University of Oulu

Gebre, R.K., Hirvasniemi, J., Lantto, I. et al. Discrimination of Low-Energy Acetabular Fractures from Controls Using Computed Tomography-Based Bone Characteristics. Ann Biomed Eng (2020). https://doi.org/10.1007/s10439-020-02563-4

Discrimination of low-energy acetabular fractures from controls using computed tomography-based bone characteristics

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Author: Gebre, Robel K.1; Hirvasniemi, Jukka2; Lantto, Iikka3,4;
Organizations: 1Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
2Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
3Division of Orthopaedic and Trauma Surgery, Oulu University Hospital, Oulu, Finland
4Medical Research Center, University of Oulu and Oulu University Hospital, Oulu, Finland
5Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020081148345
Language: English
Published: Springer Nature, 2020
Publish Date: 2020-08-11
Description:

Abstract

The incidence of low-energy acetabular fractures has increased. However, the structural factors for these fractures remain unclear. The objective of this study was to extract trabecular bone architecture and proximal femur geometry (PFG) measures from clinical computed tomography (CT) images to (1) identify possible structural risk factors of acetabular fractures, and (2) to discriminate fracture cases from controls using machine learning methods. CT images of 107 acetabular fracture subjects (25 females, 82 males) and 107 age-gender matched controls were examined. Three volumes of interest, one at the acetabulum and two at the femoral head, were extracted to calculate bone volume fraction (BV/TV), gray-level co-occurrence matrix and histogram of the gray values (GV). The PFG was defined by neck shaft angle and femoral neck axis length. Relationships between the variables were assessed by statistical mean comparisons and correlation analyses. Bayesian logistic regression and Elastic net machine learning models were implemented for classification. We found lower BV/TV at the femoral head (0.51 vs. 0.55, p = 0.012) and lower mean GV at both the acetabulum (98.81 vs. 115.33, p < 0.001) and femoral head (150.63 vs. 163.47, p = 0.005) of fracture subjects when compared to their matched controls. The trabeculae within the femoral heads of the acetabular fracture sides differed in structure, density and texture from the corresponding control sides of the fracture subjects. Moreover, the PFG and trabecular architectural variables, alone and in combination, were able to discriminate fracture cases from controls (area under the receiver operating characteristics curve 0.70 to 0.79). In conclusion, lower density in the acetabulum and femoral head with abnormal trabecular structure and texture at the femoral head, appear to be risk factors for low-energy acetabular fractures.

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Series: Annals of biomedical engineering
ISSN: 0090-6964
ISSN-E: 1573-9686
ISSN-L: 0090-6964
Volume: In press
DOI: 10.1007/s10439-020-02563-4
OADOI: https://oadoi.org/10.1007/s10439-020-02563-4
Type of Publication: A1 Journal article – refereed
Field of Science: 3111 Biomedicine
Subjects:
Funding: Open access funding provided by University of Oulu including Oulu University Hospital. This study was financially supported by CINOP Global through the NICHE project NICHE/ETH/246 funded by EP-Nuffic (Netherlands). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska Curie Grant Agreement No 707404.
Copyright information: © 2020 The Author(s). Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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