Imaging of vestibular function and disorders and its clinical relevance

Abstract

Translate Article

Take Notes

Purpose of reviewTo discuss recent advances in imaging of the structural organization and functional connectivity of central vestibular disorders with various MRI techniques. Vestibular paroxysmia, in particular the characteristics of neurovascular cross-compression of the eighth nerve, serves as an example of the peripheral vestibular disorders.Main findingsThe bilateral vestibular system is intricately connected with other sensory systems and is hierarchically organized within sensory, motor, cognitive, emotional, and memory networks. This has been demonstrated by fMRI using galvanic vestibular stimulation and fear-conditioning paradigms. Another study using transcranial electrical stimulation of the prefrontal cortex alongside galvanic vestibular stimulation showed that vestibular sensations and BOLD signals in the vestibular cortex were reduced, indicating a top-down control of vestibular input. Acute vascular cerebellar lesions around the midline and brainstem lesions affecting the vestibular nuclei can clinically mimic acute unilateral vestibulopathy; an MRI becomes clinically relevant after a few days. In unilateral thalamic infarcts, ipsilateral or contralateral tilts of perceived verticality can be differentiated by functional connectivity MRI. Rare cases of cortical rotational vertigo are due to a disconnection of interhemispheric pathways via the corpus callosum. About 30% of patients with vestibular migraine have a mild bilateral endolymphatic hydrops of the inner ear, especially in the vestibulum rather than the cochlea. Classical vestibular paroxysmia is caused by neurovascular cross-compression, which is most reliably detected by vestibular nerve angulation in DTI-MRI.SummaryThe general message of this selected review is that peripheral and central vestibular disorders do not present solely with purely vestibular signs and symptoms; they involve various levels of subcortical and cortical structures organized into neural networks.