Optimize deep learning-based vertebrae segmentation in longitudinal CT scans of multiple myeloma patients using structural uncertainty analysis.

Retrospective CT scans from 474 multiple myeloma patients were divided into train (179 patients, 349 scans, 2005-2011) and test cohort (295 patients, 671 scans, 2012-2020). An enhanced segmentation pipeline was developed on the train cohort. It integrated vertebrae segmentation using an open-source deep learning method (Payer's) with a post-hoc structural uncertainty analysis. This analysis identified inconsistencies, automatically correcting them or flagging uncertain regions for human review. Segmentation quality was assessed through vertebral shape analysis using topology. Metrics included 'identification rate', 'longitudinal vertebral match rate', 'success rate' and 'series success rate' and evaluated across age/sex subgroups. Statistical analysis included McNemar and Wilcoxon signed-rank tests, with p < 0.05 indicating significant improvement.

Payer's method achieved an identification rate of 95.8% and success rate of 86.7%. The proposed pipeline automatically improved these metrics to 98.8% and 96.0%, respectively (p < 0.001). Additionally, 3.6% of scans were marked for human inspection, increasing the success rate from 96.0% to 98.8% (p < 0.001). The vertebral match rate increased from 97.0% to 99.7% (p < 0.001), and the series success rate from 80.0% to 95.4% (p < 0.001). Subgroup analysis showed more consistent performance across age and sex groups.

The proposed pipeline significantly outperforms Payer's method, enhancing segmentation accuracy and reducing longitudinal matching errors while minimizing evaluation workload. Its uncertainty analysis ensures robust performance, making it a valuable tool for longitudinal studies in multiple myeloma.

To evaluate short-segment fixation (SSF), with or without advanced osteotomy, for treating thoracolumbar kyphosis caused by osteoporotic vertebral compression fractures (OVCFs).

This retrospective analysis included 28 patients with thoracolumbar kyphosis caused by OVCFs who underwent SSF at our hospital between 2017 and 2022. The change in the Cobb angle between standing and supine positions was measured to establish whether an advanced osteotomy was necessary. Bone mineral density (T-score) and related hematologic bone metabolism markers were recorded to assess the patient's osteoporosis status. The Cobb angle and sagittal plane parameters were measured before and after surgery to determine the orthopedic outcomes, and function was assessed using a visual analog scale and the Oswestry Disability Index.

A total of 28 patients successfully underwent SSF with or without advanced osteotomy, with no serious complications. The mean follow-up period was 29 ± 3 months. The Cobb angle decreased significantly, from 45° ± 6° before surgery to 11° ± 3° at the last follow-up (P < 0.05). The visual analog scale scores and Oswestry Disability Index at the last follow-up were significantly improved compared with those before surgery (P < 0.05). Five patients developed low back pain within 6 months of surgery (proximal junctional kyphosis in 4 patients and internal fixation fractures in 1 patient), and 2 of these patients underwent a second surgery. In the long-term follow-up, 2 patients had proximal junctional kyphosis/distal junctional kyphosis after the re-trauma. The 21 remaining patients maintained good internal fixation at the last follow-up, with no broken screws or rods, loosening, or displacement.

SSF, with or without advanced osteotomy, is an effective treatment for thoracolumbar kyphosis caused by OVCFs, achieving good orthopedic outcomes and improving the quality of life of patients. Continuous standardized anti-osteoporosis treatment is essential for long-term recovery.

Several conditions can increase the incidence of vertebral fragility fractures, including metastatic bone disease. Computational tools could help clinicians estimate the risk of vertebral fracture in these patients; however, comparison with in vitro data is mandatory before using them in clinical practice. Nine spine segments were tested under compression and imaged with micro-computed tomography (µCT). The displacement field was calculated for each vertebra using a global digital volume correlation (DVC) approach. Subject-specific homogenised finite element models of each vertebra were built from µCT images, applying experimentally matched boundary conditions at the endplates. Numerical and experimental displacements, reaction forces, and locations showing higher strain concentrations were eventually compared. Additionally, given that µCT cannot be performed in clinical settings, the outcomes of a µCT-based model were also compared to those of a model built from clinical CT scans of the same specimen. Good agreement between DVC and µCT-based FE displacements was found, both for healthy (R2 = 0.69 ÷ 0.83, RMSE = 3 ÷ 22%, max error < 45 μm) and metastatic (R2 = 0.64 ÷ 0.93, RMSE = 5 ÷ 18%, max error < 54 μm) vertebrae. Strong correlations were found between µCT-based and clinical CT-based FE model outcomes (R2 = 0.99, RMSE < 1.3%, max difference = 6 μm). Furthermore, the models qualitatively identified the most deformed regions identified with the experiments. In conclusion, the combination of experimental full-field technique and in-silico modelling enabled the development of a promising pipeline to validate bone strength predictors in the elastic range. Further improvements are needed to analyse vertebral post-yield behaviour better.

Since the majority of vertebral compression fractures (VCFs) are asymptomatic, they often go undetected on opportunistic CT scans. To reduce rates of undiagnosed osteoporosis, we developed a deep learning (DL)-based algorithm using 2D/3D U-Nets convolutional neural networks to opportunistically screen for VCF on CT scans. This study aimed to evaluate the performance of the algorithm using external real-world data.

CT scans acquired for various indications other than a suspicion of VCF from January 2019 to August 2020 were retrospectively and consecutively collected. The algorithm was designed to label each vertebra, detect VCF, measure vertebral height loss (VHL) and calculate mean Hounsfield Units (mean HU) for vertebral bone attenuation. For the ground truth, two board-certified radiologists defined if VCF was present and performed the measurements. The algorithm analyzed the scans and the results were compared to the experts' assessments.

A total of 100 patients (mean age: 76.6 years ± 10.1[SD], 72% women) were evaluated. The overall labeling agreement was 94.9% (95%CI: 93.7%-95.9%). Regarding VHL, the 95% limits of agreement (LoA) between the algorithm and the radiologists was [-9.3, 8.6]; 94.1% of the differences lay within the radiologists' LoA and the intraclass correlation coefficient was 0.854 (95%CI: 0.822-0.881). For the mean HU, Pearson's correlation was 0.89 (95%CI: 0.84-0.92; p-value <0.0001). Finally, the algorithm's VCF screening sensitivity and specificity were 92.3% (95%CI: 81.5%-97.9%) and 91.7% (95%CI: 80.0%-97.7%), respectively.

This automated tool for screening and quantification of opportunistic VCF demonstrated high reliability and performance that may facilitate radiologists' task and improve opportunistic osteoporosis assessments.

Vertebral compression fractures (VCFs) cause significant morbidity in the elderly population. This study aimed to determine the difference in pain-related outcomes in the elderly population who suffered vertebral body fractures, treated with balloon kyphoplasty at "early" (<4 weeks) and "late" (>4 weeks) stages. To the best of our knowledge, this has not been previously evaluated in a meta-analysis.

