Introduction
Osteoporosis and sarcopenia frequently coexist as interrelated components of the degeneration of a broader musculoskeletal segment, the “bone–muscle unit,” and are referred to as the “osteosarcopenia” [1]. In the context of the spine, this coupling manifests as impaired vertebral bone strength with paraspinal muscle degeneration, both conditions being independently associated with pain, functional limitation, mechanical complications, and poorer surgical outcomes [2,3]. Hence, understanding the relationship between imaging-derived bone and muscle metrics is essential for improving risk stratification and optimizing perioperative decision-making in spine care.
Lately, opportunistic imaging biomarkers are gaining attention as practical tools for assessing bone and muscle health without requiring dedicated diagnostic imaging studies. Computed tomography (CT)-derived vertebral attenuation (measured in Hounsfield Units [HU]) is a validated surrogate for bone mineral density and vertebral strength and is widely used in spine surgery for opportunistic osteoporosis assessment [4]. However, CT involves ionizing radiation and is not routinely obtained solely for bone quality screening or longitudinal follow-up. In contrast, magnetic resonance imaging (MRI) serves as the cornerstone of spinal imaging as it averts radiation exposure and provides detailed information on vertebral marrow composition, as well as paraspinal musculature. MRI-based vertebral bone quality (VBQ) score is commonly used as an index of VBQ and typically calculated from T1-weighted images by normalizing vertebral marrow signal intensity to a reference region, such as cerebrospinal fluid [5,6]. Higher VBQ values generally indicate poorer bone quality, reflecting increased marrow fat content. Beyond bone assessment, MRI also enables quantification of the size and composition of paraspinal muscles in terms of cross-sectional area (CSA), functional CSA (FCSA), and fat infiltration measures, which are known to be correlated with frailty, disability, and adverse spine surgery outcomes [5].
Although recent evidence has demonstrated that elevated VBQ is associated with postoperative mechanical complications, such as cage subsidence, screw loosening, and junctional pathology, most studies have focused on VBQ as a prognostic marker rather than examining its physiological validity [6]. Furthermore, the degree to which VBQ concurs with established CT-based bone metrics, such as vertebral attenuation in HU, and whether VBQ reflects broader musculoskeletal degeneration involving paraspinal muscle quality remains ill-defined. Clarifying these relationships is critical for determining whether VBQ can serve as a valid, reliable, radiation-free surrogate for assessing bone quality and as an imaging marker of the bone–muscle unit. While several individual studies have explored associations between bone metrics (VBQ or HU) and paraspinal muscle characteristics, the reported results are heterogeneous, with significant variability across spinal regions, imaging protocols, and muscle measurement definitions. No prior synthesis has comprehensively integrated MRI-derived VBQ, CT-derived vertebral attenuation (HU), and paraspinal muscle metrics within a single quantitative framework.
Accordingly, this systematic review and meta-analysis aimed to: (1) quantify the association between MRI-derived VBQ and CT-derived vertebral attenuation in HU; (2) evaluate the relationship between VBQ and paraspinal muscle characteristics, including muscle size and fat infiltration; and (3) assess how CT-based HU measures correlate to paraspinal muscle metrics. In addition, where feasible, we sought to explore the possibility of cross-modality translation to derive an interpretable regression relationship between VBQ and HU by reconstructing individual participant data. By integrating bone and muscle imaging metrics, this study aimed to provide a physiologically-grounded evaluation of VBQ and clarify its role within the broader context of spine-related musculoskeletal degeneration.
Methods
Protocol registration and reporting framework
This systematic review and meta-analysis was designed and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to ensure methodological transparency and reproducibility. The study protocol was registered with PROSPERO (registration number: CRD420251238599).
Eligibility criteria
Original studies involving human subjects aged ≥18 years were eligible for inclusion if they reported quantitative associations between: (1) MRI-derived VBQ indices (the VBQ score or closely related variants) and CT-derived vertebral attenuation measured in HU; and/or (2) bone quality metrics (VBQ or HU) and paraspinal muscle characteristics, including measures of muscle size (CSA, FCSA, or relative CSA) and muscle composition (fat infiltration or fat fraction). Studies were considered if they provided extractable quantitative association data, such as correlation coefficients or regression parameters linking these metrics. Non-original articles (literature reviews, editorials, commentaries), animal or cadaveric studies, and studies lacking extractable quantitative data were excluded.
