[Analysis of risk factors for postoperative delirium in elderly patients undergoing spinal surgery].

OBJECTIVE: To investigate the risk factors of postoperative delirium in elderly patients undergoing spine surgery. METHODS: The basic case data of 566 patients who underwent spine surgery under general anesthesia from January 2021 to January 2023 were retrospectively analyzed. There were 296 males and 270 females with an average age of (71.58 ± 4.21) years old. There were 195 cases of cervical spine surgery, 26 cases of thoracic spine surgery and 345 cases of lumbar spine surgery.According to the occurrence of postoperative delirium, the patients were divided into postoperative delirium group(41 patients) and non-delirium group (525 patients). Univariate analysis was used to analyze the possible influencing factors such as gender, age, weight, smoking history, drinking history, surgical site, preoperative anxiety, intraoperative hypotension times, blood loss and so on, and binary Logistic regression was used to analyze the univariate factors with P<0.05. RESULTS: A total of 41 patients developed postoperative delirium. Univariate analysis showed that age (P=0.000), duration of surgery (P=0.039), preoperative anxiety (P=0.001), blood loss (P=0.000), history of opioid use (P=0.003), history of stroke (P=0.005), C-reactive protein (P=0.000), sodium ion(P=0.000) were significantly different between delirium group and non-delirium group. These factors were included in the binary Logistic regression analysis, and the results showed that age [OR=0.729, 95%CI(0.569, 0.932), P=0.012], opioid use [OR=21.500, 95%CI(1.334, 346.508), P=0.031], blood loss [OR=0.932, 95%CI(0.875, 0.993), P=0.029], C-reactive protein [OR=0.657, 95%CI(0.485, 0.890), P=0.007], preoperative anxiety [OR=23.143, 95%CI(1.859, 288.090), P=0.015], and sodium [OR=1.228, 95%CI(1.032, 1.461), P=0.020] were independent risk factors for the development of delirium after spinal surgery in elderly patients. CONCLUSION: Age, opioid use, blood loss, preoperative anxiety, elevated c-reactive protein, and hyponatremia are independent risk factors for the development of postoperative delirium in elderly patients undergoing spinal surgery.

Comparison of three artificial intelligence algorithms for automatic cobb angle measurement using teaching data specific to three disease groups.

Spinal deformities, including adolescent idiopathic scoliosis (AIS) and adult spinal deformity (ASD), affect many patients. The measurement of the Cobb angle on coronal radiographs is essential for their diagnosis and treatment planning. To enhance the precision of Cobb angle measurements for both AIS and ASD, we developed three distinct artificial intelligence (AI) algorithms: AIS/ASD-trained AI (trained with both AIS and ASD cases); AIS-trained AI (trained solely on AIS cases); ASD-trained AI (trained solely on ASD cases). We used 1612 whole-spine radiographs, including 1029 AIS and 583 ASD cases with variable postures, as teaching data. We measured the major and two minor curves. To assess the accuracy, we used 285 radiographs (159 AIS and 126 ASD) as a test set and calculated the mean absolute error (MAE) and intraclass correlation coefficient (ICC) between each AI algorithm and the average of manual measurements by four spine experts. The AIS/ASD-trained AI showed the highest accuracy among the three AI algorithms. This result suggested that learning across multiple diseases rather than disease-specific training may be an efficient AI learning method. The presented AI algorithm has the potential to reduce errors in Cobb angle measurements and improve the quality of clinical practice.

Spinal posture, mobility, and position sense in adolescents with chest wall deformities: a comparison of pectus excavatum, pectus carinatum and healthy peers.

