Stress fractures are common in the limb bones of human and equine athletes alike. Repetitive
skeletal loading can lead to remodeling and the accumulation of microdamage in bone, which only
becomes grossly evident during catastrophic fracture of the bone due to the accumulated
microdamage. Though various metrics attempting to quantify bone health exist, none have
distinguished themselves as early predictors of the susceptibility of bone to fracture. In this
exploratory study, we examine the ability of several evaluation methods to distinguish between
third metacarpal (MC3) bones from racehorses that have experienced a limb-bone fracture and
from those that have not. Third metacarpal bones were harvested from deceased Thoroughbred
racehorses and categorized into four groups: MC3 bones from horses whose cause of death was
not related to skeletal fracture (Control group, n = 20), MC3 bones form horses that were
euthanized after fracturing proximal sesamoid bones (Sesamoid group, n = 20), MC3 bones from
horses that were euthanized after fracturing a non-MC3 long bone (Long Bone group, n = 19), and
MC3 bones from horses that were euthanized after fracturing an MC3 (MC3 group, n = 5). Each
MC3 bone underwent testing using a variety of tools and methods at the proximal, midshaft, and
distal levels of the lateral, dorsal, and medial surfaces. All tools and methods (OsteoProbe
reference point indentation, BioDent reference point indentation, x-ray, micro-CT, and pQCT)
exhibited some capability in differentiating between control and fracture groups. The long-term
objective of this project is to create a model that will utilize data from a set of evaluations and
output the susceptibility of the horse to fracture a bone, a long bone, or the MC3, specifically.
Although the sample size in this study is not sufficient to create a reliably predictive logistic
regression model, promising results from preliminary models provide incentive to further explore
the possibility of creating one. While clinical practicality will be a vital consideration for a model
in the future, establishing this basis for the capability of each evaluation at hand is a necessary first
step in predicting and preventing fracture in bone.