High-Spatial-Resolution Bone Densitometry with Dual-Energy X-ray Absorptiometric Region-free Analysis

Purpose: To outline the conceptual development of dual-energy absorptiometric (DXA) region-free analysis, quantify its precision, and evaluate its application to quantify the change in longitudinal femoral periprosthetic bone mineral density (BMD) in patients during the 12 months after total hip arthroplasty. Materials and Methods: All subjects had undergone total hip arthroplasty for idiopathic arthritis, and the scans were collected as part of previous ethically approved studies (1998–2005) for which informed consent was provided. Contemporary image processing approaches were used to develop a region of interest–free DXA analysis method with increased spatial resolution for assessment of proximal femoral BMD. The method was calibrated, and its accuracy relative to a proprietary algorithm was assessed by using a hip phantom. The precision of the method was examined by using repeat DXA acquisitions in 29 patients, and its ability to allow spatial resolution of localized periprosthetic BMD change at the hip was assessed in an independent group of 19 patients who were measured throughout a 12-month period. Differences were evaluated with t tests (P < .05). Results: The method allowed spatial resolution of more than 10 000 individual BMD data points on a typical archived prosthetic hip scan. The median data point–level error of the method after calibration was −1.9% (interquartile range, −7.2% to 3.5%) relative to a proprietary algorithm. The median data point–level precision, expressed as a coefficient of variation, was 1.4% (interquartile range, 1.2%–1.6%). Evaluation of BMD change in a model of periprosthetic bone loss demonstrated large but highly focal changes in BMD that would not be resolved by using traditional region of interest–based analysis approaches. Conclusion: The proposed approach provides a quantitative, precise method for extracting high-spatial-resolution BMD data from existing DXA datasets without the limitations imposed by region of interest–based analysis