PURPOSE: The study aimed to compare spinal posture, mobility, and position sense in adolescents with pectus excavatum (PE), pectus carinatum (PC), and healthy control (HC). METHODS: 22 with PE, 22 with PC, and 21 HC were included in the study. The spinal posture (thoracic kyphosis, lumbar lordosis, pelvic tilt, thoracic, lumbar, pelvic lateral tilt angles) and mobility (thoracic, lumbar, hip/sacral, and overall, in the sagittal and frontal plane) with the spinal mouse, and spinal position sense (repositing errors) with the inclinometer were assessed. RESULTS: The thoracic kyphosis angle of PE and PC was higher than in HC (p < 0.001; p = 0.001). Hip/sacral mobility in the sagittal plane was lower in the PE and PC than control, respectively (p < 0.001; p < 0.001). Overall sagittal spinal mobility (p:0.007) and hip/sacral mobility in the frontal plane (p:0.002) were lower in the PC than in HC. Overall frontal spinal mobility was lower in the PE and PC than in HC (p:0.002; p:0.014). The PE and PC repositing errors were higher (p < 0.001; p:0.014). CONCLUSION: The study found that adolescents with PE and PC had decreased spinal mobility, spinal alignment disorders, and a decline in spinal position sense. It is important not to overlook the spine during physical examinations of adolescents with chest wall deformities. In clinical practice, we suggest that adolescents with chest deformities should undergo a spine evaluation and be referred for physical therapy to manage spinal disorders.

Appropriateness and Quality of Composite Endpoint Use and Reporting in Spine Surgery: A Systematic Review.

BACKGROUND: A composite endpoint (CEP) is a measure comprising 2 or more separate component outcomes. The use of these constructs is increasing. We sought to conduct a systematic review on the usage, quality of reporting, and appropriate use of CEPs in spine surgery research. METHODS: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Articles reporting randomized controlled trials of a spine surgery intervention using a CEP as a primary outcome were included. We assessed the quality of CEP reporting, appropriateness of CEP use, and correspondence between CEP treatment effect and component outcome treatment effect in the included trials. RESULTS: Of 2,321 initial titles, 43 citations were included for analysis, which reported on 20 unique trials. All trials reported the CEP construct well. In 85% of trials, the CEP design was driven by US Food and Drug Administration guidance. In the majority of trials, the reporting of CEP results did not adhere to published recommendations: 43% of tests that reported statistically significant results on component outcomes were not statistically significant when adjusted for multiple testing. 67% of trials did not meet appropriateness criteria for CEP use. In addition, CEP treatment effect tended to be 6% higher than the median treatment effect for component outcomes. CONCLUSION: Given that CEP analysis was not appropriate for the majority of spine surgery trials and the inherent challenges in the reporting and interpretation of CEP analysis, CEP use should not be mandated by regulatory bodies in spine surgery trials. LEVEL OF EVIDENCE: Level I. See Instructions for Authors for a complete description of levels of evidence.

Automated detection, labelling and radiological grading of clinical spinal MRIs.

Spinal magnetic resonance (MR) scans are a vital tool for diagnosing the cause of back pain for many diseases and conditions. However, interpreting clinically useful information from these scans can be challenging, time-consuming and hard to reproduce across different radiologists. In this paper, we alleviate these problems by introducing a multi-stage automated pipeline for analysing spinal MR scans. This pipeline first detects and labels vertebral bodies across several commonly used sequences (e.g. T1w, T2w and STIR) and fields of view (e.g. lumbar, cervical, whole spine). Using these detections it then performs automated diagnosis for several spinal disorders, including intervertebral disc degenerative changes in T1w and T2w lumbar scans, and spinal metastases, cord compression and vertebral fractures. To achieve this, we propose a new method of vertebrae detection and labelling, using vector fields to group together detected vertebral landmarks and a language-modelling inspired beam search to determine the corresponding levels of the detections. We also employ a new transformer-based architecture to perform radiological grading which incorporates context from multiple vertebrae and sequences, as a real radiologist would. The performance of each stage of the pipeline is tested in isolation on several clinical datasets, each consisting of 66 to 421 scans. The outputs are compared to manual annotations of expert radiologists, demonstrating accurate vertebrae detection across a range of scan parameters. Similarly, the model's grading predictions for various types of disc degeneration and detection of spinal metastases closely match those of an expert radiologist. To aid future research, our code and trained models are made publicly available.

Origins of mammalian vertebral function revealed through digital bending experiments.

