Abstract

Navicular syndrome (NS) is a chronic, degenerative condition of the equine thoracic limb that compromises the distal sesamoid bone (DSB) and associated structures responsible for stabilization and load absorption during locomotion. Although historically attributed to vascular alterations, its etiology is now recognized as biomechanical, characterized by chronic overload of the deep digital flexor tendon. Conventional diagnostic techniques-radiography, scintigraphy, and ultrasonography-lack the sensitivity and precision required to detect early microarchitectural alterations. This study aimed to evaluate changes in the trabecular microarchitecture of the DSB in horses with and without NS using micro-computed tomography (micro-CT) and to explore its diagnostic potential. Samples from eight horses (NS group, n = 4; Not affected group (control), n = 4) were analyzed. Micro-CT images were processed to obtain parameters such as bone volume, relative density, trabecular thickness and separation, porosity, and connectivity. Group comparisons were performed using nonparametric tests and Pearson correlation analyses to explore internal structural relationships. Correlations between groups were then compared using Fisher's Z test. Horses with NS exhibited lower bone volume, trabecular density, thickness, and connectivity, alongside increased trabecular separation, porosity, and anisotropy compared to controls. In healthy horses, strong positive correlations between volume and density, and inverse relationships with trabecular fragmentation, indicated an elevated, well-connected architecture. By contrast, affected horses displayed deteriorated microarchitecture with compensatory trabecular consolidation, reduced trabecular numbers, and a more cylindrical structure-signifying pathological adaptation. Two correlations differed significantly between groups, underscoring disease-induced microstructural reorganization. Micro-CT effectively identified navicular syndrome-specific microarchitectural changes not detectable with conventional methods, yielding quantifiable metrics (thickness, separation, and porosity) that may serve as early diagnostic and monitoring biomarkers. These findings justify broader studies with larger sample sizes and longitudinal designs to validate clinical applicability.