Combination of vertebral bone quality scores from different magnetic resonance imaging sequences improves prognostic value for the estimation of osteoporosis

Abstract

Background Context

Recent findings revealed a correlation between vertebral bone quality based on T1-weighted (VBQT1) magnetic resonance imaging (MRI) and volumetric bone mass density (vBMD) measured using quantitative computerized tomography. The coherence of VBQ for other MRI sequences, such as T2 or short tau inversion recovery (STIR), has not been examined. The combination of different VBQs has not been studied. Purpose

The aims of the study were to confirm the correlation between VBQT1 and vBMD and to examine VBQs from other MRI sequences and their combination with vBMD. Study Design/Setting

This was a retrospective cross-sectional study. Patient Sample

The sample consisted of patients older than 18 years, who received treatment at a level-one university spine center of the German Spine Society for degenerative or traumatic reasons in 2017–2021. Outcome Measures

The outcome measures were the correlation of VBQs from different MRI sequences with vBMD and the association of VBQs with osteopenia/osteoporosis. Methods

Patients’ VBQ was calculated based on the signal intensities of the vertebral bodies L1–4 in T1-, T2-, and STIR-weighted MRI. The VBQ was standardized according to the signal intensity of the cerebrospinal fluid. The vBMD was determined using data from a calibrated scanner (SOMATOM Definition AS+) and processed with CliniQCT (Mindways Software, Inc., USA). Groups were divided according to vBMD into the following groups: (I) osteoporosis/osteopenia (< 120 mg/m3) and (II) healthy (≥120 mg/m3). An analysis of the correlation between various VBQs and vBMD as well as receiver operating characteristic (ROC) and binary regression analyses were performed for the prediction of osteoporosis/osteopenia. Results

We included 136 patients (women: 56.6%) in the study (69.7 ± 15.0 years). According to vBMD, 108 patients (79.4%) had osteoporosis/osteopenia. Women were affected significantly more often than men (p = .045) and had significantly higher VBQT1 and VBQT2 values than men (VBQT1: p = .048; VBQT2: p = .013). VBQT1 and VBQT2 values were significantly higher in patients with osteoporosis/osteopenia than in healthy persons (VBQT1: p<.001; VBQT2: p = .025). VBQT1 and VBQT2 were significantly negatively correlated with vBMD with a moderate effect size (p<.001), while VBQSTIR was not significantly correlated with vBMD, although it showed a positive coherence. The combination of different VBQs in terms of VBQT1 × VBQT2 / VBQSTIR distinctly increased the effect size of the negative correlation with vBMD compared to VBQ alone. A cutoff value for VBQT1 × VBQT2 / VBQSTIR of 2.9179 achieved a sensitivity of 80.0%, a specificity of 75.0%, and an area under the curve (AUC) of 0.775 for the determination of osteoporosis. The mathematical model derived from the binary logistic regression showed an excellent AUC of 0.846. Conclusions

This study confirms a significant correlation between VBQT1 and vBMD. The combination of VBQs from different MRI sequences enhances the prognostic value of VBQ for the determination of osteoporosis. While safe clinical application of VBQ for the determination of osteoporosis requires further validation, VBQ might offer opportunistic estimation for further diagnostics.