MRI-based pedicle bone quality score: correlation to quantitative computed tomography bone mineral density and its role in quantitative assessment of osteoporosis.

BACKGROUND CONTEXT

Bone quality in the pedicle region generally determines screw pullout strength, insertion torque, and vertebral body loading characteristics. Dual-energy X-ray absorptiometry (DEXA), as the gold standard for evaluating bone mineral density (BMD), cannot measure the BMD of specific parts, such as pedicle, and DEXA is limited in many ways. Recent studies have shown a correlation between the magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score and BMD measured using DEXA or quantitative computed tomography (QCT). However, no studies have been reported on the MRI-based pedicle bone quality (PBQ) score. Moreover, few studies have investigated the relationship between MRI-based PBQ and osteoporosis.

PURPOSE

To create a new site-specific MRI-based PBQ assessment method and assess its diagnostic capacity in patients with normal BMD and osteopenia/osteoporosis.

STUDY DESIGN/SETTING: A retrospective study.

PATIENT SAMPLE

A total of 156 patients underwent lumbar fusion surgery for chronic low back pain at our hospital between 2021 and 2022, with lumbar QCT and T1-weighted MRI performed before surgery.

OUTCOME MEASURES

Correlation of the PBQ score with QCT BMD, and the association between the PBQ score and presence of osteopenia/osteoporosis.

METHODS

BMD of the lumbar was calculated as the mean BMD of the L1 and L2 vertebral bodies on the basis of asynchronous QCT measurements. The PBQ score, which is the average of the bone quality values of both pedicles on the basis of site-specific T1-weighted sagittal MRI images, was calculated by dividing the median signal intensity of the L1-L4 pedicles by the signal intensity of the cerebrospinal fluid at the L3 level. The interobserver reliability of the PBQ score was assessed using the intraclass correlation coefficient (ICC). A receiver operating characteristic curve was drawn, and the area under the curve (AUC) was calculated to assess the predictive performance of PBQ for osteoporosis. The PBQ score was compared with QCT BMD, as the gold standard, using Pearson correlation analysis.

RESULTS

In total, 156 patients participated in this study, including 51 in the Normal BMD group and 105 in the osteopenia/osteoporosis group. The PBQ score in the osteopenia/osteoporosis group was significantly higher than that in the normal BMD group (3.19±0.55 vs 2.84±0.51, p<.001). The VBQ and PBQ scores were calculated by 2 authors and were in good agreement (intraclass correlation coefficient=0.949 and 0.929, respectively). Pearson's test showed a significant negative correlation between PBQ and QCT BMD (r=-0.4887, p<.001). The optimal cutoff PBQ score to differentiate patients with osteopenia/osteoporosis from those with normal BMD was 3.160, with a sensitivity of 66.7%, specificity of 72.5%, and AUC of 0.776. The PBQ score correlated more strongly with QCT BMD (r=-0.4887) than VBQ (r=-0.4078).

CONCLUSIONS

In this study, we propose a novel, MRI-based pedicle-specific bone quality score. This is the first study to investigate the relationship between the PBQ score and QCT BMD. The PBQ score showed diagnostic utility, differentiating between patients with osteopenia/osteoporosis and those with normal BMD (AUC=0.776), and the PBQ score correlated more strongly with QCT BMD than VBQ.