We conducted a systematic literature review as per PRISMA guidelines using databases that included PubMed, EMBASE, Cochrane and Scopus.The search included adults (age 19+) who sustained osteoporotic vertebral compression fractures that were treated with BKP, grouped by time to intervention as compared to conservative treatment to determine impact on radiographic and clinical outcomes.

A total of 9 studies were included from a total of 139 screened records eligible for title and abstract screening after deduplication (39 PubMed, 85 EMBASE, 6 Cochrane, 50 Scopus). The total study sample size was 595. Of these, 6 studies defined their "Early" group as < 4 weeks and were included in our sub-analyses. In regard to pain scores we found a significant improvement in pain score in the early vs. late group. However, we did not find a significant correction in kyphotic correction.

Our study suggests that early treatment of vertebral compression fractures with Balloon Kyphoplasty (BKP), defined as < 4 weeks, provides a statistically significant improvement in pain scores and kyphotic angle correction compared to late treatment (>4 weeks). However, no statistically significant differences were observed in terms of height restoration or the risk of adjacent level fractures. These findings support the benefits of early intervention for pain relief and alignment, though further research is needed to standardize methodologies and assess long-term outcomes.

Vertebral fractures are a common cause of back pain and pain-related functional impairments in elderly patients. Despite their widespread occurrence, vertebral fractures frequently remain underdiagnosed, often leading to suboptimal management and poor clinical outcomes. This review specifically examines the role of physical therapy (PT) in managing vertebral fractures, describing current literature and evidence-based guidelines from the American Physical Therapy Association and the American Academy of Orthopaedic Surgeons. PT following vertebral fractures has been shown to significantly improve back pain and patient-reported outcomes, with studies even showing a correlation between resistance and aerobic training with improved bone mineral density. These findings highlight the need for interdisciplinary care and comprehensive PT interventions to address the growing burden of vertebral fractures as their incidence rises with the aging population.

The spine is a complex structure critical for stability, force transmission, and neural protection, with spinal fractures and spondylolisthesis posing significant challenges to its integrity and function. Spinal fractures arise from trauma, degenerative conditions, or osteoporosis, often affecting transitional zones like the thoracolumbar junction. Spondylolisthesis results from structural defects or degenerative changes, leading to vertebral displacement and potential neurological symptoms. Diagnostic and classification systems, such as AO Spine and TLICS, aid in evaluating instability and guiding treatment strategies. Advances in surgical techniques, including minimally invasive approaches, pedicle screws, interbody cages, and robotic-assisted systems, have improved precision and recovery while reducing morbidity. Vertebral augmentation techniques like vertebroplasty and kyphoplasty offer minimally invasive options for osteoporotic fractures. Despite these innovations, postoperative outcomes vary, with challenges such as persistent pain and hardware complications necessitating tailored interventions. Future directions emphasize predictive analytics and enhanced recovery strategies to optimize surgical outcomes and patient quality of life.

Vertebral compression fractures (VCFs) are common among the elderly, causing significant morbidity, pain, and disability. This study quantitatively analyzes the vertebral height restoration via Kyphoplasty (KP) and Vertebroplasty (VP), along with the cement volume used and leakage percentage. Our meta-analysis of 14 randomized controlled trials (RCTs) compares these objective outcomes, considering cement volume and leakage in both procedures.

Databases searched included Medline, PubMed, and Web of Science using MeSH keywords: 'Kyphoplasty,' 'Vertebroplasty,' 'Vertebral height restoration,' 'Bone cement volume,' and 'Vertebral compression fractures.' Fourteen RCTs were selected, focusing on outcomes such as anterior and central vertebral body height, kyphotic angle, cement volume, and leakage. Data analysis included mean values, standard deviations, ranges, Cohen's d-effect sizes, and standard errors, summarized in a forest plotQuery.

The review included 1456 patients (mean age 71.11 years). Follow-up ranged from 1 to 48 months (mean 15 months). KP showed a greater effect size in restoring anterior and central vertebral body height and kyphotic angle. Combined data from KP and VP showed increases of 3.48 mm (19.14%) in anterior vertebral heights, 4.38 mm in central vertebral heights, and a 2.85-degree correction in kyphotic angle.

Both KP and VP effectively restore vertebral height in VCF patients. KP is superior in restoring anterior and central vertebral body height and correcting kyphotic angle. VP, particularly unilateral, shows higher central vertebral height restoration but higher cement leakage. Standardized reporting and patient-specific volumetric assessments are crucial for optimizing vertebral augmentation procedures.

This study evaluated the performance of a deep learning-based vertebral compression fracture (VCF) detection tool in patients with incidental VCF. The purpose of this study was to validate this tool across multiple sites and multiple vendors.

This was a retrospective, multicenter, multinational blinded study using anonymized chest and abdominal CT scans performed for indications other than VCF in patients ≥50 years old. Images were obtained from 2 teleradiology companies in France and United States and were processed by CINA-VCF v1.0, a deep learning algorithm designed for VCF detection. Ground truth was established by majority consensus across 3 board-certified radiologists. Overall performance of CINA-VCF was evaluated, as well as subset analyses based on imaging acquisition parameters, baseline patient characteristics, and VCF severity. A subgroup was also analyzed and compared with available clinical radiology reports.

Four hundred seventy-four CT scans were included in this study, comprising 166 (35.0%) positive and 308 (65.0%) negative VCF cases. CINA-VCF demonstrated an area under the curve (AUC) of 0.97 (95% CI: 0.96-0.99), accuracy of 93.7% (95% CI: 91.1%-95.7%), sensitivity of 95.2% (95% CI: 90.7%-97.9%), and specificity of 92.9% (95% CI: 89.4%-96.5%). Subset analysis based on VCF severity resulted in a specificity of 94.2% (95% CI: 90.9%-96.6%) for grade 0 negative cases and a specificity of 64.3% (95% CI: 35.1%-87.2%) for grade 1 negative cases. For grades 2 and 3 positive cases, sensitivity was 89.7% (95% CI: 79.9%-95.8%) and 99.0% (95% CI: 94.4%-100.0%), respectively.

CINA-VCF successfully detected incidental VCF and even outperformed clinical reports. The performance was consistent among all subgroups analyzed. Limitations of the tool included various confounding pathologies such as Schmorl's nodes and borderline cases. Despite these limitations, this study validates the applicability and generalizability of the tool in the clinical setting.

This study evaluated the applicability of the classical method, height loss ratio (HLR), for identifying major acute compression fractures in clinical practice and compared its performance with deep learning (DL)-based VCF detection methods. Additionally, it examined whether combining the HLR with DL approaches could enhance performance, exploring the potential integration of classical and DL methodologies.

End-to-End VCF Detection (EEVD), Two-Stage VCF Detection with Segmentation and Detection (TSVD_SD), and Two-Stage VCF Detection with Detection and Classification (TSVD_DC). The models were evaluated on a dataset of 589 patients, focusing on sensitivity, specificity, accuracy, and precision.

