Magnetic resonance imaging-based bone and muscle quality parameters for predicting clinical subsequent vertebral fractures after percutaneous vertebral augmentation.

Early human evidence such as case series or small samples is exploring possible benefits.

• Level A · Stronger Clinical Evidence
• Level B · Emerging clinical evidence with positive signals
• Level C · Early human research exploring benefits
• Level D · Scientific groundwork from lab and animal studies
• Emerging · Emerging topic under active research

Abstract (original English)

Clinical subsequent vertebral fracture (SVF) is a common complication following percutaneous vertebral augmentation treatment for osteoporotic vertebral compression fracture. Magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score, cross-sectional area (CSA), and degree of fat infiltration (DFI) of paravertebral muscles are effective predictors of spinal surgery-related complications. However, the relationship between these parameters and SVF remains unclear. The purpose of this study was to evaluate the utility of these MRI-based bone and muscle quality parameters for predicting SVF after percutaneous vertebral augmentation. This retrospective study included consecutive patients with osteoporotic vertebral compression fracture treated with percutaneous vertebral augmentation at Xuzhou Central Hospital between January 2017 and December 2020. Clinical SVF was diagnosed if there was new episode of back pain and a confirmed acute fracture on MRI. Noncontrast T1-weighted MRI and axial T2-weighted MRI were used to determine the VBQ score and measure CSA and DFI, respectively. A multivariable logistic regression analysis adjusted for confounding factors was performed to determine the correlation between VBQ score, DFI, CSA, and SVF. Receiver operating characteristic curves were plotted, and the area under the curve (AUC) was calculated to evaluate the predictive abi

Evidence level

Early human evidence such as case series or small samples is exploring possible benefits.

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