Unravelling the functional steps that underlie major transitions in the fossil record is a significant challenge for biologists owing to the difficulties of interpreting functional capabilities of extinct organisms. New computational modelling approaches provide exciting avenues for testing function in the fossil record. Here, we conduct digital bending experiments to reconstruct vertebral function in non-mammalian synapsids, the extinct forerunners of mammals, to provide insights into the functional underpinnings of the synapsid-mammal transition. We estimate range of motion and stiffness of intervertebral joints in eight non-mammalian synapsid species alongside a comparative sample of extant tetrapods, including salamanders, reptiles and mammals. We show that several key aspects of mammalian vertebral function evolved outside crown Mammalia. Compared to early diverging non-mammalian synapsids, cynodonts stabilized the posterior trunk against lateroflexion, while evolving axial rotation in the anterior trunk. This was later accompanied by posterior sagittal bending in crown mammals, and perhaps even therians specifically. Our data also support the prior hypothesis that functional diversification of the mammalian trunk occurred via co-option of existing morphological regions in response to changing selective demands. Thus, multiple functional and evolutionary steps underlie the origin of remarkable complexity in the mammalian backbone.

Osteological features of some clupeid fishes (Teleostei: Clupeiformes) of Iran.

This paper presents the conclusions of a comparative analysis of six osteological features: the Structure of the vertebral column, the morphology of the predorsal bones, the vertebral column regionalization, the pterygiophore interdigitation with neural spines of dorsal fin, the pterygiophores interdigitation of with the haemal spines of the anal fin, and the intermuscular bones (IMB) and hypomerals (HM) of 12 clupeid species of the families Alosidae, Dorosomatidae, Dussumieridae and Ehiravidae. Conceivable taxonomically beneficial osteological features are nominated and utilized to discrete the clupeid species explored. Formulae for the structure of the vertebral column, the dorsal- and anal-fin pterygiophores' interdigitation with the neural and haemal spines of the vertebrae are established. These morphological descriptive traits disclose a morphotype that may be related to the mode of swimming of the species searched. The morphological study of the vertebral column of the species in question permits the division of this bony structure into six morphologically different regions. This regionalization is more intricate than the classical division in abdominal and caudal parts only.

Spinal loads during dynamic full flexion and return to standing posture in different age and sex groups: A musculoskeletal model study.

During forward flexion, spine motion varies due to age and sex differences. Previous studies showed that lumbar/pelvis range of flexion (RoF) and lumbo-pelvic ratio (L/P) are age/sex dependent. How variation of these parameters affects lumbar loading in a normal population requires further assessment. We aimed to estimate lumbar loads during dynamic flexion-return cycle and the differences in peak loads (compression) and corresponding trunk inclinations due to variation in lumbar/pelvis RoF and L/P. Based on in vivo L/P (0.11-3.44), temporal phases of flexion (early, middle, and later), the lumbar (45-55°) and hip (60-79°) RoF; full flexion-return cycles of six seconds were reconstructed for three age groups (20-35, 36-50 and 50+ yrs.) in both sexes. Six inverse dynamic analyses were performed with a 50th percentile model, and differences in peak loads and corresponding trunk inclinations were calculated. Peak loads at L4-L5 were 179 N higher in younger males versus females, but 228 N and 210 N lower in middle-aged and older males, respectively, compared to females. Females exhibited higher trunk inclinations (6°-20°) than males across all age groups. Age related differences in L4-L5 peak loads and corresponding trunk inclinations were found up to 415 N and 19° in males and 152 N and 13° in females. With aging, peak loads were reduced in males but were found non-monotonic in females, whereas trunk inclinations at peak loads were reduced in both sexes from young to middle/old age groups. In conclusion, lumbar loading and corresponding trunk inclinations varied notably due to age/sex differences. Such data may help distinguishing normal or pathological condition of the lumbar spine.

A Computed Tomography-Based Fracture Prediction Model With Images of Vertebral Bones and Muscles by Employing Deep Learning: Development and Validation Study.

