Mechanical testing and biomechanical CT analysis to assess vertebral flexion strength of Chinese cadavers

Bone mineral density surrounding the screw thread predicts the risk of pedicle screw loosening

BACKGROUND

Screw loosening remains a serious complication for patients undergoing pedicle screw fixation surgeries. An accurate risk prediction is significant for prevention of screw loosening through preoperative planning. In this study, we proposed a novel index, namely the bone mineral density surrounding the screw thread (thread BMD), and tested its predictability in screw loosening.

METHODS

86 screws (18 loosening and 68 non-loosening) from L3-L5 of 20 patients who experienced pedicle screw loosening were analyzed. The preoperative and postoperative quantitative CT scans of the same vertebra were spatially registered and a helix-based approach was developed to extract the thread BMD. BMDs of the vertebral body, the pedicle and the screw trajectory were also measured from the preoperative CT scans. Finite element analysis was conducted to determine pullout strength and tissue failure around the screw. Receiver operating characteristic (ROC) curve analysis was used to assess the performances of all BMD indices and pullout strength in predicting screw loosening. Linear regression was used to examine correlations between different BMD indices and screw pullout strength.

RESULTS

The thread BMD had the greatest value of area under the curve (AUC = 0.73, p = 0.004) compared to vertebral BMD (AUC = 0.51, p = 0.923), pedicle BMD (AUC = 0.56, p = 0.474) and trajectory BMD (AUC = 0.67, p = 0.020). Also, the thread BMD showed a stronger correlation with the pullout strength (r = 0.83, p < 0.001) than vertebral BMD (r = 0.59, p < 0.001), pedicle BMD (r = 0.65, p < 0.001) and trajectory BMD (r = 0.60, p < 0.001).

CONCLUSIONS

We developed a novel approach to measure a newly-defined thread BMD, which indicates superior capacities over other BMD indices in predicting pedicle screw loosening.

Using QCT for the prediction of spontaneous age- and gender-specific thoracolumbar vertebral fractures and accompanying distant vertebral fractures

PURPOSE

To investigate the value and age- and gender-specific threshold values of bone mineral density (BMD) by quantitative computed tomography (QCT) for the prediction of spontaneous thoracolumbar vertebral fractures and thoracolumbar junction fractures accompanying distant vertebral fractures.

METHODS

Among the 556 patients included, 68 patients had thoracolumbar vertebral fractures (12 patients with distant vertebral fractures, 56 patients without distant vertebral fractures) and 488 patients had no vertebral fractures. All patients were grouped by gender and age. According to the principle of Youden index, the threshold values were calculated from receiver operating characteristic (ROC) curves.

RESULTS

The threshold values for predicting thoracolumbar vertebral fractures were 89.8 mg/cm3 for all subjects, 90.1 mg/cm3 for men, and 88.6 mg/cm3 for women. The threshold values for men aged < 60 years old and ≥ 60 years old were 117.4 mg/cm3 and 87.5 mg/cm3, respectively. The threshold values for women aged < 60 years old and ≥ 60 years old were 88.6 and 68.4 mg/cm3, respectively. The threshold value for predicting spontaneous thoracolumbar junction fractures with distant vertebral fractures was 62.7 mg/cm3.

CONCLUSIONS

QCT provides a good ability to predict age- and gender-specific spontaneous thoracolumbar vertebral fractures, and to further predict spontaneous thoracolumbar junction fractures with distant vertebral fractures.

Craniocaudal toggling increases the risk of screw loosening in osteoporotic vertebrae

BACKGROUND AND OBJECTIVE

Screw loosening remains a prominent problem for osteoporotic patients undergoing pedicle screw fixation surgeries but its underlying mechanisms are not fully understood. This study sought to examine the interactive effect of craniocaudal or axial cyclic loading (toggling) and osteoporosis on screw fixation.

METHODS

QCT-based finite element models of normal (n = 7; vBMD = 156 ± 13 mg/cm³) and osteoporotic vertebrae (n = 7; vBMD = 72 ± 6 mg/cm³) were inserted with pedicle screws and loaded with or without craniocaudal toggling. Among them, a representative normal vertebra (age: 55; BMD: 140 mg/cm³) and an osteoporotic vertebra (age: 64; BMD: 79 mg/cm³) were also loaded with or without axial toggling. The individual and interactive effects of craniocaudal toggling and osteoporosis on screw fixation strength (the force when the pull-up displacement of the screw head reached 1 mm) and bone tissue failure (characterized by equivalent plastic strain) were examined by repeated measure ANOVA.

