Alqahtani, F.F., Messina, F., Kruger, E. et al. (5 more authors) (2017) Evaluation of a semi-automated software program for the identification of vertebral fractures in children. Clinical Radiology, 72 (10). 904.E11-904.E20. ISSN 0009-9260
Abstract
AIM: To assess observer reliability and diagnostic accuracy in children, of a semi-automated six-point technique developed for vertebral fracture (VF) diagnosis in adults, which records percentage loss of vertebral body height.
MATERIALS AND METHODS: Using a semi-automated software program, five observers independently assessed T4 to L4 from the lateral spine radiographs of 137 children and adolescents for VF. A previous consensus read by three paediatric radiologists using a simplified algorithm-based qualitative technique (i.e., no software involved) served as the reference standard.
RESULTS: Of a total of 1,781 vertebrae, 1,187 (67%) were adequately visualised according to three or more observers. Interobserver agreement in vertebral readability for each vertebral level for five observers ranged from 0.05 to 0.47 (95% CI: -0.19, 0.76). Intra-observer agreement using the intraclass correlation coefficient (ICC) ranged from 0.25 to 0.61. The overall sensitivity and specificity were 18% (95% CI: 14-22) and 97% (95% CI: 97-98), respectively.
CONCLUSION: In contrast to adults, the six-point technique assessing anterior, middle, and posterior vertebral height ratios is neither satisfactorily reliable nor sensitive for VF diagnosis in children. Training of the software on paediatric images is required in order to develop a paediatric standard that incorporates not only specific vertebral body height ratios but also the age-related physiological changes in vertebral shape that occur throughout childhood.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Elsevier. This is an author produced version of a paper subsequently published in Clinical Radiology. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > The Medical School (Sheffield) > Division of Genomic Medicine (Sheffield) > Department of Oncology and Metabolism (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 30 May 2017 14:17 |
Last Modified: | 28 Jul 2023 15:42 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.crad.2017.04.010 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116988 |