Open Access
CC BY-NC-ND 4.0 · Indian J Radiol Imaging 2020; 30(02): 139-148
DOI: 10.4103/ijri.IJRI_58_19
Head and Neck Imaging

Imaging in congenital inner ear malformations—An algorithmic approach

Abhinav C Bhagat
Departments of Radiodiagnosis, Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, India
,
Jyoti Kumar
Departments of Radiodiagnosis, Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, India
,
Anju Garg
Departments of Radiodiagnosis, Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, India
,
Anjali Prakash
Departments of Radiodiagnosis, Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, India
,
Ravi Meher
Departments of ENT, Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, India
,
Shivali Arya
Departments of Radiodiagnosis, Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, India
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Abstract

Malformations of the inner ear are an important cause of congenital deaf-mutism. Arrest in embryologic development of inner ear during various stages gives rise to the variety of malformations encountered. Current treatment options include hearing aids, cochlear implants, and auditory brainstem implants (ABI). With the advent of cochlear implant surgery and ABI, decent functional outcomes can be obtained provided such cases are diagnosed correctly and timely. To that end, high-resolution computed tomography (HRCT) has a fundamental role in the assessment of these conditions, ably supplemented by magnetic resonance imaging (MRI). The purpose of this pictorial essay is to illustrate the imaging features of inner ear anomalies in children with congenital deaf-mutism as per the latest terminology and classification and provide an algorithmic approach for their diagnosis.



Publikationsverlauf

Eingereicht: 06. Juni 2019

Angenommen: 30. November 2019

Artikel online veröffentlicht:
19. Juli 2021

© 2020. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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