TSVD_SD outperformed all other methods, achieving the highest sensitivity (84.46%) and accuracy (95.05%), making it particularly effective for identifying true positives. The complementary use of DL methods with HLR further improved detection performance. For instance, combining HLR-negative cases with TSVD_SD increased sensitivity to 87.84%, reducing missed fractures, while combining HLR-positive cases with EEVD achieved the highest specificity (99.77%), minimizing false positives.

These findings demonstrated that DL-based approaches, particularly TSVD_SD, provided robust alternatives or complements to traditional methods, significantly enhancing diagnostic accuracy for acute VCFs in clinical practice.

Percutaneous vertebroplasty (PVP) is a primary treatment for osteoporotic vertebral compression fractures (OVCF). Historically, surgeons preferred a bilateral approach for PVP; however, this approach may impose greater financial strain on patients. This retrospective study examines the efficacy of the unilateral approach compared to the bilateral approach.

A total of193 patients were categorized into Group A (unilaterally extrapedicular approach) and Group B (bilateral approach) based on the operative method. Efficacy was evaluated using perioperative indicators, follow-up results, and imaging evaluation results.

Out of the 193 patients involved, 169 were eligible for analysis. All patients completed follow-up visits lasting 49-70 months. Compared to Group B, Group A exhibited significantly shorter operation time, puncture duration, amount of bone cement injected, and number of X-ray fluoroscopies (P < 0.05). While initial pain reduction, as measured by the visual analog scale and Oswestry Disability Index scores, was lower in Group A, the difference between the groups narrowed by the final follow-up. At the final imaging follow-up, no statistically significant differences were observed between the two groups regarding the relative height of the injured vertebral bodies and local Cobb angle measurements.

This technique holds the potential for accelerated patient rehabilitation and reduced hospitalization expenses, presenting a promising treatment option for OVCF patients.

This study aims to identify risk factors for vertebral compression fracture and enhance the ability to indicate fracture risk.

A retrospective collection of clinical and imaging data was conducted for patients with vertebral compression fractures and control subjects who underwent quantitative computed tomography scans. Stepwise logistic regression analysis was employed to identify variables associated with fractures, constructing both unadjusted model and adjusted model.

Compared with the non-fracture group, the fracture group showed significant differences in weight, body mass index (BMI), bone mineral density (BMD), vertebral cross-sectional area, paraspinal muscle area and right psoas major muscle fat area (all P < 0.05). Adjusted characteristics analyzed by stepwise logistic regression indicated that bone load index (BLI) (OR = 3.19, P = 0.041), paraspinal muscle fat infiltration (PMFI) (OR = 2.27, P = 0.039), and right psoas major muscle fat infiltration (RPMFI) (OR = 1.08, P = 0.005) were independent risk factors for vertebral fractures. Interaction analysis revealed a positive interaction between BLI and PMFI (OR = 1.95, P = 0.008) as well as RPMFI (OR = 1.53, P = 0.045). Compared with the unadjusted model, the diagnostic performance of the adjusted model was significantly improved (training set IDI: 19.5 %, validation set IDI: 18.4 %, P < 0.001). Correlation analysis demonstrated significant associations between BMD (r = -0.353, P = 0.002), BLI (r = 0.631, P < 0.001), PMFI (r = 0.412, P < 0.001), RPMFI (r = 0.513, P < 0.001), and the degree of vertebral compression.

Under conditions of bone maladaptive loading and muscle degeneration, vertebral bodies may become more susceptible to external forces, increasing the risk of vertebral compression fracture.

The development of novel therapeutics in the field of spinal neurosurgery faces a litany of translational challenges. Achieving precise drug targeting within the confined spaces associated with the spinal cord, canal and vertebra requires the development of next generation delivery systems and devices. These must be capable of overcoming inherent barriers related to drug diffusion, whilst concurrently ensuring optimal drug distribution and retention. In this review, we provide an overview of the most recent advances in the therapeutic management of diseases and disorders affecting the spine, including systems and devices capable of releasing small molecules and biopharmaceuticals that help eliminate pain and restore the mechanical function and stability of the spine. We highlight material-based approaches and minimally invasive techniques that can be employed to provide control over drug release kinetics and improve retention. We also seek to explore how the newest advancements in nanotechnology, biomaterials, additive manufacturing technologies and imaging modalities can be employed in this translational pursuit. Finally, we discuss the landscape of clinical trials and recently approved products aimed at overcoming the complexities associated with drug delivery to the spine.

Spine disorders can cause severe functional limitations, including back pain, decreased pulmonary function, and increased mortality risk. Plain radiography is the first-line imaging modality to diagnose suspected spine disorders. Nevertheless, radiographical appearance is not always sufficient due to highly variable patient and imaging parameters, which can lead to misdiagnosis or delayed diagnosis. Employing an accurate automated detection model can alleviate the workload of clinical experts, thereby reducing human errors, facilitating earlier detection, and improving diagnostic accuracy. To this end, deep learning-based computer-aided diagnosis (CAD) tools have significantly outperformed the accuracy of traditional CAD software. Motivated by these observations, we proposed a deep learning-based approach for end-to-end detection and localization of spine disorders from plain radiographs. In doing so, we took the first steps in employing state-of-the-art transformer networks to differentiate images of multiple spine disorders from healthy counterparts and localize the identified disorders, focusing on vertebral compression fractures (VCF) and spondylolisthesis due to their high prevalence and potential severity. The VCF dataset comprised 337 images, with VCFs collected from 138 subjects and 624 normal images collected from 337 subjects. The spondylolisthesis dataset comprised 413 images, with spondylolisthesis collected from 336 subjects and 782 normal images collected from 413 subjects. Transformer-based models exhibited 0.97 Area Under the Receiver Operating Characteristic Curve (AUC) in VCF detection and 0.95 AUC in spondylolisthesis detection. Further, transformers demonstrated significant performance improvements against existing end-to-end approaches by 4-14% AUC (p-values < 10-13) for VCF detection and by 14-20% AUC (p-values < 10-9) for spondylolisthesis detection.

This work focuses on the growth patterns of the human fourth lumbar vertebra (L4) in a paediatric population, with specific attention to sexual dimorphism. The study aims to understand morphological and density changes in the vertebrae through age-dependent statistical shape and statistical appearance models, which can describe full three-dimensional anatomy. Results show that the main growth patterns are associated with isotropic volumetric vertebral growth, a decrease in the relative size of the vertebral foramen, and an increase in the length of the transverse processes. Moreover, significant sexual dimorphism was demonstrated during puberty. We observe significant age and sex interaction in the anterior vertebral body height (P = 0.005), where females exhibited an earlier increase in rates of vertebral height evolution. Moreover, we also observe an increase in cross-sectional area (CSA) with age (P = 0.020), where the CSA is smaller in females than in males (significant sex effect P = 0.042). Finally, although no significant increase in trabecular bone density with age is observed (P = 0.363), a trend in the statistical appearance model suggests an increase in density with age.

This study aims to assess the limitations of the height loss ratio (HLR) method and introduce a new approach that integrates a deep learning (DL) model to enhance vertebral compression fracture (VCF) detection performance.