BACKGROUND: With the progressive increase in aging populations, the use of opportunistic computed tomography (CT) scanning is increasing, which could be a valuable method for acquiring information on both muscles and bones of aging populations. OBJECTIVE: The aim of this study was to develop and externally validate opportunistic CT-based fracture prediction models by using images of vertebral bones and paravertebral muscles. METHODS: The models were developed based on a retrospective longitudinal cohort study of 1214 patients with abdominal CT images between 2010 and 2019. The models were externally validated in 495 patients. The primary outcome of this study was defined as the predictive accuracy for identifying vertebral fracture events within a 5-year follow-up. The image models were developed using an attention convolutional neural network-recurrent neural network model from images of the vertebral bone and paravertebral muscles. RESULTS: The mean ages of the patients in the development and validation sets were 73 years and 68 years, and 69.1% (839/1214) and 78.8% (390/495) of them were females, respectively. The areas under the receiver operator curve (AUROCs) for predicting vertebral fractures were superior in images of the vertebral bone and paravertebral muscles than those in the bone-only images in the external validation cohort (0.827, 95% CI 0.821-0.833 vs 0.815, 95% CI 0.806-0.824, respectively; P<.001). The AUROCs of these image models were higher than those of the fracture risk assessment models (0.810 for major osteoporotic risk, 0.780 for hip fracture risk). For the clinical model using age, sex, BMI, use of steroids, smoking, possible secondary osteoporosis, type 2 diabetes mellitus, HIV, hepatitis C, and renal failure, the AUROC value in the external validation cohort was 0.749 (95% CI 0.736-0.762), which was lower than that of the image model using vertebral bones and muscles (P<.001). CONCLUSIONS: The model using the images of the vertebral bone and paravertebral muscle showed better performance than that using the images of the bone-only or clinical variables. Opportunistic CT screening may contribute to identifying patients with a high fracture risk in the future.

Bilateral Back Extensor Exosuit for multidimensional assistance and prevention of spinal injuries.

Lumbar spine injuries resulting from heavy or repetitive lifting remain a prevalent concern in workplaces. Back-support devices have been developed to mitigate these injuries by aiding workers during lifting tasks. However, existing devices often fall short in providing multidimensional force assistance for asymmetric lifting, an essential feature for practical workplace use. In addition, validation of device safety across the entire human spine has been lacking. This paper introduces the Bilateral Back Extensor Exosuit (BBEX), a robotic back-support device designed to address both functionality and safety concerns. The design of the BBEX draws inspiration from the anatomical characteristics of the human spine and back extensor muscles. Using a multi-degree-of-freedom architecture and serially connected linear actuators, the device's components are strategically arranged to closely mimic the biomechanics of the human spine and back extensor muscles. To establish the efficacy and safety of the BBEX, a series of experiments with human participants was conducted. Eleven healthy male participants engaged in symmetric and asymmetric lifting tasks while wearing the BBEX. The results confirm the ability of the BBEX to provide effective multidimensional force assistance. Moreover, comprehensive safety validation was achieved through analyses of muscle fatigue in the upper and the lower erector spinae muscles, as well as mechanical loading on spinal joints during both lifting scenarios. By seamlessly integrating functionality inspired by human biomechanics with a focus on safety, this study offers a promising solution to address the persistent challenge of preventing lumbar spine injuries in demanding work environments.

Unraveling sauropod diversity in the Portezuelo Formation of Patagonia through a comprehensive analysis of new and existing material.

The Portezuelo Formation preserves an outstanding record of the upper Turonian - lower Coniacian. Despite the discovery of a significant quantity of sauropod fossil material from the formation, only two species have been formally described to date: Malarguesaurus florenciae and Futalognkosaurus dukei. Here we present new sauropod material mostly composed of non-articulated caudal vertebrae (MCF-PVPH 916 and 917) that belong to two titanosauriforms on the basis of the following features: anterior caudal vertebrae with procoelous-opisthoplatyan articulations, transverse processes that reach the posterior articular face of the centrum and neural spines with a transverse width of around 50% of their anteroposterior length; anterior and middle caudal vertebrae with the neural arch restricted to the anterior half of the centrum; middle caudal centra with circular cross-section. Phylogenetic analysis recovers the new material in close relation to Malarguesaurus within a monophyletic clade at the base of Somphospondyli. This clade shares large pedicel height with a vertical anterior border on the middle caudal vertebrae, a vertical orientation of the neural spines on the distalmost middle caudal vertebrae and proximalmost posterior caudal vertebrae, and subequal relative lengths of the proximal ulnar condylar processes. The specimens presented here are distinct not only from Futalognkosaurus, but also from other indeterminate titanosaurian remains from the same formation. However, there are no significant differences between the specimen MCF-PVPH 917 and Malarguesaurus, but there are differences between the posterior caudal vertebrae of MCF-PVPH 916 and Malarguesaurus, so they could be considered different species. Whilst we err on the side of caution in not naming new taxa here, the two specimens significantly expand what we know about sauropods in the Turonian-Coniacian ecosystems of Patagonia, which will continue to do so as more material is discovered.

