24 March 2016 Assessing vertebral fracture risk on volumetric quantitative computed tomography by geometric characterization of trabecular bone structure
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Abstract
The current clinical standard for measuring Bone Mineral Density (BMD) is dual X-ray absorptiometry, however more recently BMD derived from volumetric quantitative computed tomography has been shown to demonstrate a high association with spinal fracture susceptibility. In this study, we propose a method of fracture risk assessment using structural properties of trabecular bone in spinal vertebrae. Experimental data was acquired via axial multi-detector CT (MDCT) from 12 spinal vertebrae specimens using a whole-body 256-row CT scanner with a dedicated calibration phantom. Common image processing methods were used to annotate the trabecular compartment in the vertebral slices creating a circular region of interest (ROI) that excluded cortical bone for each slice. The pixels inside the ROI were converted to values indicative of BMD. High dimensional geometrical features were derived using the scaling index method (SIM) at different radii and scaling factors (SF). The mean BMD values within the ROI were then extracted and used in conjunction with a support vector machine to predict the failure load of the specimens. Prediction performance was measured using the root-mean-square error (RMSE) metric and determined that SIM combined with mean BMD features (RMSE = 0.82 ± 0.37) outperformed MDCT-measured mean BMD (RMSE = 1.11 ± 0.33) (p < 10-4). These results demonstrate that biomechanical strength prediction in vertebrae can be significantly improved through the use of SIM-derived texture features from trabecular bone.
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Walter A. Checefsky, Anas Z. Abidin, Mahesh B. Nagarajan, Jan S. Bauer, Thomas Baum, Axel Wismüller, "Assessing vertebral fracture risk on volumetric quantitative computed tomography by geometric characterization of trabecular bone structure", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978508 (24 March 2016); doi: 10.1117/12.2216898; https://doi.org/10.1117/12.2216898
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