AUTHOR=Wu Shenghui , Wang Wei , Li Ruiyang , Guo Jingyi , Miao Yu , Li Guangyi , Mei Jiong 

TITLE=Fractured morphology of femoral head associated with subsequent femoral neck fracture: Injury analyses of 2D and 3D models of femoral head fractures with computed tomography

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2023.1115639

DOI=10.3389/fbioe.2023.1115639

ISSN=2296-4185

ABSTRACT=Background: The injury of femoral head varies among femoral head fractures (FHFs). In addition, the injury degree of the femoral head is a significant predictor of femoral neck fracture (FNF) incidence in patients with femoral head fractures (FHFs). However, the exact measurement methods have yet been clearly defined based on injury models of FHFs. This study aimed to design a new measurement for the injury degree of the femoral head on 2D and 3D models with computed tomography (CT) images and investigate its association with FHFs with FNF.
Methods: A consecutive series of 209 patients with FHFs was assessed regarding patient characteristics, CT images, and rate of FNF. New parameters for injury degree of femoral head, including percentage of maximum defect length (PMDL) in the 2D CT model and percentage of fracture area (PFA) in the 3D CT-reconstruction model, were respectively measured. Reliability tests for all parameters were evaluated in 100 randomly selected patients. The sensitivity, specificity, likelihood ratios, and positive and negative predictive values for different parameter cut-off values were employed to test the diagnostic accuracy for FNF prediction.
Results: Intra- and inter-class coefficients for all parameters were ≥ 0.887. The results of logistic regression analysis showed that average PMDL across all three planes and PFA were the significant predictors of FNF (p < 0.05). Areas under curves (AUCs) of all parameters were ≥ 0.719 (p < 0.05). The cutoff values of the average PMDL across all three planes and PFA were 91.65% and 29.68%. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, predictive positive value and negative predictive value of 2D (3D) parameters were 91.7% (83.3%), 93.4% (58.4%), 13.8 (2.0), 0.09 (0.29), 45.83% (10.87%) and 99.46% (98.29%).
Conclusion: The new measurement on 2D and 3D injury models with CT has been established to assess the fracture risk of femoral neck in patients with FHFs in the clinic practice. 2D and 3D parameters in FHFs were a feasible adjunctive diagnostic tool in identifying FNFs. In addition, this finding might also provide a theoretic basis for the investigation of the convenient digital-model in complex injurie analysis.