A new stegosaur (Dinosauria: Ornithischia) from the Middle Jurassic of Gansu Province, China.

Stegosaurs are a minor but iconic clade of ornithischian dinosaurs, yet due to a poor fossil record, their early evolution is poorly understood. Here, we describe a new stegosaur, Baiyinosaurus baojiensis, gen. et sp. nov. from the Middle Jurassic Wangjiashan Formation of the Pingchuan District, Baiyin City, Gansu Province, China. The frontal of Baiyinosaurus possesses a unique characteristic among Stegosauria: it is wider than long and contributes to both the medial and anterior margins of the supratemporal fenestra. The character combinations of dorsal vertebrae of Baiyinosaurus are also different to other stegosaurs: its neural arches are not greatly elongated, its parapophyses are well developed, and its neural spines are axially expanded in lateral. The features of the frontal and vertebrae of Baiyinosaurus are reminiscent of basally branching thyreophorans, indicating that Baiyinosaurus is transitional in morphology between early thyreophorans and early-diverging stegosaurs. Systematic analysis shows that Baiyinosaurus is an early-diverging stegosaur.

Task-based image quality assessment of an intraoperative CBCT for spine surgery compared with conventional CT.

PURPOSE: To analyze the image quality of a novel, state-of-the art platform for CBCT image-guided spine surgery, focusing particularly on the dose-effectiveness compared with conventional CT (the gold standard for postoperative assessment). METHODS: The ClarifEye platform (Philips Healthcare) with integrated augmented-reality surgical navigation, has been compared with a GE Revolution CT (GE Healthcare). The 3D spatial resolution (TTF) and noise (NPS) were evaluated considering relevant feature contrasts (200-900 HU) and background noise for differently sized patients (200-300 mm water-equivalent diameter). These measures were used to determine the noise equivalent quanta (NEQ) and observer model detectability. RESULTS: The CBCT system exhibited a linear response with 50% TTF at 5.7 cycles/cm (10% TTF at 9.2 cycles/cm), and the axial noise power peaking at about 3.6 cycles/cm (average frequency of 4.1 cycles/cm). The noise magnitude and texture differed markedly compared to iteratively reconstructed CT images (GE ASiR-V). The CBCT system had 26% lower detectability for a high-frequency task (related to edge detection) compared with CT images reconstructed using the Bone kernel combined with ASiR-V 50%. Likewise, it had 18% lower detectability for low- and mid-frequency tasks compared with CT images reconstructed using the Standard kernel. This difference translates to 50%-80% higher CBCT imaging doses required to match the CT image quality. CONCLUSIONS: The ClarifEye platform demonstrates intraoperative CBCT-imaging capabilities that under certain circumstances are comparable with conventional CT. However, due to limited dose-effectiveness, a trade-off between timeliness and radiation exposure must be considered if end-of-procedure CBCT is to replace postoperative CT.

Sensitivity to change of structural outcomes in axial spondyloarthritis after 10 years of follow up. Data from the DESIR cohort.