We conducted a retrospective study on 589 patients with chronic VCFs. We compared four different methods: HLR-only, DL-only, a combination of HLR and DL for positive VCF, and a combination of HLR and DL for negative VCF. The models were evaluated using dice similarity coefficient, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC).

The combined method (HLR + DL, positive) demonstrated the best performance with an AUROC of 0.968, sensitivity (94.95%), and specificity (90.59%). The HLR-only and the HLR + DL (negative) also showed strong discriminatory power, with AUROCs of 0.948 and 0.947, respectively. The DL-only model achieved the highest specificity (95.92%) but exhibited lower sensitivity (82.83%).

Our study highlights the limitations of the HLR method in detecting chronic VCFs and demonstrates the improved performance of combining HLR with DL models.

This study investigated the relationship between sagittal spinal alignment and musculoskeletal health in older women, particularly those exhibiting diminished bone density without apparent symptoms. The study assessed the impact of global tilt (GT) and the presence of coronal malalignment on spinal health. The research involved 165 asymptomatic older women with an average age of 68.91 ± 7.25 years and average body mass index of 24.26 ± 3.66 kg/m². Comprehensive standing anteroposterior and lateral spine radiographs were used for assessment. Through multivariate linear regression analysis, the study identified significant correlations between increased GT angles and various factors, including coronal malalignment, the C7 slope, and pelvic incidence. This led to the formulation of a predictive GT model: GT = -9.79 + 0.06 × menopausal period + 0.19 × body mass index (BMI)- 0.81 × average T score - 0.11 × grip strength + 3.03 × (presence of coronal malalignment) + 0.08 × sagittal vertical axis (SVA) + 0.12 × C7 slope - 0.35 × upper lumbar lordosis (ULL) - 0.43 × lower lumbar lordosis (LLL) + 0.70 × pelvic incidence (PI), with an adjusted R² of 0.816. The study findings highlight the prevalence of coronal malalignment in this demographic and its significant associations with critical spinal parameters. The proposed GT predictive model may enable development of personalized treatment plans for older women with low bone mass.

Current vertebral augmentation procedures (VAPs) often involve devices associated with bone cement leakage. Tripod-Fix is designed to mitigate the risk of bone cement leakage by expanding in three dimensions to fit a narrower vertebral space. This study enrolled 12 patients diagnosed with osteoprorotic vertebral compression fractures (VCFs) for 12 month follow up. The primary outcomes assessed were changes in the Visual Analog Score (VAS) and Oswestry Disability Index (ODI) before and after treatment. Our results demonstrated significant pain relief with VAS decreasing from 8.58 ± 1.83 to 2.75 ± 1.54 cm and improved mobility with ODI decreasing from 73.67 ± 16.29 to 31.83 ± 23.33% post-treatment and sustained for 12 months. Follow-up radiographs revealed no device-related adverse events such as cement leakage, vertebral body collapse, or adjacent vertebral fractures (AVFs). In addition, the mean anterior height restoration ratio after treatment was 15.87 ± 5.13%. Our preliminary findings suggest that Tripod-Fix exhibits safety and efficacy comparable to the third-generation devices currently utilized for treating osteoporotic VCFs.

Osteoporosis is the most common chronic metabolic bone disease worldwide. Vertebral compression fracture (VCF) is the most common type of osteoporotic fracture. Approximately 700,000 osteoporotic VCFs are diagnosed annually in the USA alone, resulting in an annual economic burden of ~$13.8B. With an aging population, the rate of osteoporotic VCFs and their associated burdens are expected to rise. Those burdens include pain, functional impairment, and increased medical expenditure. Therefore, it is of utmost importance to develop an analytical tool to aid in the identification of VCFs. Computed Tomography (CT) imaging is commonly used to detect occult injuries. Unlike the existing VCF detection approaches based on CT, the standard clinical criteria for determining VCF relies on the shape of vertebrae, such as loss of vertebral body height. We developed a novel automated vertebrae localization, segmentation, and osteoporotic VCF detection pipeline for CT scans using state-of-the-art deep learning models to bridge this gap. To do so, we employed a publicly available dataset of spine CT scans with 325 scans annotated for segmentation, 126 of which also graded for VCF (81 with VCFs and 45 without VCFs). Our approach attained 96% sensitivity and 81% specificity in detecting VCF at the vertebral-level, and 100% accuracy at the subject-level, outperforming deep learning counterparts tested for VCF detection without segmentation. Crucially, we showed that adding predicted vertebrae segments as inputs significantly improved VCF detection at both vertebral and subject levels by up to 14% Sensitivity and 20% Specificity (p-value = 0.028).

Postoperative refracture of osteoporotic compression fractures in the elderly due to underlying illnesses is a complicated matter involving several variables. A multidisciplinary approach involving orthopedics, geriatrics, endocrinology, and rehabilitation medicine is necessary for an investigation of these issues. investigating the impact of older patients' underlying medical conditions on the refracture of osteoporotic compression fractures following surgery.

A retrospective analysis was conducted on 2383 patients between August 2013 and August 2023. 550 patients with comorbid geriatric underlying diseases were screened, 183 patients underwent refractories, and 367 patients were classified as non-refractories. The patients were then divided into two groups: those undergoing refractories and those not, and the underlying diseases of the patients in both groups were examined using ROC curves and unifactorial and multifactorial logistic regression analyses.

Among the patients gathered, the frequency of re-fracture was 33.3%. A statistically significant difference was observed when re-fracture was linked to patients with long-term alcohol consumption, operated vertebrae ≤ 1, hypertension, COPD, diabetes mellitus, stroke sequelae, conservative treatment of coronary heart disease, trauma, mental abnormality, scoliosis, and chronic renal disease. Having hypertension decreased the risk of re-fracture (P = 0.018, OR = 0.548), while alcohol intake ≥ 10years (P = 0.003, OR = 2.165), mental abnormality (P < 0.001, OR = 4.093), scoliosis (P < 0.001, OR = 6.243), chronic kidney disease (P = 0.002, OR = 2.208), and traumatic injuries (P = 0.029, OR = 3.512) were the risk factors examined in a binary logistic regression analysis. The results of multiple linear stepwise regression analysis indicated that re-fracture was more influenced by scoliosis.

Hypertensive disorders were protective factors against the formation of re-fracture, while alcohol intake usage for more than ten years, psychological abnormalities, scoliosis, chronic kidney disease, and trauma were risk factors. Scoliosis had the highest influence on re-fracture.

