Differentiation of Traumatic Osteoporotic and Non-Osteoporotic Vertebral AO A3 Fractures by Analyzing the Posterior Edge Morphology-A Retrospective Feasibility Study

In vivo bone regeneration performance of hydroxypropyl methylcellulose hydrogel-based composite bone cements in ovariectomized and ovary-intact rats: a preliminary investigation

The objective of this study is to fabricate and develop hydroxypropyl methylcellulose (HPMC) hydrogel (HG)-based composite bone cements with incorporation of hydroxyapatite (HA), beta-tricalcium phosphate (β-TCP), and with/without polymethylmethacrylate (PMMA) for vertebroplasty. For animal study, twenty female Wister rats (250-300 g, 12 weeks of age) were divided into four groups including a two non-ovariectomy (NOVX) groups and two ovariectomy (OVX)-induced osteoporosis groups. Two prepared biocomposites including HG/β-TCP/HA and HG/β-TCP/HA/PMMA were injected into the tibial defects of both OVX and NOVX rats for evaluating in vivo osteogenesis after 12 weeks. Micro-computed tomography and histological analysis using hematoxylin and eosin (H&E) and Masson's trichrome stains of the two composite cements implanted into the tibial defects of OVX and NOVX rats revealed enhanced bone regeneration potential. However, no statistically significant differences were noted among the groups based on new bone formation, demonstrating that the injected composite cements showed similar osteogenesis effects in both OVX and NOVX rats. These findings suggest that the newly developed composite bone cement composed of HG, β-TCP, HA and/or PMMA may be a promising and professional tool for treating osteoporotic and non-osteoporotic vertebral fractures.

Application of machine learning in prediction of bone cement leakage during single-level thoracolumbar percutaneous vertebroplasty

BACKGROUND

In the elderly, osteoporotic vertebral compression fractures (OVCFs) of the thoracolumbar vertebra are common, and percutaneous vertebroplasty (PVP) is a common surgical method after fracture. Machine learning (ML) was used in this study to assist clinicians in preventing bone cement leakage during PVP surgery.

METHODS

The clinical data of 374 patients with thoracolumbar OVCFs who underwent single-level PVP at The First People's Hospital of Chenzhou were chosen. It included 150 patients with bone cement leakage and 224 patients without it. We screened the feature variables using four ML methods and used the intersection to generate the prediction model. In addition, predictive models were used in the validation cohort.

RESULTS

The ML method was used to select five factors to create a Nomogram diagnostic model. The nomogram model's AUC was 0.646667, and its C value was 0.647. The calibration curves revealed a consistent relationship between nomogram predictions and actual probabilities. In 91 randomized samples, the AUC of this nomogram model was 0.7555116.

CONCLUSION

In this study, we invented a prediction model for bone cement leakage in single-segment PVP surgery, which can help doctors in performing better surgery with reduced risk.