Information sources and search strategy
A comprehensive literature search was conducted in the PubMed, Embase, Scopus, and Web of Science databases for all literature published until December 9, 2025, targeting bone, muscle, and imaging modalities. The following search strings were used for the literature search: ((“vertebral bone quality” OR “endplate bone quality”) OR VBQ OR EBQ OR MVBQ OR “modified vertebral bone quality” OR “MRI-based vertebral bone quality” OR ((vertebr* OR endplate* OR spinal OR spine) AND (“bone quality” OR “bone marrow fat” OR “trabecular bone”) AND (score* OR scoring OR metric*))) AND (“paraspinal muscle*” OR “paravertebral muscle*” OR multifidus OR “erector spinae” OR psoas) AND (MRI OR “magnetic resonance”)) OR ((“Hounsfield unit*” OR HU) AND (MRI OR “MR imaging”) AND (“vertebral bone quality” OR “fat infiltration” OR “myosteatosis” OR CSA)). Reference lists of included studies were also manually screened to identify any additional eligible records.
Study selection
All retrieved records were imported into a reference management database; duplicates were removed prior to screening. Two reviewers (M.A. and A.B.) independently screened titles and abstracts of all studies for relevance, followed by full-text assessment of potentially eligible studies. Any discrepancies were resolved through discussion and mediation with a third reviewer. The PRISMA flowchart for the study selection process is presented in Fig. 1.
Data extraction
Data extraction was performed independently by two reviewers (M.A. and A.B.) using a standardized data collection form. The following variables were extracted: study design, country, sample size, population characteristics, spinal region and vertebral levels analyzed, MRI acquisition details and VBQ methodology, CT acquisition and HU measurement protocols, paraspinal muscle metrics (CSA, FCSA, relative CSA, and fat-related measures), and reported association statistics. Any disagreements in data were resolved by consensus, with input from a third reviewer (F.R.) when necessary.
Risk of bias assessment
We used the Newcastle–Ottawa Scale (NOS) for assessing the methodological quality and risk of bias in the included studies. All evaluations were conducted independently by two reviewers (M.A. and A.B.), with additional input from a third reviewer (F.R.) to resolve any discrepancies. Studies were categorized according to standard NOS criteria across selection, comparability, and outcome domains.
Outcomes
The primary outcomes of interest were quantitative associations between: (1) MRI-derived VBQ (and related indices) and CT-derived HU; (2) VBQ and paraspinal muscle characteristics, including muscle size and fat infiltration; and (3) CT-derived HU and paraspinal muscle characteristics.
Statistical analysis
The meta-analysis was performed using R ver. 4.3.2 (R Core Team, 2023, “meta” package; The R Foundation for Statistical Computing, Vienna, Austria). Correlation coefficients reported in the included studies were transformed into Fisher’s Z values before pooling. Random-effects models were fitted using restricted maximum likelihood, with Hartung-Knapp adjustment applied to generate robust confidence intervals (CIs). Pooled estimates were subsequently back-transformed to Pearson’s correlation coefficients (r) for interpretability. Statistical heterogeneity was assessed using the I2 statistic and Cochran’s Q test. For studies reporting Spearman’s rank correlation coefficients, values were converted to Pearson’s “r” using the established approximation r=2×sin (ρπ/6) to allow consistent pooling [7]. To maintain statistical independence, multiple dependent correlation coefficients derived from the same cohort (such as in studies reporting separate correlations for multifidus and erector spinae muscles) were combined into a single composite effect size by averaging Fisher’s Z values. Conversely, when independent subgroup data (e.g., sex-stratified cohorts) were reported, weighted averages were calculated using inverse-variance weighting prior to pooling.
Prespecified subgroup analyses were conducted based on spinal region (cervical vs. lumbar) and muscle metric definitions (CSA vs. FCSA) when sufficient data were available. Publication bias and small-study effects were evaluated using contour-enhanced funnel plots and Egger’s regression test when the number of contributing studies met accepted thresholds.
Regression synthesis using reconstructed individual participant data
To enhance the clinical applicability of the relationship between MRI-derived VBQ and CT-derived HU, individual participant data were reconstructed from published scatter plots using WebPlotDigitizer [8]. Digitized data were validated by comparing them with the original study-level correlation coefficients before pooling. Extracted data points were then aggregated, and both study-specific and pooled simple linear regression models were fitted to estimate the overall VBQ–HU relationship.
Results
The literature search yielded a total of 794 records across the four databases. After removing 555 duplicates, the titles and abstracts of 239 records were screened for inclusion, of which 196 were excluded. Subsequently, 43 full-text articles were assessed for eligibility, of which five were not retrievable, and 13 were excluded due to inappropriate design, population, or outcomes. Ultimately, 24 studies comprising 4,447 participants were included in the synthesis (Fig. 1).
The included studies were predominantly observational and retrospective in design; most were conducted in China, with a smaller number from the United States. Study populations primarily involved patients with degenerative spine conditions or those undergoing spine surgery and encompassed cohorts of both cervical and lumbar spines. Detailed study characteristics, including imaging modalities, spinal levels assessed, and muscle metrics analyzed, are summarized in Table 1 [6,9–31].