Osteoporosis and low bone mineral density (BMD) pose significant challenges in adult spinal deformity surgery, increasing the risks of complications such as vertebral compression fractures, hardware failure, proximal junctional kyphosis/failure, and pseudoarthrosis. This narrative review examines the current evidence on bone health optimization strategies for spinal deformity patients. Preoperative screening and medical optimization are crucial, with vitamin D supplementation showing particular benefit. Among the pharmacologic agents, bisphosphonates demonstrate efficacy in improving fusion rates and reducing hardware-related complications, though the effects may be delayed. Teriparatide, a parathyroid hormone analog, shows promise in accelerating fusion and enhancing pedicle screw fixation. Newer anabolic agents like abaloparatide and romosozumab require further study but show potential. Romosozumab, in particular, has demonstrated significant improvements in lumbar spine BMD over a shorter duration compared to other treatments. Surgical techniques like cement augmentation and the use of larger interbody cages can mitigate the risks in osteoporotic patients. Overall, a multifaceted approach incorporating medical optimization, appropriate pharmacologic treatment, and tailored surgical techniques is recommended to improve outcomes in adult spinal deformity patients with compromised bone quality. Future research should focus on optimizing the treatment protocols, assessing the long-term outcomes of newer agents in the spine surgery population, and developing cost-effective strategies to improve access to these promising therapies.

Vertebral compression fractures (VCFs) of the thoracolumbar spine are commonly caused by osteoporosis or result from traumatic events. Early diagnosis of vertebral compression fractures can prevent further damage to patients. When assessing these fractures, plain radiographs are used as the primary diagnostic modality. In this study, we developed a deep learning based fracture detection model that could be used as a tool for primary care in the orthopedic department. We constructed a VCF dataset using 487 lateral radiographs, which included 598 fractures in the L1-T11 vertebra. For detecting VCFs, Mask R-CNN model was trained and optimized, and was compared to three other popular models on instance segmentation, Cascade Mask R-CNN, YOLOACT, and YOLOv5. With Mask R-CNN we achieved highest mean average precision score of 0.58, and were able to locate each fracture pixel-wise. In addition, the model showed high overall sensitivity, specificity, and accuracy, indicating that it detected fractures accurately and without misdiagnosis. Our model can be a potential tool for detecting VCFs from a simple radiograph and assisting doctors in making appropriate decisions in initial diagnosis.

To understand experiences and perceptions on non-pharmacological treatment of vertebral fractures and virtual-care from the perspective of care professionals' (HCPs).

We conducted semi-structured interviews with 13 HCPs within Canada (7 F, 6 M, aged 46 ± 12 years) and performed a thematic and content analysis from a post-positivism perspective.

Two themes were identified: acuity matters when selecting appropriate interventions; and roadblocks to receiving non-pharmacological interventions. We found that treatment options were dependent on the acuity/stability of fracture and were individualized accordingly. Pain medication was perceived as important, but non-pharmacological strategies were also considered helpful in supporting recovery. Participants discussed barriers related to the timely identification of fracture, referral to physiotherapy, and lack of knowledge among HCPs on how to manage osteoporosis and vertebral fractures. HCPs reported positive use of virtual-care, but had concerns related to patient access, cost, and comprehensive assessments.

HCPs used and perceived non-pharmacological interventions as helpful and selected specific treatments based on the recency of fracture and patient symptoms. HCPs' also believed that virtual-care that included an educational component, an assessment by a physiotherapist, and an exercise group was a feasible alternative, but concerns exist and may require further evaluation.

Osteoporosis is significantly associated with fractures and burdens the health of especially older people. Osteoporotic fractures cause pain, disability, and increased mortality. Early diagnosis of osteoporosis allows earlier initiation of treatment, thereby reducing the risk of osteoporotic fractures. Chiropractors encounter potential osteoporotic patients daily, and perform radiological evaluation of these and other patients, including evaluation of X-rays done for other purposes than osteoporosis. Therefore, chiropractors may identify vertebral fractures, vertebral deformity or osteopenia not otherwise suspected or recorded.

This study examines procedures available to the chiropractor to describe conventional X-rays with the focus of osteoporosis related findings. We review the indications for radiological examination in chiropractic practice, and in the realm of osteoporosis we describe radiological methods available for examination of conventional radiographs, and the necessity of inter-disciplinary communication.

National guidelines are available regarding referral for X-rays in chiropractic practice. Standardized protocols ensure image acquisition of the highest quality in the chiropractors' radiological department. Conventional X-ray examination is not indicated on clinical suspicion of osteoporosis alone, as bone mineral density testing is the diagnostic test. Radiological assessment of all available X-rays of patients above the age of 50 years should include evaluation of the bone quality, and hip and vertebral fracture assessment. The Singh index, Genant Semi-Quantitative tool (GSQ), and Algorithm-Based Qualitative method (ABQ) should be used consistently during interpretation. Referral for additional imaging and evaluation should be prompt and systematic when needed.

This article presents an overview of evidence-based radiological procedures for the purpose of promoting early diagnosis of osteoporosis. We present recommendations to the clinicians where we propose an opportunistic evaluation of X-rays, done for any reason, which include systematic evaluation of bone quality, presence of hip and vertebral fractures, and vertebral deformation of all patients above the age of 50 years. Detailed referral to healthcare professionals for further diagnostic evaluation is performed when needed. Consistent, high-quality radiological procedures in chiropractic practices could feasibly contribute to the timely diagnosis of osteoporosis, ultimately minimizing the impact of osteoporosis-related complications on patients' health.

Objective The primary objective of this study was to assess opioid use in the 90 days following kyphoplasty (KP) compared to the period between compression fracture and KP. Methods All patients aged 50-85 who underwent KP following a newly diagnosed vertebral compression fracture (VCF) at a large, urban academic medical center between January 1st, 2015, and January 1st, 2023, were screened for inclusion. Patients were excluded if they had an opioid prescription in the month prior to the compression fracture, had a history of malignancy, or underwent concomitant or other surgical procedures in the 90 days following KP. Opioid measures, including the prescribed amount of morphine milliequivalents (MME) per day, number of opioid days, and total MME (MME per day x number of opioid days), in addition to numerical rating scale (NRS) pain scores, were analyzed pre- and post-KP. Results A total of 27 patients met the eligibility criteria, with a mean age of 69.7 and 59.2% being female. Sixteen patients (59%) had received an opioid prescription between compression fracture and KP (opioid group). The median differences pre- and post-KP in prescribed MMEs per day, number of opioid days, and total MMEs were 17.7 (p=.0009), 11.0 (p=.0004), and 232.5 (p<.0001), respectively. There was a significant difference in NRS pain scores in both the opioid group (6.25, p<.0001) and the non-opioid group (4.36, p<.0001) pre- and post-KP. Conclusion Our findings suggest that KP may be associated with a reduction in both opioid use and pain scores in opioid-naïve patients with VCFs. Larger studies that directly compare KP to conservative management are needed to fully assess the impact of KP on opioid and pain outcome measures.

Vertebral compression fractures (VCFs) occur in 1 to 1.5 million patients in the US each year and are associated with pain, disability, altered pulmonary function, secondary vertebral fracture, and increased mortality risk. A better understanding of VCFs and their management requires preclinical models that are both biomechanically analogous and accessible. We conducted a study using twelve spinal vertebrae (T12-T14) from porcine specimens. We created mathematical simulations of vertebral compression fractures (VCFs) using CT scans for reconstructing native anatomy and validated the results by conducting physical axial compression experiments. The simulations accurately predicted the behavior of the physical compressions. The coefficient of determination for stiffness was 0.71, the strength correlation was 0.88, and the failure of the vertebral bodies included vertical splitting on the lateral sides or horizontal separation in the anterior wall. This finite element method has important implications for the preventative, prognostic, and therapeutic management of VCFs. This study also supports the use of porcine specimens in orthopedic biomechanical research.