RESULTS

A significant interactive effect between craniocaudal toggling and osteoporosis on screw fixation strength was detected (p = 0.008). Specifically, craniocaudal toggling led to a marked decrease in the fixation strength (68%, p < 0.05) and stiffness (83%, p < 0.05) only in the osteoporotic vertebrae but had no effect on screw fixation strength and stiffness of the normal vertebrae (p > 0.05). Likewise, most of the bone tissues around the screw in the osteoporotic vertebrae yielded following craniocaudal toggling whereas this result was not seen in the normal vertebrae. The axial toggling had no significant effect on bone tissue failure as well as pedicle screw fixation in normal or osteoporotic vertebrae.

CONCLUSIONS

Craniocaudal toggling substantially reduces the screw fixation strength of the osteoporotic vertebrae by progressively increasing tissue failure around the screw, and therefore may contribute to the higher rates of screw loosening in osteoporotic compared to normal patients, whereas axial toggling is not a risk factor for pedicle screw loosening in normal or osteoporotic patients.

Biomechanical MRI detects reduced bone strength in subjects with vertebral fractures

Vertebral fracture is one of the most serious consequences of osteoporosis. Estimation of vertebral strength from magnetic resonance imaging (MRI) scans may provide a new approach for the prediction of vertebral fractures. To that end, we sought to establish a biomechanical MRI (BMRI) method to compute vertebral strength and test its ability to distinguish fracture from non-fracture subjects. This case-control study included 30 subjects without vertebral fractures and 15 subjects with vertebral fractures. All subjects underwent MRI with a mDIXON-Quant sequence and quantitative computed tomography (QCT), from which proton fat fraction-based bone marrow adipose tissue (BMAT) content and volumetric bone mineral density (vBMD) were measured, respectively. Nonlinear finite element analysis was applied to MRI and QCT scans of L2 vertebrae to compute vertebral strength (BMRI- and BCT-strength). The differences in BMAT content, vBMD, BMRI-strength and BCT-strength between the two groups were examined by t-tests. Receiver operating characteristic (ROC) analysis was performed to assess the ability of each measured parameter to distinguish fracture from non-fracture subjects. Results showed that the fracture group had 23 % lower BMRI-strength (P < .001) and 19 % higher BMAT content (P < .001) than the non-fracture group, whereas no significant difference in vBMD was detected between the two groups. A poor correlation was found between vBMD and BMRI-strength (R² = 0.33). Compared to vBMD and BMAT content, BMRI- and BCT-strength had the larger area under the curve (0.82 and 0.84, respectively) and provided better sensitivity and specificity in separating fracture from non-fracture subjects. In conclusion, BMRI is capable of detecting reduced bone strength in patients with vertebral fracture, and may serve as a new approach for risk assessment of vertebral fracture.

Biomechanical CT-computed bone strength predicts the risk of subsequent vertebral fracture

Following primary fractures and percutaneous kyphoplasty (PKP), patients have a high risk of incurring a subsequent vertebral fracture (SVF). Given that SVF is a consequence of mechanical deterioration of the vertebra, we sought to examine whether vertebral strength derived from QCT-based finite element analysis (i.e., BCT) can predict the risk of SVF. Sixty-six patients who underwent PKP were categorized into two groups: control or non-SVF group (age: 70 ± 7 years; n = 40) and SVF group (age: 69 ± 8 years; n = 26). BCT was performed on L4 or L3 vertebrae to noninvasively measure vertebral strength. Vertebral strength was also estimated based upon the geometry and material properties of the vertebra. Additionally, trabecular volumetric bone mineral density (vBMD) and L1 Hounsfield unit (HU) were measured. t-Test, χ² test or Mann Whitney U test were used to compare differences in these parameters between the two groups. The predictive abilities of BCT strength and other measured parameters were evaluated using the receiver operating characteristic (ROC) analysis. Results showed no significant difference in either vBMD or L1 HU between the control and SVF groups (p > 0.05), whereas BCT-computed and estimated vertebral strength values were significantly reduced by 33 % and 24 % for the SVF group relative to the non-SVF group, respectively. ROC curve indicated that BCT strength had the largest area under the curve, compared to other parameters. These results suggest that BCT-computed vertebral strength may serve as a surrogate for assessing risk of SVF.