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REVIEW  MÉNIÈRE'S DISEASE 

Otorinolaringologia 2020 December;70(4):137-41

DOI: 10.23736/S0392-6621.20.02327-9

Copyright © 2020 EDIZIONI MINERVA MEDICA

language: English

Ménière’s disease imaging: MRI, CT and machine learning

Arnaud ATTYÉ 1, 2, Raphaele QUATRE 3, Michael ELIEZER 4, Georges DUMAS 3, Flavio PEROTTINO 5, Roberto ALBERA 6, Sébastien SCHMERBER 3, 7

1 Department of Neuroradiology and MRI, SFR RMN Neurosciences, Grenoble Alpes University Hospital, Grenoble, France; 2 IRMaGe, Grenoble Alpes University Hospital, Grenoble, France; 3 Department of Oto-Rhino-Laryngology, Head and Neck Surgery, Grenoble Alpes University Hospital, Grenoble, France; 4 Unit of Neuroradiology, Department of Neuroradiology, Lariboisiere University Hospital, Paris, France; 5 Department of Oto-Rhino-Laryngology, Escartons Hospital Center CHR Briançon, Briançon, France; 6 Department of Surgical Sciences, University of Turin, Turin, Italy; 7 INSERM BrainTec Lab UMR 1205, Grenoble, France



There is currently a great interest in the study of Ménière’s disease using imaging. Magnetic resonance imaging (MRI) with delayed acquisition provides a powerful means to characterize endolymphatic hydrops noninvasively by using the properties of contrast media on inner ear perilymph. Despite their popularity and widespread use, there are a number of practical considerations that must be considered in order to increase the robustness of endolymphatic hydrops evaluation in Ménière’s disease patients. Besides endolymphatic hydrops, other imaging biomarkers have more recently proven to be useful in Ménière’s disease patients characterization and follow-up, such as blood-labyrinthine barrier impairment or an absence of visible saccule. The progressive ossification of the vestibular aqueduct in both temporal bones of Ménière’s disease patients have also been described, including using nonenhanced CT/cone beam CT scans to rule out the presence of endolymphatic hydrops. This article describes what we consider as major findings of imaging Ménière’s disease patients using MRI scan (first part) and CT/CBCT scan (second part), with particular emphasis on technical considerations that can have an important impact in the results. The recommendations here are intended to inform healthcare providers on potential important shortcomings of their current imaging protocols, as well as to guide future physicians on some of the key issues and decisions that must be faced when doing the imaging report. Finally, we will provide perspectives on what could be expected for Ménière’s disease imaging in the next few years, based on machine learning new developments (last part).


KEY WORDS: Magnetic resonance imaging; Endolymphatic hydrops; Machine learning; Ménière disease

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