Lumbar disc bulging or herniation (LDBH) is one of the major causes of spinal stenosis and related nerve compression, and its severity is the major determinant for spine surgery. MRI of the spine is the most important diagnostic tool for evaluating the need for surgical intervention in patients with LDBH. However, MRI utilization is limited by its low accessibility. Spinal X-rays can rapidly provide information on the bony structure of the patient. Our study aimed to identify the factors associated with LDBH, including disc height, and establish a clinical diagnostic tool to support its diagnosis based on lumbar X-ray findings. In this study, a total of 458 patients were used for analysis and 13 clinical and imaging variables were collected. Five machine-learning (ML) methods, including LASSO regression, MARS, decision tree, random forest, and extreme gradient boosting, were applied and integrated to identify important variables for predicting LDBH from lumbar spine X-rays. The results showed L4-5 posterior disc height, age, and L1-2 anterior disc height to be the top predictors, and a decision tree algorithm was constructed to support clinical decision-making. Our study highlights the potential of ML-based decision tools for surgeons and emphasizes the importance of L1-2 disc height in relation to LDBH. Future research will expand on these findings to develop a more comprehensive decision-supporting model.

Vertebral fragility fractures (VFFs) commonly result from low bone mass and microarchitecture deterioration of bone tissue. spinal orthoses are common non-pharmacological options for managing vertebral fracture pain. However, the effects of spinal orthoses on pain, physical functioning, and quality of life (QoL) are still debated.

This survey aimed to investigate the patients-reported outcomes of a dynamic spinal orthosis prescribed in the routine clinical practice of VFFs management.

This multi-center national-wide prospective cohort study assessed older patients (aged > 60 years) diagnosed with acute VFFs and prescribed with a dynamic spinal orthosis (Spinfast®). A survey questionnaire was realized and included sections on patient characterization, osteoporosis characterization, spinal orthosis, clinical outcomes, pain medications, and osteoporosis medications. The questionnaire was administered at baseline and after three months. A total of 68 patients completed the questionnaire at three months. Most patients had one or two VFFs and were treated with pain medications and osteoporosis medications. Compliance and tolerability of the spinal orthosis were assessed, and clinical outcomes such as pain intensity, physical functioning, and QoL were measured.

The results showed no significant differences in outcomes between age subgroups. Italian physical medicine and rehabilitation physicians were commonly involved in the management of VFFs patients. Sixty-six patients completed the questionnaire. The results showed that pain intensity, physical functioning and QoL improved after three months of spinal orthosis wearing (p< 0.0001).

The correct management of VFFs is mandatory to improve pain and reduce disability, and our findings suggested a positive role of dynamic spinal orthosis to improve the comprehensive management of VFFs patients. However, high-quality research trials are warranted to provide clear recommendations for the correct clinical management of VFF.

The thoracolumbar spine is prone to vertebral compression fractures (VCFs). An injury mechanism known as flexion compression is responsible for thoracolumbar spine compression fractures. Usually, this mechanism affects the longitudinal ligament at the front and the front part of the vertebral body as the first components. Pain is the first and foremost symptom; here we present a case report of a 34-year-old male, who came to the hospital with complaints of back pain, and difficulty in breathing followed by a road traffic accident (RTA). MRI and X-ray investigations were done. The patient was diagnosed with a fracture of the anterolateral aspect of the right fourth and fifth ribs and posterolateral aspect of the sixth rib, acute anterior wedge compression fracture of the L1 vertebra, and bilateral minimal pneumothorax and haemothorax. The patient was managed surgically with post-decompression and spinal fusion at the D12-L2 level. The outcomes used were the Oswestry Low-Back Disability Questionnaire, the numerical pain rating scale, and Manual Muscle Testing (MMT). This case report specifies the physiotherapeutic rehabilitation protocol, mainly focusing on techniques like breathing exercises, and upper limb and lower limb strengthening along with trunk and pelvic floor muscles strengthening.

Vertebral fracture (VF) is one of the most common injuries seen in individuals with osteoporosis, especially in post-menopausal females. There is an increase in bone resorption rate, leading to the destruction of the microarchitecture of bone. A 67-year-old female patient diagnosed with wedge compression fracture of the D12 vertebra, mild compression of the spinal cord, and bilateral foot drop came to a tertiary care hospital, where she underwent spinal fusion at the D11-L1 level and posterior decompression, after which she was referred to physiotherapy, where a patient-tailored treatment protocol was made and implemented over three weeks. Outcome measures like the visual analog scale (VAS), functional independence measure (FIM), and Oswestry's low back disability questionnaire were recorded before and after rehabilitation, and improvement in pain and activities of daily living (ADL) was found. The patient needed mild assistance. There was also improvement in the range and strength of the lower limb muscles. This case report aims to provide a comprehensive treatment protocol for a post-operative spinal fusion and bilateral foot drop patient.

The general objectives of spine surgery are to alleviate pain, restore neurologic function, and prevent or treat spinal deformities or instability. The accumulating expanse of outcome measures has allowed us to more objectively quantify these variables and, therefore, gauge the success of treatments, ultimately improving the quality of the delivered health care. It has become increasingly evident that spinal conditions and their accompanying interventions affect all aspects of a patient's life, including their physical, mental, emotional, and social well-being. This underscores the challenge of creating clinically relevant and accurate outcome measures in spine care, and the reason why there is a growing recognition of the importance of subjective measures such as patient-reported outcome measures, that consider a patients' health-related quality of life. Subjective measures provide valuable insights into patient experiences and perceptions of treatment outcomes, whereas objective measures provide a reproducible glimpse into key radiographic and clinical parameters that are associated with a successful outcome. In this narrative review, we provide a detailed analysis of the most common subjective and objective outcome measures employed in spine surgery, with a special focus on their current role as well as the possible future of outcome reporting.

To evaluate with mechanical testing (MT) using synthetic femurs, an X-shaped femoroplasty technique with polymethyl methacrylate (PMMA), analyzing the results applied to the prophylaxis of proximal femur (PF) fractures caused by low-energy trauma. MT was performed simulating a fall on the greater trochanter, using fifteen Sawbones™ models. They were divided into three experimental groups (n = 5): control (DP) group, drilled without augmentation (DWA) group, and X-shaped augmentation (DX) group. Maximum load, stiffness, absorbed energy and displacement were analyzed primarily in all groups; and secondarily then, morphology and fracture type were verified in all groups while PMMA volume, temperature and time polymerization were analyzed only in the DX group. The MT results obtained for synthetic models respectively in the DP, DWA, and DX groups were: mean maximum load (5562.0 ± 464.8) N, (4798.0 ± 121.2) N, and (7132.0 ± 206.9) N; mean stiffness values (673 ± 64.34) N/mm, (636 ± 8.7) N/mm, and (738 ± 17.13) N/mm, and mean absorbed energy values (36,203 ± 3819) N.mm, (27,617 ± 3011) N.mm, (44,762 ± 3219) N.mm; mean displacement values (13.6 ± 1.45) N, (11.1 ± 0.5) N, and (13.2 ± 0.69) N. The mean volume, temperature reached during filling in the DX group were 9.8 mL, 42.54ºC with 1' 56" of polymerization. The fracture types were similar between the DP and DWA groups, affecting the trochanteric region, as distinctly to those in the DX group, which were restricted to the femoral neck. The values obtained in MT showed statistical significance when analyzed by one-way ANOVA (5%) for maximum load, stiffness, and absorbed energy between groups. In conclusion, X-shaped PMMA augmentation presents a protective biomechanical characteristic against PF fractures generated in synthetic models by boundary a fall on the greater trochanter.

