Prediction of bone strength from cancellous structure of the distal radius: Can we improve on DXA?

Recent studies show that structural parameters of bone, obtained from compu terized image analysis of radiographs, can improve the noninvasive determin ation of bone strength when used in conjunction with bone density measureme nts. The present study was designed to assess the ability of image features alone to predict the mechanical characteristics of bones. A multifactorial model was used to incorporate simultaneously a number of characteristics o f the image, including periodicity and spatial orientation of the trabecula e. Fifteen pairs (29 specimens) of unembalmed human distal radii were used. The cancellous bone structure was determined using computerized spectral a nalysis of their radiographic images and the bones were tested to failure u nder compression. Multilayered perceptron neural networks were used to inte grate the various image parameters reflecting the periodicity and the spati al distribution of the trabeculae and to predict the mechanical strength of the specimens. The correlation between each of the isolated image paramete rs and bone strength was generally significant, but weak. The values of mec hanical parameters predicted by the neural networks, however, had a very hi gh correlation with those observed, namely 0.91 for the load at fracture an d 0.93 for the ultimate stress. Both these correlations were superior to th ose obtained with dual-energy X-ray absorptiometry and with the cross-secti onal area from CT scans: 0.87 and 0.49 respectively. Our observation sugges ts that image parameters can provide a powerful noninvasive predictor of bo ne strength. The simultaneous use of various parameters substantially impro ved the performance of the system. The multifactorial architecture applied is nonlinear and possibly more effective than traditional multicorrelation methods. Further, this system has the potential to incorporate other non-im age parameters, such as age and bone density itself, with a view to improvi ng the assessment of the risk of fracture for individual patients.