Abstract
Based on the current paradigm, a healthy bone is one with adequate mass without microarchitectural decay. However, these two features may not be sufficient to ensure that a bone is healthy. In addition, components must be correctly assembled and aligned. This ensures "the right amount of bone, at the right place" and thus, an optimal cohesion or interplay between constituents. Disorganization may be an independent contributor to bone abnormalities including fragility fractures. Indeed, many bone diseases may be characterized by the presence of disorganized bone, including osteogenesis imperfecta, hypophosphatasia, and atypical femur fractures (AFFs). Despite its likely importance, currently, there are no tools to quantify disorganization in vivo. We address this unmet need by describing a novel method for quantifying bone disorganization from X-ray images. Disorganization is quantified as variations in the orientation of bone components in relation to a target reference point. True disorganization created by disarranging (misplacing) pixels within the bone served as "gold standard." To further validate the method in clinical settings, we compared disorganization in three groups of femurs: (i) femurs of women with AFFs (n = 9); (ii) fracture-free femurs contralateral to AFFs (n = 9); and (iii) fracture-free femurs from controls (n = 25). There was excellent agreement between measured disorganization and "gold standard," with R (2) values ranging from 0.84 to 0.99. Precision error ranged from 1.72% to 4.69%. Disorganization produced by abnormalities associated with AFFs was accurately captured. Disorganization level was lowest in fracture-free control femurs, higher in fracture-free contralateral femurs to AFFs, and highest in femurs with AFFs (all p < 0.0001). Quantification of disorganization, a novel biomarker, may provide novel insights into the pathogenesis of metabolic bone diseases beyond that provided by bone mineral density (BMD) or microarchitecture. We provide evidence that measurement of disorganization is likely to help identify patients at risk for fractures, especially in those poorly explained by BMD or microarchitecture such as AFFs. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.