Literature DB >> 28913762

The role of computed tomography (CT) in predicting diplopia in orbital blowout fractures (BOFs).

Michaela Cellina1, Chiara Floridi2, Marta Panzeri3, Oliva Giancarlo2.   

Abstract

PURPOSE: The management of orbital blowout fractures (BOFs) is controversial: the evaluation of diplopia is the most important criterion for planning whether to undertake surgery. Our aim was to determine CT findings that may suggest the presence of diplopia when patients with BOFs cannot be adequately examined to plan an orbital repair. METHOD AND MATERIALS: We retrospectively evaluated CT of all patients presented to our Emergency Department for blunt craniofacial trauma (N = 3334) from January 2014 to March 2016, selecting patients with CT-demonstrated BOFs. The following CT variables were assessed: fracture location, fracture multifocality, bone fragments displacement, extraocular muscles (EOM) thickening, EOM entrapment, EOM displacement, EOM hooking, intraconal and extraconal emphysema, intraconal and extraconal hematoma, and fat herniation. All patients underwent Hess-Lancaster test, to establish the presence of diplopia. After performing group comparison with Pearson χ2 test, we derived our prediction model by using logistic regression, with diplopia as the prediction and CT variables as predictors.
RESULTS: We observed 299 patients with BOFs, 46 (15.4%) with a Hess Lancaster test-proven diplopia. The CT variables with statistically significant difference between the group with diplopia and the group without diplopia were as follows: floor fracture (p = .014), bone fragments displacement (p = .001), multifocality (p = .005), EOM thickening (p = .001), EOM entrapment (p < .001), EOM displacement (p < .001), fat herniation (p = .003). The CT variables with significance as predictors of diplopia at multivariate analysis were as follows: orbital floor fracture (p value 0.015; odds ratio 2.871, 95% confidence interval of odds ratio 0.223-6.738), EOM displacement (p value 0.001; odds ratio 10.693, 95% confidence interval of odds ratio 3.761-30.401), EOM entrapment (p value 0.001; odds ratio 11.510, 95% confidence interval of odds ratio 3.059-43.306).
CONCLUSION: The presence of diplopia can be suggested on the basis of CT findings after an orbital trauma.

Entities:  

Keywords:  CT; Computed tomography; Diplopia; Extraocular muscles; Fracture; Orbital blowout fractures; Orbital blunt trauma

Mesh:

Year:  2017        PMID: 28913762     DOI: 10.1007/s10140-017-1551-1

Source DB:  PubMed          Journal:  Emerg Radiol        ISSN: 1070-3004


  26 in total

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2.  Correlation of preoperative computed tomography and postoperative ocular motility in orbital blowout fractures.

Authors:  G J Harris; G H Garcia; S C Logani; M L Murphy
Journal:  Ophthalmic Plast Reconstr Surg       Date:  2000-05       Impact factor: 1.746

3.  Can a Specific Computed Tomography-Based Assessment Predict the Ophthalmological Outcome in Pure Orbital Floor Blowout Fractures?

Authors:  Stéphane Bruneau; Raoul De Haller; Delphine S Courvoisier; Paolo Scolozzi
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  4 in total

1.  Prolapse of Orbital Fat through the Inferior Orbital Fissure: Description, Prevalence, and Assessment of Possible Pathologic Associations.

Authors:  P M Bunch; K Buch; H R Kelly
Journal:  AJNR Am J Neuroradiol       Date:  2019-06-27       Impact factor: 3.825

2.  Nontraumatic orbital emergencies: a pictorial essay - CT and MRI features for an imaging findings-based approach.

Authors:  Michaela Cellina; Maurizio Cè; Giovanni Irmici; Carlo Martinenghi; Sara Marziali; Natallia Khenkina; Anna Maria Ierardi; Giancarlo Oliva; Gianpaolo Carrafiello
Journal:  Emerg Radiol       Date:  2022-04-14

3.  Evaluation of Concomitant Orbital Floor Fractures in Patients with Head Trauma Using Conventional Head CT Scan: A Retrospective Study at a Level II Trauma Center.

Authors:  Li-Kuo Huang; Hsi-Feng Tu; Liang-De Jiang; Ying-Yuan Chen; Chih-Yuan Fu
Journal:  J Clin Med       Date:  2019-11-02       Impact factor: 4.241

Review 4.  Computed tomography in traumatic orbital emergencies: a pictorial essay-imaging findings, tips, and report flowchart.

Authors:  Michaela Cellina; Maurizio Cè; Sara Marziali; Giovanni Irmici; Daniele Gibelli; Giancarlo Oliva; Gianpaolo Carrafiello
Journal:  Insights Imaging       Date:  2022-01-12
  4 in total

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