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Osteoporotic fractures are related not only to bone mineral density (BMD) but also to bone structure or microarchitecture, which is not assessed routinely with currently available methods. We have developed radiographic texture analysis (RTA) for calcaneal images from a peripheral densitometer as an easy, noninvasive method for assessing bone structure. We conducted a cross-sectional study of the relationship between RTA and prevalent vertebral fractures (n = 148) among 900 subjects (ages 19 to 99 years, 94 males) referred for bone densitometry as part of their routine medical care. RTA features were derived from Fourier-based image analysis of the radiographic texture pattern (including root mean square, first moment, and power spectral analyses). RTA features were associated with age, weight, gender, and race, as well as glucocorticoid use. When controlling for clinical risk factors and BMD (or a summary measure calculated using FRAX algorithms), RTA features were significantly different for subjects with and without prevalent vertebral fractures [adjusted odds ratio (OR) = 1.5 per 1 standard deviation (SD) decrease in RTA feature beta, 95% confidence interval (CI) 1.2-1.8, p = .001]. Gender and use of pharmacologic therapy for osteoporosis did not significantly affect this association, suggesting that RTA can be applied to a wide range of densitometry patients. We conclude that RTA obtained using a portable instrument has a potential as a noninvasive method to enhance identification of patients at increased risk of osteoporotic fractures., (2010 American Society for Bone and Mineral Research)

Radiographic texture analysis (RTA) is a computerized analysis of the spatial pattern of radiographic images used as a way of evaluating bone structure. We have shown that RTA performed on high-resolution heel images obtained using a portable densitometer differentiates subjects with and without osteoporotic fractures. In the present study, short-term precision of RTA was examined on densitometric heel images obtained from 33 subjects scanned 8 times each, with 3 observers placing a region of interest (ROI) 3 times on each image. The long-term precision was examined on images obtained from 10 subjects 3 times on each of 3 days separated by 1 week, with 2 observers placing an ROI on each image. The RTA features examined included the root mean square (RMS) variation, a measure of the contrast between the light and dark areas of the image, the first moment of the power spectrum, a measure of the spatial frequency of the trabecular pattern, and Minkowski fractal (MINK), a measure of roughness/smoothness of the trabecular pattern. The precision of the RTA features expressed as coefficient of variation ranged between the lowest of 0.5-0.7% for MINK and the highest of 14-16% for RMS. The short- and long-term precision was similar, and was not significantly influenced by repositioning and rescanning, or by ROI placement by the same or different observers. Significant sources of variability of RTA were the between-subject differences and differences between regions of the heel, but not differences due to repositioning, rescanning in the same position, or ROI placement by the same or different observers. We conclude that technical aspects of image acquisition and processing are adequate to allow further development of RTA of the densitometric images for clinical application as a method for noninvasive assessment of bone structure.

Rationale and Objectives: In the noninvasive evaluation of bone quality, bone mineral density (BMD) has been shown to be the single most important predictor of bone strength and osteoporosis-related fracture. Among the methods of measuring BMD, dual x-ray absorptiometry (DXA) has widespread acceptance due to its low radiation, low cost, and high precision. However, DXA measures area BMD instead of true volumetric density; thus, a larger bone will tend to have a high BMD than will a smaller bone. Therefore, the comparison of BMDs of bones of different sizes can be misleading. In this study, the authors tried to compensate for the size effect by normalizing the area BMD with bone size as measured from a standard pelvic radiograph., Materials and Methods: The overall method for calculation of normalized BMD included conventional area-based BMD from DXA and the extraction of geometric measures from pelvic radiographs. The database for analysis included 34 femoral neck specimens. Regression analysis was performed between the normalized volumetric BMD, measured from femoral neck region, and the mechanical properties obtained from trabecular bone cubes machined from the same region., Results: After normalization of the area BMD, the coefficient of determination increased from 0.30 to 0.43 for the Young modulus and from 0.27 to 0.37 for bone compressive strength., Conclusion: A noninvasive method of normalizing BMD can improve the prediction of bone mechanical properties and has potential in monitoring changes in growing skeletons and in the clinical evaluation of bone quality.

We are developing computerized methods for characterizing the bone texture pattern from digitized skeletal radiographs. For this method to be useful clinically, it must be able to distinguish between weak and strong bone under the range of exposure conditions potentially encountered in the clinical setting. In this study, we examined the effect of exposure conditions on Fourier-based texture features. Thirty-four femoral specimens from total hip arthroplasties were radiographed multiple times under different exposure conditions. The specimens underwent mechanical strength testing from which load to failure values were obtained. The performance of the texture features were investigated in the task of distinguishing between strong and weak bone as characterized by the load to failure values. The texture features showed no dependence upon focal spot size of the x-ray tube or magnification. The texture features did show a dependence with relative exposure, peak kilovoltage, and amount of scattering material.

We are investigating computerized methods to ultimately characterize bone trabecular pattern from clinical skeletal radiographs. In this paper, we present a "phantom" for potential use in the development and evaluation of computerized methods for characterizing radiographic trabecular patterns and ultimately bone strength. Femoral neck specimens were excised during total hip arthroplasties from subjects exhibiting a range of diseases. To mimic the femoral neck in vivo, a "simulated clinical" setup was implemented in which specimens were exposed under conditions that yielded radiographs similar in appearance to standard pelvis radiographs. Fourier-based and fractal-based texture measures were used in the computer analysis; including RMS variation, first moment of the power spectrum, angular-dependent forms of these measures, and fractal dimension. The texture measures obtained from the "simulated clinical" specimen films correlated modestly with those from direct exposure "verification" films of the specimens (r= 0.59-0.69; p<0.0001). From our study, we conclude that the femoral neck specimen "phantoms" may be useful in the development and evaluation of computerized methods for analyzing bone trabecular patterns from skeletal radiographs. The use of a phantom that simulates the clinical radiographic examination allows for repeat exposures without the concern of excessive radiation exposure to a patient.

Both bone mineral density (BMD) and trabecular structure are important determinates of bone mechanical properties. However, neither BMD or trabecular structural features can completely explain the variations in bone mechanical properties. In this study, we combine BMD and bone structural features to characterize bone mechanical behavior. Radiographs were obtained from 34 femoral neck specimens excised during total hip arthroplasties. Each neck radiograph was digitized and a region of interest (ROI) was selected from the medial side of the femoral neck. Textural features, the global Minkoswski dimension and trabecular orientation, were extracted from each ROI image using Minkowski dimension analysis. The BMD of each specimen was measured using dual-energy x-ray absorptiometry (DXA) and subsequently normalized by bone size as measured from a standard pelvis radiograph. Mechanical testing was performed on the trabecular bone cubes machined from each femoral neck to yield bone mechanical properties. Multiple regression was performed to select the best features to predict bone mechanical properties. The results suggest that, using multiple predictors including normalized BMD structural features, and patient age, the coefficients of determination (R2) improved over the use of BMD alone. For bone strength, the R2 was improved from 0.24 using conventional BMD to 0.48 using a four-predictor model. Similar results were obtained in the prediction of Young's modulus, i.e., the R2 was improved from 0.25 to 0.55 in going from the model using conventional BMD to a four-predictor model. This study demonstrates the contributions of normalized BMD, structural features, and age to bone mechanical properties, and suggests a potential method for the noninvasive evaluation of bone mechanical properties.