Computed tomography-derived structural analysis for the likelihood of pathologic fracture in canine antebrachial osteosarcoma.

Vet Radiol Ultrasound

Department of Surgical and Radiological Sciences, School of Veterinary Medicine, University of California-Davis, Davis, California, USA.

Published: September 2024

AI Article Synopsis

  • The study focuses on assessing the risk of pathologic fractures in dogs with primary bone tumors in the distal radius to improve treatment selection.
  • Previous research linked the strength of canine antebrachii with bone tumors to CT-derived metrics, revealing key structural factors like rigidity and failure forces.
  • Among 19 dogs evaluated, 8 developed fractures, and the study found that torsional rigidity (Fc) was the most effective metric in predicting fracture occurrence, suggesting that body weight should also be considered in fracture risk assessments.

Article Abstract

Determining the risk of pathologic fracture in dogs with a primary bone tumor would aid in case selection for in-situ treatment options. Prior research found strong relationships between in vitro strength of canine antebrachii with primary bone tumors and CT-derived metrics. This study assesses the prognosis for pathologic fracture in dogs with distal radial bone tumors using CT-derived structural analysis metrics. CT images of the antebrachium in dogs with aggressive osseous lesions of the radius were used to calculate structural rigidity and failure forces, including axial rigidity (AR), craniocaudal bending rigidity (BR), torsional rigidity (TR), and failure forces for a slightly-curved/asymmetric beam (Fs) or a curved beam (Fc). Metrics were compared with the clinical outcome of radial fracture. Eight of 19 dogs with CT-derived metrics developed a radial fracture. The prognostic potential of the metrics to discriminate fractured and nonfractured bones was analyzed using receiver operating characteristic curves (area under the curve), stepwise logistic regression, and classification regression (CART) analyses. Fc was the most sensitive and specific metric for prognosing fracture occurrence (AUC = 0.864). When dog body weight (BW) was included, all five metrics had AUC > 0.705. Fc was the best predictor of fracture using stepwise logistic regression and CART analysis, followed by BR. An indication of fracture probability can be determined by normalizing Fc or BR with dog BW or by using the logistic regression equation of either metric with dog BW. Results warrant further analysis of a larger cohort to evaluate fracture likelihood in dogs with antebrachial bone neoplasia.

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http://dx.doi.org/10.1111/vru.13403DOI Listing

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