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Comparison of Different Diffusion Weighted MR Techniques in the Diagnosis of the Middle Ear Cholesteatoma?Value of Non-Echo Planar Diffusion-Weighted MRI

Tomasz Zatoński, Marek Sąsiadek and Anna Zimny

Objective: Magnetic resonance (MR) imaging is essential to detect middle ear cholesteatoma, especially using Diffusion weighted imaging (DWI). The aim of the study was to analyse the value of two different DWI techniques (Echoplanar imaging (EPI) and non-EPI) in the diagnosis of cholesteatoma.

Methods: Our material consisted of 32 patients with a clinical suspicion of cholesteatoma who underwent Magnetic resonance imaging (MRI) of the temporal bone using both EPI and non-EPI DWI. Only studies with histopathological results were included. Two independent readers retrospectively analysed MR images. Intra-and interobserver agreements as well sensitivity, specificity, negative (NPV) and positive (PPV) predictive values of two DWI sequences were assessed.

Results: Using non-EPI DWI all cholesteatomas were correctly diagnosed by both readers with no false negative nor inconclusive cases and with only one false positive result. Non-EPI DWI revealed high interobserver agreement (ĸ=1) and high correlation with histopathological results (r=0.895). EPI DWI misdiagnosed 27-31% of cholesteatomas (false negative results), showing also significantly low interobserver agreement (ĸ=0.373) and low correlation with histopathological results (r=0.328 for reader 1 and r=0.267 for reader 2). Non-EPI DWI revealed very high sensitivity (100%), specificity (83.3%), as well as NPV (100%), and PPV (96.3%) in comparison to EPI DWI which showed lower sensitivity (69.2%), specificity (66.6-83.3%), NPV (33.3-38.4%) and PPV (90-94.7%).

Conclusion: Compared to EPI, non-EPI DWI is a highly reliable method of detecting middle ear cholesteatoma with high sensitivity, specificity and interobserver agreement which make this technique very useful in the clinical settings regardless of the pre- or postoperative state of the ear.

Avertissement: Ce résumé a été traduit à l'aide d'outils d'intelligence artificielle et n'a pas encore été examiné ni vérifié.