Association between MRI-derived VBQ and CT-derived HU
Across all included studies, MRI-derived VBQ demonstrated a moderate inverse association with CT-derived vertebral attenuation. The overall random-effects pooled correlation coefficient was r=−0.55 (95% CI, −0.65 to −0.43), indicating that higher VBQ values were consistently associated with lower HU values. Substantial heterogeneity was observed among the studies included (I2=93.2%).
Subgroup analyses by spinal region yielded similar results. In cervical spine cohorts, the pooled random-effects correlation analysis yielded an “r” value of −0.53 (95% CI, −0.68 to −0.33; I2=88.7%), whereas lumbar spine cohorts demonstrated a pooled correlation “r” of −0.57 (95% CI, −0.73 to −0.37; I2=95.4%). There was no statistically significant difference between the cervical and lumbar spine subgroups (p>0.05), suggesting a consistent VBQ–HU relationship across spinal regions (Fig. 2) [9–17,20–22,28,30,31].
Association between VBQ and paraspinal muscle area (CSA/FCSA)
VBQ showed a small but statistically significant negative association with the lumbar paraspinal muscle area. Pooled data from studies reporting CSA and FCSA yielded an overall random-effects correlation “r” of −0.19 (95% CI, −0.35 to −0.02), with moderate heterogeneity (I2=71.8%).
Subgroup analyses based on muscle metric definition demonstrated comparable effect sizes. Studies reporting conventional CSA yielded a pooled correlation “r” of −0.19, while those reporting functional CSA demonstrated a similar association (r=−0.19). No significant subgroup differences were detected, indicating that higher VBQ values were moderately associated with reduced paraspinal muscle size regardless of metric definition (Fig. 3) [6,23–26,29].
Association between VBQ and paraspinal muscle fat infiltration
Five studies evaluated muscle composition; pooled analysis of data for VBQ exhibited a strong positive association with paraspinal muscle fat infiltration. The pooled random-effects correlation coefficient “r” of 0.63 (95% CI, 0.10–0.88), indicating that higher VBQ values were associated with greater degrees of myosteatosis. However, considerable heterogeneity was observed among these studies (I2=97.7%) (Fig. 4) [6,13,23,25,26].
Association between CT-derived HU and paraspinal muscle metrics
Compared with VBQ, CT-derived HU demonstrated directionally opposite associations with muscle size and composition. In studies evaluating muscle fat infiltration, HU was negatively correlated with fat infiltration (common-effect pooled correlation r=−0.70; 95% CI, −0.75 to −0.64). The corresponding random-effects estimate showed wider uncertainty due to substantial heterogeneity (I2=96.4%).
Regarding muscle size, HU showed a positive association with paraspinal muscle CSA. The pooled random-effects correlation “r” across four studies reporting CSA was 0.40 (95% CI, 0.04–0.67), with high heterogeneity (I2=88.8%). These findings mean that higher vertebral attenuation is associated with greater muscle bulk and lower muscle fat infiltration.
Regression synthesis using reconstructed individual participant data
Individual participant data were reconstructed from scatter plots published in three eligible studies [9–11]. After analysis, the digitized data closely reproduced the originally reported study-level correlation coefficients, supporting the validity of the reconstruction process. Study-specific linear regressions demonstrated consistent inverse relationships between VBQ and HU, with slopes ranging from −33.15 HU to −72.32 HU per 1-point increase in VBQ (r=−0.37 to −0.54). When all reconstructed data points were pooled, a single linear regression equation was derived to compute HU based on VBQ value (r=−0.352): HU=−50.9×VBQ+378.
Risk of bias and publication bias
All included studies had generally good methodological quality, with total NOS scores ranging from 7 to 9 (Table 2, Supplement 1) [6,9–31]. The most common limitations involved incomplete adjustment for potential confounders in the comparability domain.
Funnel plots for assessing small-study effects in the VBQ–HU meta-analysis did not reveal significant asymmetry (Egger’s test p=0.216) (Fig. 6). For other outcomes, formal testing was not performed due to the limited number of contributing studies.
Discussion
This systematic review and meta-analysis provides the first integrated quantitative synthesis of MRI-derived VBQ, CT-derived vertebral attenuation (HU), and paraspinal muscle characteristics to offer a physiological context for VBQ, supporting its role as an imaging marker of the bone–muscle unit rather than an isolated surrogate of bone mineral density.
