Method for cortical bone structural analysis from magnetic resonance images

Rationale and Objectives. Quantitative evaluation of cortical bone architecture as a means to assess bone strength typically is accomplished on the basis of images obtained by means of dual-energy X-ray absorptiometry (DXA) or computed tomography. Magnetic resonance (MR) imaging has potential advantages for this task in that it allows imaging in arbitrary scan planes at high spatial resolution. However, several hurdles have to be overcome to make this approach practical, including resolution of issues related to nonlinear receive coil sensitivity, variations in marrow composition, and the presence of periosteal isointense tissues, which all complicate segmentation. The aim of this study is to develop MR acquisition and analysis methods optimized for the detection of cortical boundaries in such complex geometries as the femoral neck. Materials and Methods. Cortical boundary detection is achieved by radially tracing intensity profiles that intersect the periosteal and endosteal boundaries of bone. Profiles subsequently are normalized to the intensity of the marrow signal, processed with morphologic image operators, and binarized. The resulting boundaries are mapped back onto the spatial image, and erroneous boundary points are removed. From the detected cortical boundaries, cortical cross-sectional area and thickness are computed. The method was evaluated on cortical bone specimens and human volunteers on the basis of high-resolution images acquired at a 1.5-Tesla field strength. To assess whether the method is sensitive to detect the expected dependencies of cortical parameters in weight-bearing bone on overall habitus, 10 women aged 46-73 years (mean age, 56 years) underwent the cortical imaging protocol in the proximal femur, and results were compared with DXA bone mineral density parameters of the hip and spine. Results. Reproducibility was approximately 2%. Double oblique images of the femoral neck in the 10 women studied showed that cortical cross-sectional area correlated strongly with height (r = 0.88; p =.0008), whereas cortical diameter versus age approached significance (r = 0.61; p =.06). Measurements in specimens of some cortical parameters indicated resolution dependence. However, note that specimen ranking within each parameter remained constant across all resolutions studied. Conclusion. Data suggest the new method to be robust and applicable on standard clinical MR scanners at arbitrary anatomic locations to yield clinically meaningful quantitative results.