Aug 2026· Journal of Neurosurgery : Spine· pp.
1-10
· 0 citations· 36 references
Medicine
TL;DR
Three-dimensional HU represents a novel vBMD assessment methodology that achieves diagnostic parity with QCT using conventional CT scanners without extra radiation exposure or specialized equipment, and demonstrates that precise, universally accessible osteoporosis screening is now achievable.
Abstract
Objective
This study aimed to develop a novel 3D Hounsfield unit (HU) technique for assessing volumetric bone mineral density (vBMD) using routine preoperative CT scans. It was designed to enable opportunistic osteoporosis screening by leveraging existing imaging data. The diagnostic accuracy of this approach was rigorously evaluated against quantitative CT (QCT).
Methods
The authors retrospectively analyzed the records of spine surgery patients who underwent both spinal CT and QCT within a 1-week period. Patients were divided into 3 groups (osteoporosis, osteopenia, and normal bone mineral density [BMD]) based on QCT-vBMD. Baseline characteristics and radiological parameters were compared among the 3 groups. Three-dimensional HU measurements were obtained from lumbar CT scans. Multivariable logistic regression, Pearson correlation analysis, and receiver operating characteristic (ROC) analysis were used to assess the relationships between vBMD and 3D-HU. To evaluate interscanner reliability, a subset of patients received additional CT scanning using both GE and Philips systems. Bland-Altman analysis was used to assess agreement between 3D-HU measurements from different scanner platforms.
Results
Among 264 enrolled patients, 94 were classified as osteoporotic, 114 as osteopenic, and 56 as having normal BMD. Multivariable logistic regression analyses identified lower 3D-HU as an independent predictor of both osteoporosis (OR 0.723, 95% CI 0.618-0.806; p < 0.0001) and osteopenia (OR 0.698, 95% CI 0.564-0.799; p < 0.0001). Three-dimensional HU demonstrated a strong correlation with QCT-vBMD (T12, r = 0.979; L1, r = 0.968; L2, r = 0.962). ROC analysis demonstrated that 3D-HU achieved diagnostic accuracy comparable to QCT for both osteoporosis and osteopenia. Specifically, for osteoporosis, the area under the ROC curve (AUC) was 99.1% (sensitivity 94.7%, specificity 98.3%); for osteopenia, the AUC was 98.5% (sensitivity 93.9%, specificity 94.6%). Bland-Altman analysis demonstrated excellent interscanner agreement (mean difference 0.13; 95% limits of agreement -8.23 to 8.50), with only 2% of measurements falling outside the agreement limits.
Conclusions
Three-dimensional HU represents a novel vBMD assessment methodology that achieves diagnostic parity with QCT. Crucially, this precision is attained using conventional CT scanners without extra radiation exposure or specialized equipment. This study demonstrated that precise, universally accessible osteoporosis screening is now achievable, promising a transformative advance in public bone health.
Objectives To evaluate the agreement and classification concordance of artificial intelligence (AI)-assisted proximal femur bone mineral density (BMD) assessment using multiphase contrast-enhanced abdominal computed tomography (CT), with unenhanced CT-derived quantitative computed tomography (QCT) serving as the reference standard. Methods This retrospective study included 429 patients (mean age, 60.48 ± 12.30 years) who underwent a standardized five-phase abdominal CT protocol, comprising unenhanced, arterial, portal venous, late venous, and excretory phases. A commercially available AI-based QCT workstation was used for semi-automatic proximal femur segmentation and volumetric BMD (vBMD) and T-score calculation. Repeated-measures ANOVA and Bland-Altman analysis were performed to assess inter-phase differences and agreement. Classification concordance was evaluated using the unenhanced CT-derived QCT results as the reference standard. Results The study cohort comprised 378 osteoporotic patients and 51 non-osteoporotic patients, categorized according to unenhanced CT-derived T-score reference values. Results from repeated-measures ANOVA indicated significant phase-related variations in T-scores and vBMD (both P < 0.001). Subsequent post-hoc comparisons revealed that T-scores and vBMD in the arterial and portal venous phases were consistent with the unenhanced phase, whereas modest yet statistically significant deviations were observed in the late venous and excretory phases. Bland-Altman analyses showed minimal mean bias across arterial, portal venous, and excretory phases; however, the late venous phase exhibited broader limits of agreement (LoA). Classification concordance compared to the unenhanced reference was consistently high across all phases, ranging from 98.14 to 99.53%. Additionally, intraobserver reproducibility remained excellent, with ICC values between 0.964 and 0.996. Conclusion AI-assisted proximal femur BMD assessment on contrast-enhanced abdominal CT showed high agreement and classification concordance with unenhanced CT-derived QCT. The arterial and portal venous phases were particularly suitable for opportunistic osteoporosis screening, although external validation against DXA or independent QCT remains necessary.
Fenghuang Lin, Juan Xu, Yanxia Chen et al.· Frontiers in Medicine· 0 citations
VBQ can serve as an opportunistic exploratory screening marker of low BMD and FBQcsf may complement VBQ by identifying early marrow-related changes, although further validation is required.
