Background/Purpose: Rheumatoid Arthritis (RA) is a chronic inflammatory disease characterized by both localized and generalized bone loss. The inhibition of Receptor Activator of Nuclear Factor Kappa-B Ligand (RANKL) has emerged as a promising therapeutic approach in RA, effectively targeting osteoclast-mediated bone resorption. To accurately assess treatment efficacy in preclinical models, a comprehensive understanding of disease progression is essential, especially concerning less obvious bone alterations. This study introduces a novel 3D method for measuring bone surface roughness from micro-computed tomographic (µCT) data. Despite high-resolution images, current automated methods fail to accurately quantify radiographic changes. This necessitates manual scoring, which varies between scorers and may not accurately measure remodeling in erosive disease models. Hence, the application of surface roughness analysis offers a promising alternative, enhancing the sensitivity of bone evaluation methods.

Methods: We use the K/BxN serum-transfer induced arthritis (STIA) model to study arthritis associated bone destruction. Wild-type (WT) mice (n=36) were subjected to STIA and terminated at nine different time points. In addition, WT mice (n=34) subjected to STIA, were treated with anti-RANKL antibody. A Skyscan1176 µCT was used to collect x-ray images of arthritic paws ex vivo. The calcaneus region was used for surface roughness analysis by our MATLAB script, which quantifies global bone surface roughness by defining an angle to differentiate between smooth and rough curvatures. Arthritis severity was assessed using clinical scoring and histology. Statistical differences were calculated with Mann-Whitney or Kruskal-Wallis tests.

Results: Surface roughness analysis of µCT images was able to capture significant arthritis-induced changes in bone structures that were negligible when using standard visual quantification. In addition, using our analysis we could define two phases of structural bone changes during STIA. A resorption phase occurring during the first 14 days, which was converted to a bone “rebuilding phase” occurring during the last 14 days. In comparison to controls, mice receiving anti-RANKL showed reduced severity of STIA (P=0.01 vs. control). This was associated with reduced bone damage, as reflected through µCT analysis, histological examination, and presence of osteoclasts by TRAP staining. Significantly increased levels of RANKL (P=0.0004) during the course of STIA in parallel with significantly increased levels of matrix metalloproteinases (E.g., MMP9 [P=0.0002], MMP14 [P=0.0001]), further indicate osteoclast recruitment and the promotion of RANKL availability.

Conclusion: We introduce and validate a new method to analyze structural bone changes, which show increased sensitivity compared to current methods. In addition, we find that inhibition of RANKL reduces severity of disease suggesting that enhanced osteoclast generation and bone destruction promotes development of inflammatory arthritis. In summary, the primary benefit of our algorithm is highlighted in the preclinical study, demonstrating its use in assessing disease severity and advancing drug development.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/a-novel-quantitative-method-reveals-bone-structural-changes-during-course-of-inflammatory-arthritis/