title: Unraveling the role of structure and density in determining vertebral bone strength.
abstract: The strength of bone is determined not only by bone density but also by structure. Therefore, quantification of the structure in radiographs by texture parameters may result in a better prediction of fracture risk. Since in radiographs density and structure are strongly correlated, the predictive power of texture parameters should be corrected for the influence of BMD to determine the additional information conveyed by these parameters. In this study, we evaluated the predictive power of various texture parameters based on the Grey-Level Dependence Method and the Morphological Gradient Method. This study was performed on 67 vertebrae obtained from 20 male and 12 female human cadaver thoracolumbar spines. BMD and area of the vertebral body were determined from QCT images and texture parameters were derived from direct magnification (DIMA) radiographs. The fracture force, measured under conditions simulating the in vivo situation, was corrected with the area of the vertebra to yield the fracture stress (FS). Results of the study indicate that BMD correlates significantly with FS r = 0.82 (P < 0. 001, n = 24) and r = 0.94 (P < 0.001, n = 43) for female and male vertebrae, respectively. Correlation coefficients of the investigated texture parameters were as high as 0.80 (P < 0.001) and 0.67 (P < 0.001) for the female and male vertebrae, respectively. Multiple regression analysis showed that in female vertebrae, the addition of one texture parameter to BMD results in a better prediction of strength. The multiple correlation coefficient was 0. 87 (P < 0.001) in this case. In male vertebrae, BMD was the best predictor of fracture stress. These results suggest that texture parameters, as measured in magnification radiographs, can predict bone strength. Whereas in all cases BMD is the best single predictor of bone strength, for women texture parameters contain useful additional information.
authors.affiliation: Department of Medical Informatics, Postbox 1738, Erasmus University, 3000 DR Rotterdam, The Netherlands.
authors.forename: J F
authors.initials: JF
authors.lastname: Veenland
authors.forename: T M
authors.initials: TM
authors.lastname: Link
authors.forename: W
authors.initials: W
authors.lastname: Konermann
authors.forename: N
authors.initials: N
authors.lastname: Meier
authors.forename: J L
authors.initials: JL
authors.lastname: Grashuis
authors.forename: E S
authors.initials: ES
authors.lastname: Gelsema
mesh_terms: D015519:Bone Density; D002102:Cadaver; D005260:Female; D006801:Humans; D008159:Lumbar Vertebrae / Q000000981:diagnostic imaging / Q000502:physiology; D008297:Male; D008433:Mathematics; D008954:Models, Biological; D011237:Predictive Value of Tests; D011859:Radiography; D012044:Regression Analysis; D012307:Risk Factors; D016103:Spinal Fractures / Q000000981:diagnostic imaging / Q000503:physiopathology*; D013131:Spine / Q000000981:diagnostic imaging / Q000502:physiology*; D013904:Thoracic Vertebrae / Q000000981:diagnostic imaging / Q000502:physiology