Vertebral compression fracture represents a major health burden for the aging populations globally. However, limited studies exist on the relative efficacy and safety of surgical interventions for vertebral compression fracture. Here, we aim to compare clinical and patient-reported outcomes following vertebral augmentation using balloon kyphoplasty, vertebroplasty, and SpineJack vertebral implant.

An institutional review board-approved, retrospective, multi-institutional review of patients undergoing vertebral augmentation with kyphoplasty, vertebroplasty, and/or a SpineJack vertebral implant was performed between 2018 and 2021. Primary outcomes included pre- and postprocedural pain ratings and vertebral body height restoration. The secondary outcome was a change in the local kyphotic angle. The Kruskal-Wallis test was used to compare outcomes across 3 treatment options. Complications were reviewed during and 30-90 days after the procedure.

Vertebral augmentation of 344 vertebral compression fracture levels was performed during the study period. Sixty-seven patients had 79 kyphoplasty procedures (55% women; mean age, 64.2 [SD, 12.3] years). Seventy-four patients underwent a mean of 84 vertebroplasty procedures (51% women; mean age, 63.5 [SD, 12.8] years), and 61 patients had a mean of 67 SpineJack vertebral implant procedures (57.4% women; mean age, 68.3 [SD, 10.6] years). Following kyphoplasty, vertebroplasty, and SpineJack vertebral implant, pain scores improved significantly (P < .001). Resting pain improvement was similar across the 3 procedures, whereas improvement of "worst pain" was significantly better following a SpineJack vertebral implant compared with kyphoplasty and vertebroplasty (P < .001). Patients with a SpineJack vertebral implant had greater improvement in vertebral body height restoration and local kyphotic angle compared with those undergoing kyphoplasty and vertebroplasty. Adjacent level fractures (6.7% incidence) occurred similarly in the 3 procedure types. There were no other peri- or postoperative complications.

The SpineJack vertebral implant showed equivalent pain improvement compared with vertebroplasty and kyphoplasty, but it had superior vertebral body height restoration and local kyphotic angle improvement. This study supports the SpineJack vertebral implant as a safe and effective alternative (adjunct) for vertebral augmentation, especially in patients with moderate-to-severe vertebral compression fractures for greater improvement in vertebral body height restoration.

Background: Traditional treatment modalities for vertebral compression fractures (VCFs) include bed rest, pain medications, muscle relaxants, back braces, and physical therapy. In cases where conservative treatment proves ineffective, a new procedure called core decompression of the vertebral body is explored. Core decompression of the vertebral body has the potential to lower and stabilize the intraosseous pressure, resulting in enhanced blood circulation, which contributes to pain reduction. In this trial, we evaluated the efficacy of core decompression of the vertebral body in patients with painful VCFs compared with conventional conservative treatment. Methods: This prospective randomized controlled trial was conducted at a tertiary education hospital between June 2017 and May 2020. The participants were randomly assigned in a 1:1 ratio to one of two treatment groups: the core decompression group and the conservative treatment group. The primary outcome measure was the visual analog scale (VAS) pain score of the back 3 months after the procedure. Secondary outcome measures included the Oswestry Disability Index (ODI) for lumbar disabilities, the European Quality of Life-5 Dimensions (EQ-5D) score for quality of life, and radiographic outcomes such as changes in compression rate. Results: All patients underwent the assigned intervention (48 core decompression and 50 conservative treatments). At both 1 month and 3 months, there were no significant differences between the core decompression group and conservative treatment group in VAS pain score (adjusted treatment effect: -0.1 and 2.0; 95% confidence interval [CI]: -7.5 to 7.3 and -5.6 to 9.6; p = 0.970 and p = 0.601, respectively). In addition, there were no significant inter-group differences in ODI and EQ-5D scores throughout the follow-up period (p = 0.917 and 0.704, respectively). Conclusion: Core decompression of the vertebral body did not demonstrate any significant improvement in pain and disability compared to conventional conservative treatment.

This comprehensive review delves into the intricate landscape of vertebral height restoration after balloon kyphoplasty in cases of vertebral compression fractures. With a comprehensive examination of procedural intricacies, radiological evaluations, clinical outcomes, and influential factors, a nuanced comprehension unfolds. Beyond its immediate alleviation of pain, vertebral height restoration emerges as a linchpin in enhancing spinal alignment, fostering functional recuperation, and augmenting the overall quality of life. This review underscores the pivotal role of balloon kyphoplasty, transcending its mere medical utility to become a conduit for renewed independence and well-being among individuals grappling with vertebral compression fractures. The ongoing advancements in medical science and the continued pursuit of research stand poised to amplify the significance of vertebral height restoration, manifesting a promising horizon for individuals seeking respite from pain, a revitalised capacity for movement, and a life unburdened by its constraints.

To train an artificial neural network model using 3D radiomic features to differentiate benign from malignant vertebral compression fractures (VCFs) on MRI. This retrospective study analyzed sagittal T1-weighted lumbar spine MRIs from 91 patients (average age of 64.24 ± 11.75 years) diagnosed with benign or malignant VCFs from 2010 to 2019, of them 47 (51.6%) had benign VCFs and 44 (48.4%) had malignant VCFs. The lumbar fractures were three-dimensionally segmented and had their radiomic features extracted and selected with the wrapper method. The training set consisted of 100 fractured vertebral bodies from 61 patients (average age of 63.2 ± 12.5 years), and the test set was comprised of 30 fractured vertebral bodies from 30 patients (average age of 66.4 ± 9.9 years). Classification was performed with the multilayer perceptron neural network with a back-propagation algorithm. To validate the model, the tenfold cross-validation technique and an independent test set (holdout) were used. The performance of the model was evaluated using the average with a 95% confidence interval for the ROC AUC, accuracy, sensitivity, and specificity (considering the threshold = 0.5). In the internal validation test, the best model reached a ROC AUC of 0.98, an accuracy of 95% (95/100), a sensitivity of 93.5% (43/46), and specificity of 96.3% (52/54). In the validation with independent test set, the model achieved a ROC AUC of 0.97, an accuracy of 93.3% (28/30), a sensitivity of 93.3% (14/15), and a specificity of 93.3% (14/15). The model proposed in this study using radiomic features could differentiate benign from malignant vertebral compression fractures with excellent performance and is promising as an aid to radiologists in the characterization of VCFs.