VBQ and CT-HU: cross-modality convergence
The most significant finding of this study is the consistent inverse relationship between VBQ and HU observed across spinal regions. The pooled correlation (r=−0.55) indicates moderate-to-strong convergence between MRI- and CT-based assessments of VBQ, with similar effect sizes observed in the cervical and lumbar subgroups. This supports the construct validity of VBQ as a bone-related imaging biomarker, aligning with previous single-center studies demonstrating an inverse association between VBQ and HU [6,9–12].
From a clinical perspective, this finding reinforces the potential value of VBQ as an opportunistic screening tool for osteoporosis assessment derived from routine MRI, particularly in patients who may not otherwise undergo CT-based bone assessment; however, the substantial heterogeneity observed across studies underscores the fact that VBQ and HU are not interchangeable. As emphasized in previous narrative reviews, VBQ represents relative marrow signal intensity; consequently, it is influenced by MRI acquisition parameters, reference region selection, and marrow composition rather than calibrated mineral density alone [32]. Thus, VBQ can identify patients at risk of compromised bone quality, whereas CT-HU is the primary marker for measuring absolute bone strength estimation or detailed osseous planning.
Bone–muscle coupling: VBQ, muscle size, and myosteatosis
A key finding of this meta-analysis is that VBQ aligns more strongly with paraspinal muscle composition than with muscle size. In the analysis, VBQ showed only a small negative correlation with paraspinal muscle CSA/FCSA, whereas the association with muscle fat infiltration was moderate-to-strong and directionally consistent across studies. This indicates that, as an imaging marker, VBQ preferentially reflects qualitative muscle degeneration (myosteatosis) rather than gross reductions in muscle bulk.
This distinction is particularly relevant because in clinical settings, muscle size may be preserved despite substantial fatty infiltration, especially in older or frail patients; however, myosteatosis has been more consistently associated with impaired function, frailty, and adverse surgical outcomes [2,19]. Furthermore, the strong association observed between VBQ and fatty infiltration supports the concept that elevated VBQ identifies a systemic osteosarcopenic phenotype involving fatty changes in the muscle tissue rather than isolated low bone density. This may also explain why VBQ has significant prognostic relevance for mechanical complications, such as cage subsidence, screw loosening, and junctional failure, reported in previous studies focused on surgical outcomes [6,33,34].
CT-HU and paraspinal muscle metrics
The complementary analyses exploring the association between HU and paraspinal muscle characteristics further corroborate the existence of the bone–muscle unit framework. Higher HU values were associated with larger muscle CSA and lower fat infiltration, a relationship opposite in direction to VBQ. This implies that both imaging modalities capture biologically coherent aspects of musculoskeletal health, albeit through different signal mechanisms—HU appears to be more strongly associated with muscle size than VBQ, whereas VBQ demonstrates a stronger association with muscle fat infiltration. This divergence may arise from the fundamental differences between mineral-based attenuation observed on CT versus marrow fat-sensitive signal changes on MRI. Such modality-specific observations suggest that VBQ and HU provide complementary rather than redundant information, underscoring the importance of a combined interpretation to enhance musculoskeletal risk assessment.
Exploratory VBQ–HU translation
To improve interpretability across imaging modalities, we reconstructed individual participant data to formulate an exploratory pooled regression equation correlating VBQ to HU. While this approach allowed visualization of cross-study trends and yielded a plausible translation model, the results should be interpreted cautiously because digitization introduces measurement errors, and heterogeneity in imaging protocols limits generalizability. Nevertheless, the consistency of study-specific slopes supports the hypothesis that marrow-based deterioration captured by VBQ may be parallel to and potentially precede mineral loss reflected by HU.
Limitations
First, most included studies were retrospective and observational, and there was substantial heterogeneity across imaging protocols, VBQ definitions, HU measurement techniques, and muscle assessment methods. Muscle metrics were particularly heterogeneous, which may explain the weaker and more variable associations observed for muscle size than fat infiltration. Second, causality could not be inferred from the reported correlations. Finally, while publication bias was not detected for the primary VBQ–HU analysis, the number of studies was insufficient for robust bias assessment in the secondary analyses.
Conclusions
This systematic review with meta-analysis demonstrated that MRI-derived VBQ correlates consistently with CT-derived vertebral attenuation (measured in HU) and aligns strongly with paraspinal muscle degeneration, particularly myosteatosis. These findings provide strong physiological evidence for VBQ as an imaging marker of the bone–muscle unit and elucidate its association with adverse spine surgery outcomes. While CT-HU remains the reference standard for absolute bone assessment, VBQ serves as a radiation-free, opportunistic tool for screening that may aid in musculoskeletal risk stratification when interpreted within its biological context. Future prospective studies with standardized imaging protocols are needed to refine the cross-modality translation model developed in this study and refine the optimal clinical role of VBQ in spine care.
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