About this Research Topic
The goal of this Research Topic is to synthesize the latest data on high resolution imaging of the inner ear and its central nervous system projections. To date, the dominant challenges encountered by those who image the inner ear have been image resolution and the inner ear’s secluded position deep within the temporal bone. The interfaces between bone, soft tissue, fluid, and air of the middle ear and mastoid generate artifacts in both magnetic resonance imaging (MRI) and computed tomography (CT). New techniques in MRI and CT have allowed us to see these structures with ever-greater resolution and are beginning to reveal discoveries of inner ear pathophysiology. Flat panel CT scans have increased our ability to diagnose disorders of the bone of the middle and inner ear, such as superior semicircular canal dehiscence syndrome. Improved MRI hardware such as greater magnetic field strengths and stronger gradient coils have led to improved signal and spatial resolution, while new developments in the use of contrast and pulse sequences have shown us separate perilymph and endolymph spaces in patients with Meniere’s disease. This Topic is an opportunity to bring technological developments in imaging to an audience of clinicians and researchers who specialize in the disorders of the inner ear.
Therefore, we welcome submissions of manuscripts on the following subjects:
• Technological developments in MRI of the inner ear;
• The use of HYDROPs imaging to provide insights into clinical vestibular disorders;
• Using MRI to diagnose patients with central vestibular disorders;
• Using MRI to identify how the brain processes vestibular information;
• Technological developments in CT imaging of the inner ear;
• The use of CT imaging to diagnose middle and inner ear disorders;
• The use of CT imaging to assess the placement of inner ear devices such as cochlear and vestibular implants;
• Novel imaging techniques to study inner ear disease.
Topic Editor Arnaud Attye has received research grants from Guerbet and Bayer. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
Keywords: inner ear imaging, radiomics, artificial intelligence, machine learning, deep learning, Vestibular cortical network, vestibular connectivity, inner ear MRI, vestibular cortical dominance, visual-vestibular interaction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.