OBJECTIVE: To evaluate the sensitivity to change in structural imaging outcomes over 10 years of follow-up in patients with axial spondyloarthritis (axSpA). METHODS: Patients with axSpA from the Devenir des Spondyloarthropathies Indifferénciées Récentes cohort were included. Radiographs and MRIs of the sacroiliac joints (SIJ) and spine were obtained at baseline and at 1, 2, 5 and 10 years. The yearly rate of change of each structural outcome was analysed using generalised estimating equation models, including all patients with ≥1 score from ≥1 reader from ≥1 reading wave, using the time (years) as an explanatory variable and adjusting for reader and wave. All outcomes were standardised, and the relative standardised rate of change was calculated (ie, the standardised rate of an outcome divided by the rate of a reference outcome). RESULTS: A total of 659 patients (46% males and mean age 33.6 years) were included. The most sensitive outcome to change in the SIJ (both MRI and radiographs) was the presence of ≥3 fatty lesions at a specific timepoint, with a relative standardised rate of change per year of 5.28 using the modified New York criteria as reference.Similarly, the most sensitive to change (in both MRI and radiographs) outcome in the spine was the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS; relative standardised yearly change 1.76) using ≥1 syndesmophyte as reference. CONCLUSION: MRI structural outcomes in the SIJ (ie, fatty lesions) are more sensitive to change than radiographic outcomes. Conversely, the mSASSS remains the most sensitive method, even when compared with MRI of the spine.

Finite element models with automatic computed tomography bone segmentation for failure load computation.

Bone segmentation is an important step to perform biomechanical failure load simulations on in-vivo CT data of patients with bone metastasis, as it is a mandatory operation to obtain meshes needed for numerical simulations. Segmentation can be a tedious and time consuming task when done manually, and expert segmentations are subject to intra- and inter-operator variability. Deep learning methods are increasingly employed to automatically carry out image segmentation tasks. These networks usually need to be trained on a large image dataset along with the manual segmentations to maximize generalization to new images, but it is not always possible to have access to a multitude of CT-scans with the associated ground truth. It then becomes necessary to use training techniques to make the best use of the limited available data. In this paper, we propose a dedicated pipeline of preprocessing, deep learning based segmentation method and post-processing for in-vivo human femurs and vertebrae segmentation from CT-scans volumes. We experimented with three U-Net architectures and showed that out-of-the-box models enable automatic and high-quality volume segmentation if carefully trained. We compared the failure load simulation results obtained on femurs and vertebrae using either automatic or manual segmentations and studied the sensitivity of the simulations on small variations of the automatic segmentation. The failure loads obtained using automatic segmentations were comparable to those obtained using manual expert segmentations for all the femurs and vertebrae tested, demonstrating the effectiveness of the automated segmentation approach for failure load simulations.

Automatic 3D reconstruction of vertebrae from orthogonal bi-planar radiographs.

When conducting spine-related diagnosis and surgery, the three-dimensional (3D) upright posture of the spine under natural weight bearing is of significant clinical value for physicians to analyze the force on the spine. However, existing medical imaging technologies cannot meet current requirements of medical service. On the one hand, the mainstream 3D volumetric imaging modalities (e.g. CT and MRI) require patients to lie down during the imaging process. On the other hand, the imaging modalities conducted in an upright posture (e.g. radiograph) can only realize 2D projections, which lose the valid information of spinal anatomy and curvature. Developments of deep learning-based 3D reconstruction methods bring potential to overcome the limitations of the existing medical imaging technologies. To deal with the limitations of current medical imaging technologies as is described above, in this paper, we propose a novel deep learning framework, ReVerteR, which can realize automatic 3D Reconstruction of Vertebrae from orthogonal bi-planar Radiographs. With the utilization of self-attention mechanism and specially designed loss function combining Dice, Hausdorff, Focal, and MSE, ReVerteR can alleviate the sample-imbalance problem during the reconstruction process and realize the fusion of the centroid annotation and the focused vertebra. Furthermore, aiming at automatic and customized 3D spinal reconstruction in real-world scenarios, we extend ReVerteR to a clinical deployment-oriented framework, and develop an interactive interface with all functions in the framework integrated so as to enhance human-computer interaction during clinical decision-making. Extensive experiments and visualization conducted on our constructed datasets based on two benchmark datasets of spinal CT, VerSe 2019 and VerSe 2020, demonstrate the effectiveness of our proposed ReVerteR. In this paper, we propose an automatic 3D reconstruction method of vertebrae based on orthogonal bi-planar radiographs. With the 3D upright posture of the spine under natural weight bearing effectively constructed, our proposed method is expected to better support doctors make clinical decision during spine-related diagnosis and surgery.