Use of high resolution dual-energy x-ray absorptiometry-region free analysis (DXA-RFA) to detect local periprosthetic bone remodeling events.

Dual-energy x-ray absorptiometry (DXA) is the gold standard method for measuring periprosthetic bone remodeling, but relies on a region of interest (ROI) analysis approach. While this addresses issues of anatomic variability, it is insensitive to bone remodeling events at the sub-ROI level. We have validated a high-spatial resolution tool, termed DXA-region free analysis (DXA-RFA) that uses advanced image processing approaches to allow quantitation of bone mineral density (BMD) at the individual pixel (data-point) level. Here we compared the resolution of bone remodeling measurements made around a stemless femoral prosthesis in 18 subjects over 24 months using ROI-based analysis versus that made using DXA-RFA. Using the ROI approach the regional pattern of BMD change varied by region, with greatest loss in ROI5 (20%, p < 0.001), and largest gain in ROI4 (6%, p < 0.05). Analysis using DXA-RFA showed a focal zone of increased BMD localized to the prosthesis-bone interface (30-40%, p < 0.001) that was not resolved using conventional DXA analysis. The 20% bone loss observed in ROI5 with conventional DXA was resolved to a focal area adjacent to the cut surface of the infero-medial femoral neck (up to 40%, p < 0.0001). DXA-RFA enables high resolution analysis of DXA datasets without the limitations incurred using ROI-based approaches.

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.

Soft thresholding for medical image segmentation.

A new soft thresholding method is presented. The method is based on relating each pixel in the image to the different regions via a membership function, rather than through hard decisions. The membership function of each of the regions is derived from the histogram of the image. As a consequence, each pixel will belong to different regions with a different level of membership. This feature is exploited through spatial processing to make the thresholding robust to noisy environments.