Literature DB >> 31735177

Reliability of diffusion-weighted magnetic resonance imaging in differentiation of recurrent cholesteatoma and granulation tissue after intact canal wall mastoidectomy.

H S Allam1, A A K Abdel Razek2, B Ashraf1, M Khalek1.   

Abstract

OBJECTIVE: To assess the reliability of diffusion-weighted magnetic resonance imaging in differentiating recurrent cholesteatoma from granulation tissue after intact canal wall mastoidectomy.
METHODS: A prospective study was conducted of 56 consecutive patients with suspected cholesteatoma recurrence after intact canal wall mastoidectomy who underwent diffusion-weighted imaging and delayed contrast magnetic resonance imaging of the temporal bone. The final diagnosis was recurrence in 38 patients and granulation tissue in 18 patients.
RESULTS: Cholesteatoma detection on diffusion-weighted imaging based on two sets of readings had sensitivity of 94.7 and 94.7 per cent, specificity of 94.4 and 88.9 per cent, and accuracy of 94.6 and 92.8 per cent, with good intra-observer agreement (Κ = 0.72, p = 0.001). Cholesteatoma detection on delayed contrast magnetic resonance imaging had sensitivity of 81.6 and 78.9 per cent, specificity of 77.8 and 66.7 per cent, and accuracy of 80.4 and 75.0 per cent, with fair intra-observer agreement (Κ = 0.57, p = 0.001). The mean cholesteatoma diameter on diffusion-weighted imaging was 7.7 ± 1.8 and 7.9 ± 1.8 mm, with excellent intra-observer agreement (Κ = 0.994, p = 0.001).
CONCLUSION: Diffusion-weighted imaging is a reliable method for differentiating recurrent cholesteatoma and granulation tissue after intact canal wall mastoidectomy.

Entities:  

Keywords:  Cholesteatoma; Diffusion-Weighted MRI; Magnetic Resonance Imaging

Year:  2019        PMID: 31735177     DOI: 10.1017/S0022215119002421

Source DB:  PubMed          Journal:  J Laryngol Otol        ISSN: 0022-2151            Impact factor:   1.469


  1 in total

1.  Incidence and trends of middle ear cholesteatoma surgery and mastoidectomy in Australia-A national hospital morbidity database analysis.

Authors:  Jonathan Li; Nicholas Jufas; Martin Forer; Nirmal Patel
Journal:  Laryngoscope Investig Otolaryngol       Date:  2021-12-08
  1 in total

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