Fracture-free probability and predictors of new symptomatic fractures in sandwich, ordinary-adjacent, and non-adjacent vertebrae: a vertebra-specific survival analysis

Biomechanical analysis of sandwich vertebrae in osteoporotic patients: finite element analysis

Objective

The aim of this study was to investigate the biomechanical stress of sandwich vertebrae (SVs) and common adjacent vertebrae in different degrees of spinal mobility in daily life.

Materials and methods

A finite element model of the spinal segment of T10-L2 was developed and validated. Simultaneously, T11 and L1 fractures were simulated, and a 6-ml bone cement was constructed in their center. Under the condition of applying a 500-N axial load to the upper surface of T10 and immobilizing the lower surface of L2, moments were applied to the upper surface of T10, T11, T12, L1, and L2 and divided into five groups: M-T10, M-T11, M-T12, M-L1, and M-L2. The maximum von Mises stress of T10, T12, and L2 in different groups was calculated and analyzed.

Results

The maximum von Mises stress of T10 in the M-T10 group was 30.68 MPa, 36.13 MPa, 34.27 MPa, 33.43 MPa, 26.86 MPa, and 27.70 MPa greater than the maximum stress value of T10 in the other groups in six directions of load flexion, extension, left and right lateral bending, and left and right rotation, respectively. The T12 stress value in the M-T12 group was 29.62 MPa, 32.63 MPa, 30.03 MPa, 31.25 MPa, 26.38 MPa, and 26.25 MPa greater than the T12 stress value in the other groups in six directions. The maximum stress of L2 in M-T12 in the M-L2 group was 25.48 MPa, 36.38 MPa, 31.99 MPa, 31.07 MPa, 30.36 MPa, and 32.07 MPa, which was greater than the stress value of L2 in the other groups. When the load is on which vertebral body, it is subjected to the greatest stress.

Conclusion

We found that SVs did not always experience the highest stress. The most stressed vertebrae vary with the degree of curvature of the spine. Patients should be encouraged to avoid the same spinal curvature posture for a long time in life and work or to wear a spinal brace for protection after surgery, which can avoid long-term overload on a specific spine and disrupt its blood supply, resulting in more severe loss of spinal quality and increasing the possibility of fractures.

Is the incidence of sandwich vertebral fracture higher than that of ordinary adjacent vertebral fracture after PKP?

OBJECTIVE

To compare the incidence of fracture between sandwich vertebra and ordinary adjacent vertebra after percutaneous kyphoplasty (PKP).

METHOD

We analyzed 225 consecutive patients with osteoporotic vertebral compression fractures who underwent PKP between January 2016 and December 2020 at our medical institution. The sandwich vertebrae was located between 2 cement-augmented vertebra and was followed for at least 12 months. The clinical data of patients with sandwich vertebra and ordinary adjacent vertebra were recorded, and the incidence of postoperative fracture between sandwich vertebra and ordinary adjacent vertebra was compared.

RESULTS

The mean continuous follow-up time was 31.30 ± 18.04 months in patients with sandwich vertebra and 25.85 ± 7.96 months in patients with ordinary adjacent vertebra. It should be noted that the incidence of sandwich vertebral fractures was 10.00%, which was not statistically higher than 3.26% for ordinary adjacent vertebral fractures. However, a significant difference was observed in the cement volume of single vertebral body, procedure time, and bleeding.

CONCLUSION

Although the volume of cement in a single vertebral body is less and the procedure time and bleeding are more, the incidence of sandwich vertebral fracture is not higher than that of ordinary adjacent vertebral body.

Novel Radiomics-Clinical Model for the Noninvasive Prediction of New Fractures After Vertebral Augmentation

PURPOSE

To investigate the noninvasive prediction model for new fractures after percutaneous vertebral augmentation (PVA) based on radiomics signature and clinical parameters.

METHODS

Data from patients who were diagnosed with osteoporotic vertebral compression fracture (OVCF) and treated with PVA in our hospital between May 2014 and April 2019 were retrospectively analyzed. Radiomics features were extracted from T1-weighted magnetic resonance imaging (MRI) of the T11-L5 segments taken before PVA. Different radiomics models was developed by using linear discriminant analysis (LDA), multilayer perceptron (MLP), and stochastic gradient descent (SGD) classifiers. A nomogram was constructed by integrating clinical parameters and Radscore that calculated by the best radiomics model. The model performance was quantified in terms of discrimination, calibration and clinical usefulness.

RESULT

Four clinical parameters and 16 selected radiomics features were used for model development. The clinical model showed poor discrimination capability with area under the curves (AUCs) yielding of 0.522 in the training dataset and 0.517 in the validation dataset. The LDA, MLP and SGD classifier-based radiomics model had achieved AUCs of 0.793, 0.810, and 0.797 in the training dataset, and 0.719, 0.704, and 0.725 in the validation dataset, respectively. The nomogram showed the best performance with AUCs achieving 0.810 and 0.754 in the training and validation datasets, respectively. The decision curve analysis demonstrated the net benefit of the nomogram was higher than that of other models.

CONCLUSION

Our findings indicate that combining clinical features with radiomics features from pre-augmentation T1-weighted MRI can be used to develop a nomogram that can predict new fractures in patients after PVA.