A Novel Nomogram for Predicting Osteoporotic Vertebral Compression Fractures with Hounsfield Unit and Vertebral Bone
Chenyang Zhuang1,2,3, Xiaolong Yang2,3, Houlei Wang1,3
1Department of Orthopaedics, Shanghai Geriatrics Medical Centre, Shanghai, People's Republic of China.
Insights
Hounsfield units (HU) from CT and vertebral bone quality (VBQ) from MRI effectively predict osteoporotic vertebral compression fractures (OVCFs). A developed nomogram integrating HU, VBQ, and BMI shows promise for opportunistic OVCF risk screening.
Area of Science:
- Radiology and Imaging
- Orthopedics
- Geriatric Medicine
Background:
- Osteoporotic vertebral compression fractures (OVCFs) are a significant health concern in aging populations.
- Assessing bone quality and fracture risk is crucial for managing OVCFs.
- Hounsfield unit (HU) from CT and vertebral bone quality (VBQ) from MRI are emerging biomarkers for bone assessment.
Purpose of the Study:
- To directly compare the predictive efficacy of HU and VBQ for OVCFs.
- To develop and validate a nomogram model integrating HU and VBQ for OVCF risk prediction.
Main Methods:
- Retrospective study of 385 patients (127 OVCFs, 258 controls).
- HU and VBQ values were extracted from medical imaging.
- Statistical analyses included logistic regression and ROC curve analysis; a nomogram was developed and evaluated.
Main Results:
- The OVCF group exhibited higher VBQ and lower HU compared to controls.
- HU demonstrated higher diagnostic accuracy than VBQ via ROC analysis.
- A nomogram integrating BMI, HU, and VBQ achieved an AUC of 0.84 (training) and 0.87 (testing), showing good clinical practicability.
Conclusions:
- Both HU and VBQ are effective predictors of OVCFs.
- The developed nomogram demonstrates good internal predictive performance for OVCF risk.
- Findings suggest potential for opportunistic screening of OVCF risk in patients undergoing spinal imaging.
Purpose:
Osteoporotic vertebral compression fractures (OVCFs) cause significant morbidity in aging populations. Hounsfield unit (HU) from CT and the vertebral bone quality (VBQ) from MRI show promise in assessing bone quality and fracture risk. This study aims to directly compare the predictive efficacy of HU and VBQ for OVCFs and develop a nomogram model integrating HU and VBQ.
Patients And Methods:
A retrospective study was conducted involving 385 patients (127 with OVCFs, 258 controls) who were hospitalized at our hospitals between September, 2020 and September, 2024. HU and VBQ were derived from picture archiving and communication system (PACS). Other variables included demographic, clinical, and radiological data. Statistical analyses included t-tests, chi-square tests, multivariable logistic regression, the least absolute shrinkage and selection operator method (LASSO) regression, and receiver operating characteristic (ROC) curve analysis. Then, a nomogram model was established. The calibration, discrimination and clinical practicability of the nomogram model were also evaluated.
Results:
The OVCF group had significantly higher VBQ and lower HU compared to controls. ROC analysis showed higher diagnostic accuracy for HU than VBQ.A nomogram model for predicting the risk of OVCF occurrence in patients has been developed based on three independent predictors, namely BMI, HU and VBQ. The AUC was 0.84 in the training set and 0.87 in the test set. The model has good practicability for clinics according to the decision curve analysis (DCA) and clinical impact curve (CIC).
Conclusion:
Both HU and VBQ are effective predictors of OVCFs. The nomogram model showed good internal discrimination and calibration in our study. These findings suggest potential utility for opportunistic screening of OVCF risk in patients undergoing routine spinal CT and MRI. However, external validation in prospective and multi-center cohorts is needed before clinical implementation.
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