Literature DB >> 31287723

Incorporating Cone-Beam CT Into the Diagnostic Algorithm for Suspected Radiocarpal Fractures: A New Standard of Care?

Brian Gibney1, Michelle Smith2, Adrian Moughty3, Eoin C Kavanagh1,4, Darragh Hynes2,4, Peter J MacMahon1,4.   

Abstract

OBJECTIVE. The purpose of this study was to assess the result of adding cone-beam CT to the standard imaging algorithm for patients with suspected radiographically occult traumatic radiocarpal fractures. SUBJECTS AND METHODS. A prospective review was performed on all patients who had cone-beam CT investigation of acute wrist pain after normal initial radiographs. Patients with no identified fractures were clinically reassessed and referred for MRI if concern for a fracture persisted. RESULTS. In all, 117 patients were assessed; 50.4% had fractures identified with a total of 67 radiographically occult fractures. One fracture was identified on MRI that was not seen on cone-beam CT. Cone-beam CT had sensitivity of 98.3% (95% CI, 91.1-100%), specificity of 100% (95% CI, 93.7-100%), positive predictive value of 100%, and negative predictive value of 98.3% (95% CI, 89.1-100%). Accuracy was 99.1% (95% CI, 95.3-100%). CONCLUSION. Incorporating cone-beam CT into routine clinical practice as part of a standardized diagnostic algorithm yielded a 50% fracture detection rate in patients with negative wrist radiographs but ongoing clinical concern for radiocarpal fracture. Cone-beam CT provides more diagnostic information than radiographs at a lower radiation dose than conventional MDCT. Given the poor accuracy of radiographs for acute radiocarpal fractures and the high fracture prevalence in this cohort, we feel that cone-beam CT should be regarded as the new standard of care in the investigation of these patients.

Entities:  

Keywords:  cone-beam CT; diagnosis; trauma; wrist

Year:  2019        PMID: 31287723     DOI: 10.2214/AJR.19.21478

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  4 in total

1.  Scaphoid Fracture Detection by Using Convolutional Neural Network.

Authors:  Tai-Hua Yang; Ming-Huwi Horng; Rong-Shiang Li; Yung-Nien Sun
Journal:  Diagnostics (Basel)       Date:  2022-04-04

2.  Ultra-low-dose cone-beam CT compared to standard dose in the assessment for acute fractures.

Authors:  M C Murphy; B Gibney; J Walsh; G Orpen; E Kenny; F Bolster; P J MacMahon
Journal:  Skeletal Radiol       Date:  2021-06-16       Impact factor: 2.199

Review 3.  The use of cone-beam computed tomography (CBCT) in radiocarpal fractures: a diagnostic test accuracy meta-analysis.

Authors:  Emma Fitzpatrick; Vivek Sharma; Djamila Rojoa; Firas Raheman; Harvinder Singh
Journal:  Skeletal Radiol       Date:  2021-09-20       Impact factor: 2.199

4.  Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.

Authors:  Nils Hendrix; Ernst Scholten; Bastiaan Vernhout; Stefan Bruijnen; Bas Maresch; Mathijn de Jong; Suzanne Diepstraten; Stijn Bollen; Steven Schalekamp; Maarten de Rooij; Alexander Scholtens; Ward Hendrix; Tijs Samson; Lee-Ling Sharon Ong; Eric Postma; Bram van Ginneken; Matthieu Rutten
Journal:  Radiol Artif Intell       Date:  2021-04-28
  4 in total

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