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STUDY DESIGN: Reliability study. OBJECTIVES: The radiographic diagnosis of non-union is not standardized. Prior authors have suggested using a cutoff of .9. The ICC from these high performing reviewers was .94 (.9; .97), SEM was .45 mm, and MD was 1.26 mm. CONCLUSIONS: The MD of 2.29 mm in our study group was not precise enough to support a cutoff of more...

Ossification of the posterior longitudinal ligament (OPLL) is a significant spinal condition that can lead to severe neurological deficits. Recent advancements in machine learning (ML) and deep learning (DL) have led to the development of promising tools for the early detection and diagnosis of OPLL. This systematic review evaluated the diagnostic performance of ML and DL models and clinical implications in OPLL detection. A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed/Medline and Scopus databases were searched for studies published between January 2000 and September 2024. Eligible studies included those utilizing ML or DL models for OPLL detection using imaging data. All studies were assessed for the risk of bias using appropriate tools. The key performance metrics, including accuracy, sensitivity, specificity, and area under the curve (AUC), were analyzed. Eleven studies, comprising a total of 6,031 patients, were included. The ML and DL models demonstrated high diagnostic performance, with accuracy rates ranging from 69.6% to 98.9% and AUC values up to 0.99. Convolutional neural networks and random forest models were the most used approaches. The overall risk of bias was moderate, and concerns were primarily related to participant selection and missing data. In conclusion, ML and DL models show great potential for accurate detection of OPLL, particularly when integrated with imaging techniques. However, to ensure clinical applicability, further research is warranted to validate these findings in more extensive and diverse populations. [ABSTRACT FROM AUTHOR] more...

Objective: To develop and evaluate a technique using convolutional neural networks (CNNs) for the computer-assisted diagnosis of cervical spine fractures from radiographic x-ray images. By leveraging deep learning techniques, the study might potentially lead to improved patient outcomes and clinical decision-making. Methods: This study obtained 500 lateral radiographic cervical spine x-ray images from standard open-source dataset repositories to develop a classification model using CNNs. All the images contained diagnostic information, including normal cervical radiographic images (n=250) and fracture images of the cervical spine fracture (n=250). The model would classify whether the patient had a cervical spine fracture or not. Seventy percent of the images were training data sets used for model training, and 30% were for testing. Konstanz Information Miner (KNIME)'s graphic user interface-based programming enabled class label annotation, data preprocessing, CNNs model training, and performance evaluation. Results: The performance evaluation of a model for detecting cervical spine fractures presents compelling results across various metrics. This model exhibits high sensitivity (recall) values of 0.886 for fractures and 0.957 for normal cases, indicating its proficiency in identifying true positives. Precision values of 0.954 for fractures and 0.893 for normal cases highlight the model's ability to minimize false positives. With specificity values of 0.957 for fractures and 0.886 for normal cases, the model effectively identifies true negatives. The overall accuracy of 92.14% highlights its reliability in correctly classifying cases by the area under the receiver operating characteristic curve. Conclusion: We successfully used deep learning models for computer-assisted diagnosis of cervical spine fractures from radiographic x-ray images. This approach can assist the radiologist in screening, detecting, and diagnosing cervical spine fractures. [ABSTRACT FROM AUTHOR] more...

Spinal cord injury (SCI) is a catastrophic condition that disrupts neurons within the spinal cord, leading to severe motor and sensory deficits. While current treatments can alleviate pain, they do not promote neural regeneration or functional recovery. Three-dimensional (3D) bioprinting offers promising solutions for SCI repair by enabling the creation of complex neural tissue constructs. This review provides a comprehensive overview of 3D bioprinting techniques, bioinks, and stem cell applications in SCI repair. Additionally, it highlights recent advancements in 3D bioprinted scaffolds, including the integration of conductive materials, the incorporation of bioactive molecules like neurotrophic factors, drugs, and exosomes, and the design of innovative structures such as multi-channel and axial scaffolds. These innovative strategies in 3D bioprinting can offer a comprehensive approach to optimizing the spinal cord microenvironment, advancing SCI repair. This review highlights a comprehensive understanding of the current state of 3D bioprinting in SCI repair, offering insights into future directions in the field of regenerative medicine. [ABSTRACT FROM AUTHOR] more...

