Directional fractal signature methods for trabecular bone texture in hand radiographs: Data from the Osteoarthritis Initiative

Abstract

Purpose: To develop directional fractal signature methods for the analysis of trabecular bone (TB) texture in hand radiographs. Problems associated with the small size of hand bones and the orientation of fingers were addressed. Methods: An augmented variance orientation transform (AVOT) and a quadrant rotating grid (QRG) methods were developed. The methods calculate fractal signatures (FSs) in different directions. Unlike other methods they have the search region adjusted according to the size of bone region of interest (ROI) to be analyzed and they produce FSs defined with respect to any chosen reference direction, i.e., they work for arbitrary orientation of fingers. Five parameters at scales ranging from 2 to 14 pixels (depending on image size and method) were derived from rose plots of Hurst coefficients, i.e., FS in dominating roughness (FSSta), vertical (FSV) and horizontal (FSH) directions, aspect ratio (StrS), and direction signatures (StdS), respectively. The accuracy in measuring surface roughness and isotropy/anisotropy was evaluated using 3600 isotropic and 800 anisotropic fractal surface images of sizes between 20 × 20 and 64 × 64 pixels. The isotropic surfaces had FDs ranging from 2.1 to 2.9 in steps of 0.1, and the anisotropic surfaces had two dominating directions of 30° and 120°. The methods were used to find differences in hand TB textures between 20 matched pairs of subjects with (cases: approximate Kellgren-Lawrence (KL) grade ≥2) and without (controls: approximate KL grade <2) radiographic hand osteoarthritis (OA). The OA Initiative public database was used and 20 × 20 pixel bone ROIs were selected on 5th distal and middle phalanges.The performance of the AVOT and QRG methods was compared against a variance orientation transform (VOT) method developed earlier [M. Wolski, P. Podsiadlo, and G. W. Stachowiak, “Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis in knee radiographs,” Proc. Inst. Mech. Eng., Part H223, 211–236 (2009)]. Results: The AVOT method correctly quantified the isotropic and anisotropic surfaces for all image sizes and scales. Values of FSSta were significantly different (P < 0.05) between the isotropic surfaces. Using the VOT and QRG methods no differences were found at large scales for the isotropic surfaces that are smaller than 64 × 64 and 48 × 48 pixels, respectively, and at some scales for the anisotropic surfaces with size 48 × 48 pixels. Compared to controls, using the AVOT and QRG methods the authors found that OA TB textures were less rough (P < 0.05) in the dominating and horizontal directions (i.e., lower FSSta and FSH), rougher in the vertical direction (i.e., higher FSV) and less anisotropic (i.e., higher StrS) than controls. No differences were found using the VOT method. Conclusions: The AVOT method is well suited for the analysis of bone texture in hand radiographs and it could be potentially useful for early detection and prediction of hand OA.