Margrit Elis Müller, João Paulo Colhado Ferreira, Laura Mulazzani Minuzzi Macedo et al.· Skeletal Radiology· 0 citations
In patients undergoing cervical spine surgery, C-VBQ demonstrates consistent associations with C-HU and DXA T-scores, supporting its potential for opportunistic preoperative bone quality assessment and Integrating radiological indicators such as C-VBQ and C-HU with DXA and BTMs may enable a more comprehensive, but still cautiously interpreted, perioperative bone health evaluation.
Xiaoteng Feng, Xiujia Xia, Zelin Shen et al.· European spine journal· 0 citations
OBJECTIVE
This study compared Hounsfield unit (HU) measurements obtained from different regions of interest (ROIs) on lumbar CT for assessing bone mineral density (BMD) and discriminating osteoporosis and thoracolumbar fragility fracture status, aiming to evaluate whether ROI selection meaningfully influences HU-based assessment.
METHODS
Five HU measurement methods were evaluated using lumbar CT. Their correlations with dual-energy X-ray absorptiometry (DEXA)-derived BMD and their discriminative performance for osteoporosis and thoracolumbar fragility fracture status were analyzed. Receiver operating characteristic (ROC) curves were constructed, and pairwise comparisons of areas under the curve (AUCs) were performed using the DeLong test. A sensitivity analysis was additionally conducted after excluding substituted vertebral levels and recalculating mean lumbar HU using only non-substituted vertebrae.
RESULTS
All five HU measurement methods showed significant correlations with DEXA-derived BMD, and no statistically significant differences in discriminative performance were observed among the five ROI methods in the primary analysis. In the sensitivity analysis excluding substituted vertebral levels, the AUCs remained comparable across methods for osteoporosis (0.816-0.826) and thoracolumbar fragility fracture status (0.677-0.689), with all pairwise DeLong tests showing no statistically significant differences (all p > 0.05).
CONCLUSION
Different lumbar CT ROI methods demonstrated comparable performance in assessing BMD and discriminating thoracolumbar fragility fracture status, and sensitivity analysis confirmed that exclusion of substituted vertebral levels did not materially affect the results. No ROI method showed statistically significant superiority, suggesting that ROI selection may be guided by clinical feasibility and workflow convenience rather than by diagnostic performance alone.
ADVANCES IN KNOWLEDGE
This study compares five commonly used lumbar CT HU measurement methods and shows that their performance is broadly similar. The findings suggest that ROI selection may be guided primarily by clinical feasibility and workflow convenience, although further external validation is required before routine clinical application.
Background/Objectives: This study aimed to evaluate whether artificial intelligence-derived vertebral volumetric bone mineral density (AI-vBMD) and paraspinal intermuscular adipose tissue (IMAT) ratio from routine computed tomography (CT) could identify moderate-to-severe vertebral compression fractures (VCFs) in breast cancer survivors, and whether paraspinal IMAT ratio and routinely available clinical variables improved diagnostic performance. Methods: This retrospective study included 275 women with breast cancer who underwent routine non-contrast CT and lumbar quantitative computed tomography (QCT). Hounsfield unit-derived volumetric bone mineral density (HU-vBMD) was derived using a QCT-referenced HU-to-vBMD conversion equation, whereas AI-vBMD and paraspinal IMAT ratio were extracted using automated software. Moderate-to-severe VCF was defined as Genant grade ≥ 2. Agreement with QCT-vBMD was assessed using correlation, intraclass correlation coefficient (ICC), and Bland–Altman analysis. Model discrimination was evaluated using receiver operating characteristic analysis and DeLong tests. Results: Moderate-to-severe VCF was present in 75 patients (27.3%). HU-vBMD and AI-vBMD showed excellent agreement with QCT-vBMD (ICC, 0.978 and 0.987, respectively). AI-vBMD outperformed HU-vBMD for identifying VCFs (AUC, 0.738 vs. 0.714; p < 0.001). IMAT ratio showed comparable standalone discrimination to AI-vBMD (AUC, 0.760 vs. 0.738; p = 0.604). Adding IMAT ratio to AI-vBMD improved discrimination (AUC, 0.786 vs. 0.738; p = 0.038). The full model incorporating clinical covariates achieved the highest AUC (0.828; 95% CI, 0.778–0.878). Conclusions: AI-vBMD and paraspinal IMAT ratio automatically extracted from routine CT improved the diagnostic assessment of prevalent moderate-to-severe VCFs in breast cancer survivors. This study supports an automated CT-based approach that integrates vertebral bone density and paraspinal muscle–fat information for opportunistic identification of clinically relevant VCFs.
Chen Wan, Lingquan Kong, Jie Hao et al.· Journal of Clinical Medicine· 0 citations
Both HU and VBQ offer useful assessments of vertebral bone quality, but HU provides higher and more stable diagnostic accuracy, demonstrating higher sensitivity, specificity, and accuracy for detecting osteopenia and osteoporosis.
Omar Lubbad, Akram Hagos, Laila Lubbad et al.· European Radiology· 0 citations
