and the development of implementation strategies are essential to fully leverage AR’s capabilities in enhancing patient care....
Knee effusion, a common and important indicator of joint diseases such as osteoarthritis, is typically more discernible on magnetic resonance imaging (MRI) scans compared to radiographs. However, the use of radiographs for the early detection of knee effusion remains promising due to their cost-effectiveness and accessibility. This multi-center prospective study collected a total of 1413 radiographs from four hospitals between February 2022 to March 2023, of which 1281 were analyzed after exclusions. To automatically detect knee effusion on radiographs, we utilized a stateof- the-art (SOTA) deep learning-based classification model with a novel preprocessing technique to optimize images for diagnosing knee effusion. The diagnostic performance of the proposed method was significantly higher than that of the baseline model, achieving an area under the receiver operating characteristic curve (AUC) of 0.892, accuracy of 0.803, sensitivity of 0.820, and specificity of 0.785. Moreover, the proposed method significantly outperformed two non-orthopedic physicians. Coupled with an explainable artificial intelligence method for visualization, this approach not only improved diagnostic performance but also interpretability, highlighting areas of effusion. These results demonstrate that the proposed method enables the early and accurate classification of knee effusions on radiographs, thereby reducing healthcare costs and improving patient outcomes through timely interventions....
Taurolidine, known for its broad-spectrum antimicrobial properties and low toxicity, has shown promise in reducing infections in various surgical settings. However, it has not been extensively evaluated in orthopedic surgery. This study assessed the efficacy of taurolidine irrigation in reducing surgical site infections in patients undergoing ankle fracture surgery. A retrospective review was conducted for patients >20 years old who underwent ankle fracture surgery between March 2016 and March 2023, with follow-ups exceeding 6 months. Patients were classified into the following two groups: those who underwent normal saline (NS) irrigation and those who underwent taurolidine irrigation. Minor infections were defined as requiring additional oral antibiotics postoperatively, while major infections were characterized by hospitalization or reoperation due to infection within 3 months. Of 844 patients, 688 were included. The taurolidine group (n = 328) had a significant reduction in minor infections (7.3% vs. 22.5%, odds ratio = 0.410, p = 0.028) compared to the NS group (n = 360). Major infections were fewer in the NS group (1.2% vs. 0%, p = 0.051), but the number of cases was too small for reliable analysis. Taurolidine irrigation significantly reduces the occurrence of minor infections in ankle fracture surgeries when compared to normal saline irrigation....
Background and Objectives: Neglected patellar dislocation in the presence of end-stage osteoarthritis (OA) is a rare condition characterized by the patella remaining laterally dislocated without reduction. Due to the scarcity of reported cases, the optimal management approach is still uncertain. However, primary total knee arthroplasty (TKA) can serve as an effective treatment option. This study aimed to present the clinical and radiological outcomes achieved using our surgical technique. Materials and Methods: A retrospective review of 12 knees in 8 patients with neglected patellar dislocation and end-stage OA who underwent primary TKA was conducted. The surgical procedure involved conventional TKA techniques (e.g., medial parapatellar arthrotomy) and additional procedures specific to the individual pathologies of neglected patellar dislocation (e.g., lateral release, medial plication, and quadriceps lengthening). Clinical outcomes, including patient-reported outcome measures (PROMs) (Knee Society Scores and theWestern Ontario and McMaster Universities Osteoarthritis Index) and knee range of motion (ROM), were assessed preoperatively and two years postoperatively. Radiological measures including mechanical femorotibial angle and patellar tilt angle were assessed preoperatively and until the last follow-up examinations. Any complications were also reviewed. Results: There were significant improvements in all PROMs, knee ROM, and radiological outcomes, including mechanical femorotibial angle and patellar tilt angle (all p < 0.05). At a mean follow-up of 68 months, no major complications requiring revision surgery, including patellar dislocation, were reported. Conclusions: Primary TKA is an effective procedure for correcting various pathologies associated with neglected patellar dislocation in end-stage OA without necessitating additional bony procedures. Satisfactory clinical and radiological outcomes can be expected using pathology-specific procedures....
The accurate and efficient segmentation of the spine is important in the diagnosis and treatment of spine malfunctions and fractures. However, it is still challenging because of large inter-vertebra variations in shape and cross-image localization of the spine. In previous methods, convolutional neural networks (CNNs) have been widely applied as a vision backbone to tackle this task. However, these methods are challenged in utilizing the global contextual information across the whole image for accurate spine segmentation because of the inherent locality of the convolution operation. Compared with CNNs, the Vision Transformer (ViT) has been proposed as another vision backbone with a high capacity to capture global contextual information. However, when the ViT is employed for spine segmentation, it treats all input tokens equally, including vertebrae-related tokens and non-vertebrae-related tokens. Additionally, it lacks the capability to locate regions of interest, thus lowering the accuracy of spine segmentation. To address this limitation, we propose a novel Vertebrae-aware Vision Transformer (VerFormer) for automatic spine segmentation from CT images. Our VerFormer is designed by incorporating a novel Vertebrae-aware Global (VG) block into the ViT backbone. In the VG block, the vertebrae-related global contextual information is extracted by a Vertebrae-aware Global Query (VGQ) module. Then, this information is incorporated into query tokens to highlight vertebrae-related tokens in the multi-head self-attention module. Thus, this VG block can leverage global contextual information to effectively and efficiently locate spines across the whole input, thus improving the segmentation accuracy of VerFormer. Driven by this design, the VerFormer demonstrates a solid capacity to capture more discriminative dependencies and vertebrae-related context in automatic spine segmentation. The experimental results on two spine CT segmentation tasks demonstrate the effectiveness of our VG block and the superiority of our VerFormer in spine segmentation. Compared with other popular CNN- or ViT-based segmentation models, our VerFormer shows superior segmentation accuracy and generalization....
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