Damage to the central nervous system (CNS) often leads to irreversible neurological deficits, and there are currently few effective treatments available. However, recent advancements in regenerative medicine have identified CNS organoids as promising therapeutic options for addressing CNS injuries. These organoids, composed of various neurons and supporting cells, have shown potential for direct repair at injury sites. CNS organoids resemble the structure and function of actual brain tissue, which allows them to adapt and function well within the physiological environment when transplanted into injury sites. Research findings suggest that CNS organoids can replace damaged neurons, form new neural connections, and promote neural recovery. This review highlights the emerging benefits, evaluates preclinical transplantation outcomes, and explores future strategies for optimizing neuroregeneration using CNS organoids. With continued research and technological advancements, these organoids could provide new hope for patients suffering from neurological deficits. [ABSTRACT FROM AUTHOR] more...

Osteoporotic vertebral compression fractures (OVCFs) are the most prevalent fractures among patients with osteoporosis, leading to severe pain, deformities, and even death. This study explored the use of ectopic embryonic calvaria derived mesenchymal stem cells (EE-cMSCs), which are known for their superior differentiation and proliferation capabilities, as a potential treatment for bone regeneration in OVCFs. We evaluated the impact of EE-cMSCs on osteoclastogenesis in a RAW264.7 cell environment, which was induced by the receptor activator of nuclear factor kappa-beta ligand (RANKL), using cytochemical staining and quantitative real-time PCR. The osteogenic potential of EE-cMSCs was evaluated under various hydrogel conditions. An osteoporotic vertebral body bone defect model was established by inducing osteoporosis in rats through bilateral ovariectomy and creating defects in their coccygeal vertebral bodies. The effects of EE-cMSCs were examined using micro-computed tomography (μCT) and histology, including immunohistochemical analyses. In vitro, EE-cMSCs inhibited osteoclast differentiation and promoted osteogenesis in a 3D cell culture environment using fibrin hydrogel. Moreover, μCT and histological staining demonstrated increased new bone formation in the group treated with EE-cMSCs and fibrin. Immunostaining showed reduced osteoclast activity and bone resorption, alongside increased angiogenesis. Thus, EE-cMSCs can effectively promote bone regeneration and may represent a promising therapeutic approach for treating OVCFs. [ABSTRACT FROM AUTHOR] more...

Since the emergence of the first cerebral organoid (CO) in 2013, advancements have transformed central nervous system (CNS) research. Initial efforts focused on studying the morphogenesis of COs and creating reproducible models. Numerous methodologies have been proposed, enabling the design of the brain organoid to represent specific regions and spinal cord structures. CNS organoids now facilitate the study of a wide range of CNS diseases, from infections to tumors, which were previously difficult to investigate. We summarize the major advancements in CNS organoids, concerning morphogenetic designs and disease models. We examine the development of fabrication procedures and how these advancements have enabled the generation of region-specific brain organoids and spinal cord models. We highlight the application of these organoids in studying various CNS diseases, demonstrating the versatility and potential of organoid models in advancing our understanding of complex conditions. We discuss the current challenges in the field, including issues related to reproducibility, scalability, and the accurate recapitulation of the in vivo environment. We provide an outlook on prospective studies and future directions. This review aims to provide a comprehensive overview of the state-of-the-art CNS organoid research, highlighting key developments, current challenges, and prospects in the field. [ABSTRACT FROM AUTHOR] more...

Osteoporotic vertebral compression fractures (OVCFs) significantly increase morbidity and mortality, presenting a formidable challenge in healthcare. Traditional interventions such as vertebroplasty and kyphoplasty, despite their widespread use, are limited in addressing the secondary effects of vertebral fractures in adjacent areas and do not facilitate bone regeneration. This review paper explores the emerging domain of regenerative therapies, spotlighting stem cell therapy's transformative potential in OVCF treatment. It thoroughly describes the therapeutic possibilities and mechanisms of action of mesenchymal stem cells against OVCFs, relying on recent clinical trials and preclinical studies for efficacy assessment. Our findings reveal that stem cell therapy, particularly in combination with scaffolding materials, holds substantial promise for bone regeneration, spinal stability improvement, and pain mitigation. This integration of stem cell-based methods with conventional treatments may herald a new era in OVCF management, potentially improving patient outcomes. This review advocates for accelerated research and collaborative efforts to translate laboratory breakthroughs into clinical practice, emphasizing the revolutionary impact of regenerative therapies on OVCF management. In summary, this paper positions stem cell therapy at the forefront of innovation for OVCF treatment, stressing the importance of ongoing research and cross-disciplinary collaboration to unlock its full clinical potential. [ABSTRACT FROM AUTHOR] more...