$$\rightleftharpoonup{xx}$$
$$\longleftharp{xx}$$,
$$\longrightharp{xx}$$,
Research on fracture healing is necessary to address a large clinical and economic problem. Each year over 12 million fractures are treated in the United States1, costing $80 billion per year2. The likelihood of a male or female suffering a fracture in their lifetime is 25% and 44%, respectively3. Problems associated with fracture healing are expected to increase with increased comorbidities as the population ages. To study and address this problem, robust models of fracture generation and stabilization are required. Rodent models are ideally suited for this purpose. They provide clinical relevance and can be modified to address specific conditions (i.e., multiple injuries, open, closed, ischemic, and infected fractures). In addition to replicating clinical scenarios, animal fracture models are important for understanding bone biology and developing therapeutics and devices. However, attempts to study differences between interventions may be complicated by the variability introduced by inconsistent fracture generation. Thus, generating reproducible and consistently closed fractures in animal models is essential to the field of musculoskeletal research.
Despite properly controlling for potential subject heterogeneity by ensuring the appropriate genetic background, sex, age, and environmental conditions, the production of clinically-relevant consistent bone injuries is a significant variable affecting reproducibility that must be controlled. Statistical comparisons using inconsistent fractures are plagued with experimental noise and a high variability4; in addition, fracture variability can result in unnecessary animal death because of the need to increase the sample size or the necessity to euthanize animals with comminuted or malpositioned fractures. The purpose of the method described herein is to optimize the fracture generation parameters that are specific to sample type and yield a consistent fracture location and pattern.
Current models of fracture generation fall into two broad categories, each with their own strengths and weaknesses. Open-fracture (osteotomy) models undergo surgery to expose the bone, after which a fracture is induced by cutting the bone or weakening it and then manually breaking it5,6,7,8. The benefits of this method are the direct visualization of the fracture site and a more consistent fracture location and pattern. However, the physiological and clinical relevance of the approach and mechanism of injury is limited. Additionally, open methods of fracture generation require a surgical approach and closure with prolonged periods during which the rodents are exposed to an increased risk of contamination.
Closed techniques address many of the open technique's limitations. Closed techniques produce fractures using an externally applied blunt force trauma which induces injury to the bone and surrounding tissues, more similar to those seen in human clinical injuries. The most common method was described by Bonnarens and Einhorn in 19849. They described a weighted guillotine being used to impart blunt trauma to break the bone without causing any external skin wounds. This method has been widely adopted to study the effect of genetics10,11, pharmacologic therapy12,13,14,15, mechanics16,17, and physiology18,19,20 on bone healing in mice and rats. While the benefit of closed methods is physiologically relevant fractures, experimental reproducibility and rigor are limited by fracture heterogeneity. The inconsistent fracture generation results in a limited between-group differentiation, lost specimens, and an increase in animals needed to achieve statistical significance.
Controlling the variability in fracture generation and stabilization is essential to produce meaningful results. In order to properly study the biology of fracture repair, a simple yet robust fracture model is needed. The model should be translatable to rodent species, bone types (femur or tibiae, for example), and across variable mouse genetic backgrounds and induced mutations. Furthermore, the ideal procedure should be technically simple and produce consistent results. To address fracture heterogeneity, the method described herein is the construction of a well-controlled fracture device that can then be used to optimize parameters and generate consistently closed fractures regardless of age, sex, or genotype.