A machine learning model using clinical, laboratory, and imaging data was developed to predict 10-year risk of menopause-related osteoporosis. The resulting predictions, which are sensitive and specific, highlight distinct clinical risk profiles that can be used to identify patients most likely to be diagnosed with osteoporosis.

The aim of this study was to incorporate demographic, metabolic, and imaging risk factors into a model for long-term prediction of self-reported osteoporosis diagnosis.

This was a secondary analysis of 1685 patients from the longitudinal Study of Women's Health Across the Nation using data collected between 1996 and 2008. Participants were pre- or perimenopausal women between 42 and 52 years of age. A machine learning model was trained using 14 baseline risk factors-age, height, weight, body mass index, waist circumference, race, menopausal status, maternal osteoporosis history, maternal spine fracture history, serum estradiol level, serum dehydroepiandrosterone level, serum thyroid-stimulating hormone level, total spine bone mineral density, and total hip bone mineral density. The self-reported outcome was whether a doctor or other provider had told participants they have osteoporosis or treated them for osteoporosis.

At 10-year follow-up, a clinical osteoporosis diagnosis was reported by 113 (6.7%) women. Area under the receiver operating characteristic curve of the model was 0.83 (95% confidence interval, 0.73-0.91) and Brier score was 0.054 (95% confidence interval, 0.035-0.074). Total spine bone mineral density, total hip bone mineral density, and age had the largest contributions to predicted risk. Using two discrimination thresholds, stratification into low, medium, and high risk, respectively, was associated with likelihood ratios of 0.23, 3.2, and 6.8. At the lower threshold, sensitivity was 0.81, and specificity was 0.82.

The model developed in this analysis integrates clinical data, serum biomarker levels, and bone mineral densities to predict 10-year risk of osteoporosis with good performance.

To understand perceptions on rehabilitation after vertebral fracture, non-pharmacological strategies, and virtual care from the perspective of individuals living with vertebral fractures.

We conducted semi-structured interviews online and performed a thematic and content analysis from a post-positivism perspective.

Ten individuals living with osteoporotic vertebral fractures (9F, 1 M, aged 71  ±  8 years).

Five themes emerged: pain is the defining limitation of vertebral fracture recovery; delayed diagnosis impacts recovery trajectory; living with fear; being dissatisfied with fracture management; and "getting back into the game of life" using non-pharmacological strategies.

Participants reported back pain and an inability to perform activities of daily living, affecting psychological and social well-being. Physiotherapy, education, and exercise were considered helpful and important to patients; however, issues with fracture identification and referral limited the use of these options. Participants believed that virtual rehabilitation was a feasible and effective alternative to in-person care, but perceived experience with technology, cost, and individualization of programs as barriers.

Vertebral compression fractures (VCFs) can have a variety of etiologies, including trauma, osteoporosis, or neoplastic infiltration. Osteoporosis related fractures are the most common cause of VCFs and have a high prevalence among all postmenopausal women with increasing incidence in similarly aged men. Trauma is the most common etiology in those >50 years of age. However, many cancers, such as breast, prostate, thyroid, and lung, have a propensity to metastasize to bone, which can lead to malignant VCFs. Indeed, the spine is third most common site of metastases after lung and liver. In addition, primary tumors of bone and lymphoproliferative diseases such as lymphoma and multiple myeloma can be the cause of malignant VCFs. Although patient clinical history could help raising suspicion for a particular disorder, the characterization of VCFs is usually referred to diagnostic imaging. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances in which evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

This study aimed to examine the key circulating miRNAs in the plasma of patients with osteoporotic vertebral compression fracture and assess their potential role as diagnostic biomarkers and explore their function in vitro and in vivo.

Weighted gene co-expression network analysis (WGCNA) was applied to identify hub miRNAs for subsequent analysis. The candidate miRNAs were tested using plasma from 144 patients and the results were applied to construct receiver operating characteristic (ROC) curves to assess their diagnostic value. In addition, the function of the target microRNA was validated in MC3T3-E1 cells, human bone marrow-derived mesenchymal stromal cells (BMSCs), and an ovariectomized (OVX) mouse model.

Seven modules were obtained by WGCNA analysis. The expression levels of circulating miR-107 in the red module were significantly lower in osteoporotic patients than in healthy controls. In addition, miR-107 provided discrimination with an AUC > 85 % by ROC analyses to differentiate women osteoporosis patients from healthy controls and differentiate women osteoporotic patients with vertebral compression fractures from osteoporotic patients without vertebral compression fractures. In vitro experiments revealed that miR-107 levels were increased in osteogenically induced MC3T3-E1 cells and BMSCs and transfection with synthetic miR-107 could promote bone formation. Lastly, the bone parameters were improved by miR-107 upregulation in OVX mice.

Our findings show that circulating miR-107 plays an essential role in facilitating osteogenesis and may be a useful diagnostic biomarker and therapeutic target in osteoporosis.

To conduct a systematic review on the effect of robot-assisted minimally invasive surgery (R-MIS) on the clinical outcomes and complications of patients with osteoporotic vertebral compression fractures (OVCFs).

The researchers searched the papers published on PubMed, The Cochrane Library, Web of Science, Embase, Scopus, Ovid MEDLINE, Wiley Online Library, China National Knowledge Infrastructure (CNKI), Chinese biomedical literature service system (SinoMed), and China Medical Association Data. The standardized mean difference (SMD) or mean difference (MD), relative risk (RR), and 95% confidence interval (CI) were calculated. Besides, the data was merged through the random-effect model or common-effect model. A meta-regression mixed-effects single-factor model was utilized to analyze the sources of heterogeneity.

Twelve studies were included, involving 1042 OVCFs cases. The prognosis of patients treated with R-MIS was significantly improved, such as Oswestry disability index (ODI) score (MD = -0.65, P = 0.0171), Cobb's angles (MD = -1.03, P = 0.0027), X-ray fluoroscopy frequency (SMD = -2.41, P < 0.0001), Length of hospital stay (MD = -0.33, P = 0.0002), and Cement leakage (RR = 0.37, P < 0.0001). However, no obvious improvement was found in the results of Visual analog scale (VAS) score (MD = -0.16, P = 0.1555), Volume of bone cement (MD = 0.22, P = 0.8339), and Operation time (MD = -3.20, P = 0.3411) after being treated by R-MIS. The meta-regression analysis demonstrated that R-MIS presented no significant impact on the covariates of VAS and Operation time.

R-MIS can significantly reduce the patients' ODI, Cobb's angles, X-ray fluoroscopy frequency, and Cement leakage ratio, and shorten the Length of hospital stay. Therefore, R-MIS may be an effective method to promote the patients' functional recovery, correct spinal deformity, reduce the X-ray fluoroscopy frequency, shorten the Length of hospital stay, and reduce the complications of OVCFs bone Cement leakage.