Search Results (6)

Background and Objectives: Commonly being the first step in trauma routine imaging, up to 67% fractures are missed on plain radiographs of the thoracolumbar (TL) spine. The aim of this study was to develop a deep learning model that detects traumatic fractures on sagittal radiographs of the TL spine. Identifying vertebral fractures in simple radiographic projections would have a significant clinical and financial impact, especially for low- and middle-income countries where computed tomography (CT) and magnetic resonance imaging (MRI) are not readily available and could help select patients that need second level imaging, thus improving the cost-effectiveness. Materials and Methods: Imaging studies (radiographs, CT, and/or MRI) of 151 patients were used. An expert group of three spinal surgeons reviewed all available images to confirm presence and type of fractures. In total, 630 single vertebra images were extracted from the sagittal radiographs of the 151 patients—302 exhibiting a vertebral body fracture, and 328 exhibiting no fracture. Following augmentation, these single vertebra images were used to train, validate, and comparatively test two deep learning convolutional neural network models, namely ResNet18 and VGG16. A heatmap analysis was then conducted to better understand the predictions of each model. Results: ResNet18 demonstrated a better performance, achieving higher sensitivity (91%), specificity (89%), and accuracy (88%) compared to VGG16 (90%, 83%, 86%). In 81% of the cases, the “warm zone” in the heatmaps correlated with the findings, suggestive of fracture within the vertebral body seen in the imaging studies. Vertebras T12 to L2 were the most frequently involved, accounting for 48% of the fractures. A4, A3, and A1 were the most frequent fracture types according to the AO Spine Classification. Conclusions: ResNet18 could accurately identify the traumatic vertebral fractures on the TL sagittal radiographs. In most cases, the model based its prediction on the same areas that human expert classifiers used to determine the presence of a fracture. Full article

The study aims to create a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome using a machine learning (ML) approach. A single spine surgery center retrospective review of prospectively collected data from January 2016 to December 2020 from the institutional registry (SpineREG) was performed. The inclusion criteria were age ≥ 18 years, both sexes, lumbar arthrodesis procedure, a complete follow up assessment (Oswestry Disability Index—ODI, SF-36 and COMI back) and the capability to read and understand the Italian language. A delta of improvement of the ODI higher than 12.7/100 was considered a “good early outcome”. A combined target model of ODI (Δ ≥ 12.7/100), SF-36 PCS (Δ ≥ 6/100) and COMI back (Δ ≥ 2.2/10) was considered an “excellent early outcome”. The performance of the ML models was evaluated in terms of sensitivity, i.e., True Positive Rate (TPR), specificity, i.e., True Negative Rate (TNR), accuracy and area under the receiver operating characteristic curve (AUC ROC). A total of 1243 patients were included in this study. The model for predicting ODI at 6 months’ follow up showed a good balance between sensitivity (74.3%) and specificity (79.4%), while providing a good accuracy (75.8%) with ROC AUC = 0.842. The combined target model showed a sensitivity of 74.2% and specificity of 71.8%, with an accuracy of 72.8%, and an ROC AUC = 0.808. The results of our study suggest that a machine learning approach showed high performance in predicting early good to excellent clinical results. Full article

While the non-linear behavior of spine segments has been extensively investigated in the past, the behavior of the Anterior Longitudinal Ligament (ALL) and its contribution during flexion and extension has never been studied considering the spine as a whole. The aims of the present study were to exploit Digital Image Correlation (DIC) to: (I) characterize the strain distribution on the ALL during flexion-extension, (II) compare the strain on specific regions of interest (ROI) of the ALL in front of the vertebra and of the intervertebral disc, (III) analyze the non-linear relationship between the surface strain and the imposed rotation and the resultant moment. Three specimens consisting of 6 functional spinal units (FSUs) were tested in flexion-extension. The full-field strain maps were measured on the surface of the ALL, and the most strained areas were investigated in detail. The DIC-measured strains showed different values of peak strain in correspondence with the vertebra and the disc but the average over the ROIs was of the same order of magnitude. The strain-moment curves showed a non-linear response like the moment-angle curves: in flexion the slope of the strain-moment curve was greater than in extension and with a more abrupt change of slope. To the authors’ knowledge, this is the first study addressing, by means of a full-field strain measurement, the non-linear contribution of the ALL to spine biomechanics. This study was limited to only three specimens; hence the results must be taken with caution. This information could be used in the future to build more realistic numerical models of the spine. Full article

From its first appearance in early vertebrates, the spine evolved the function of protecting the spinal cord, avoiding excessive straining during body motion. Its stiffness and strength provided the basis for the development of the axial skeleton as the mechanical support of later animals, especially those which moved to the terrestrial environment where gravity loads are not alleviated by the buoyant force of water. In tetrapods, the functions of the spine can be summarized as follows: protecting the spinal cord; supporting the weight of the body, transmitting it to the ground through the limbs; allowing the motion of the trunk, through to its flexibility; providing robust origins and insertions to the muscles of trunk and limbs. This narrative review provides a brief perspective on the development of the spine in vertebrates, first from an evolutionary, and then from an embryological point of view. The paper describes functions and the shape of the spine throughout the whole evolution of vertebrates and vertebrate embryos, from primordial jawless fish to extant animals such as birds and humans, highlighting its fundamental features such as strength, stability, and flexibility, which gives it huge potential as a basis for bio-inspired technologies. Full article

The increase of multidrug-resistant bacteria remains a global concern. Among the proposed strategies, the use of nanoparticles (NPs) alone or associated with orthopedic implants represents a promising solution. NPs are well-known for their antimicrobial effects, induced by their size, shape, charge, concentration and reactive oxygen species (ROS) generation. However, this non-specific cytotoxic potential is a powerful weapon effective against almost all microorganisms, but also against eukaryotic cells, raising concerns related to their safe use. Among the analyzed transition metals, silver is the most investigated element due to its antimicrobial properties per se or as NPs; however, its toxicity raises questions about its biosafety. Even though it has milder antimicrobial and cytotoxic activity, TiO₂ needs to be exposed to UV light to be activated, thus limiting its use conjugated to orthopedic devices. By contrast, gold has a good balance between antimicrobial activity as an NP and cytocompatibility because of its inability to generate ROS. Nevertheless, although the toxicity and persistence of NPs within filter organs are not well verified, nowadays, several basic research on NP development and potential uses as antimicrobial weapons is reported, overemphasizing NPs potentialities, but without any existing potential of translation in clinics. This analysis cautions readers with respect to regulation in advancing the development and use of NPs. Hopefully, future works in vivo and clinical trials will support and regulate the use of nano-coatings to guarantee safer use of this promising approach against antibiotic-resistant microorganisms. Full article

Finite element modeling has been widely used to simulate the mechanical behavior of the intervertebral disc. Previous models have been generally limited to the prediction of the disc behavior under simple loading conditions, thus neglecting its response to complex loads, which may induce its failure. The aim of this study was to generate a finite element model of the ovine lumbar intervertebral disc, in which the annulus was characterized by an anisotropic hyperelastic formulation, and to use it to define which mechanical condition was unsafe for the disc. Based on published in vitro results, numerical analyses under combined flexion, lateral bending, and axial rotation with a magnitude double that of the physiological ones were performed. The simulations showed that flexion was the most unsafe load and an axial tensile stress greater than 10 MPa can cause disc failure. The numerical model here presented can be used to predict the failure of the disc under all loading conditions, which may support indications about the degree of safety of specific motions and daily activities, such as weight lifting. Full article