Diffusion tensor imaging in children with unilateral hearing loss: a pilot study

Abstract

Objective: Language acquisition was assumed to proceed normally in children with unilateral hearing loss (UHL) since they have one functioning ear. However, children with UHL score poorly on speech-language tests and have higher rates of educational problems compared to normal hearing (NH) peers. Diffusion tensor imaging (DTI) is an imaging modality used to measure microstructural integrity of brain white matter. The purpose of this pilot study was to investigate differences in fractional anisotropy (FA) and mean diffusivity (MD) in hearing- and non-hearing-related structures in the brain between children with UHL and their NH siblings.Study Design: Prospective observational cohort.Setting: Academic medical center.Subjects and Methods: Sixty one children were recruited, tested and imaged. Twenty nine children with severe-to-profound UHL were compared to 20 siblings with NH using IQ and oral language testing, and MRI with DTI. Twelve children had inadequate MRI data. Parents provided demographic data and indicated whether children had a need for an individualized educational program (IEP) or speech therapy (ST). DTI parameters were measured in auditory and non-auditory regions of interest (ROIs). Between-group comparisons were evaluated with non-parametric tests.Results: Lower FA of left lateral lemniscus was observed for children with UHL compared to their NH siblings, as well as trends toward differences in other auditory and non-auditory regions. Correlation analyses showed associations between several DTI parameters and outcomes in children with UHL. Regression analyses revealed relationships between educational outcome variables and several DTI parameters, which may provide clinically useful information for guidance of speech therapy.Discussion/Conclusion: Our data suggests that white matter microstructural patterns in several brain regions are preserved despite unilateral rather than bilateral auditory input which contrasts with findings in patients with bilateral hearing loss.

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies

“…In a pilot study, Rachakonda et al (2014) In contrast to the more recent findings of Rachakonda et al (2014) and Vos et al (2015), Lin and colleagues (2008) found lower FA values on the contralateral side to the hearing loss in adults, while Wu et al (2008) showed a decrease in FA and an increase in MD in a group of subjects with UHL aged 8 -29 years. Thus, these two studies reveal microstructural alternations that could correlate to reorganization revealed by the change in the BOLDresponse in fMRI studies.…”

“…Usually reported is the fractional anisotropy (FA) with values ranging from 0 to 1 meaning from maximum isotropy with no perpendicular restriction to maximum anisotropy with total perpendicular restriction (Colombo et al 2009). Also reported is the mean diffusivity (MD) that ranges from 0 to 1 and measures how easily water diffuses averaged over all directions (Rachakonda et al 2014).…”

Diffusion tensor magnetic resonance imaging strategies for color mapping of human brain anatomy

“…DW-MRI has been demonstrated to be a valuable tool to study the human brain. [12345678910111213] In the meantime, it has had successful achievements that were shown in the clinical application of DW imaging (DWI). For instance, it was demonstrated that the earliest stages of ischemic events and changes in the apparent diffusion coefficients (ADC) were recorded and corresponded to changes in the ratio of extracellular/intracellular water content; this was proved to be very supportive in the early detection and assessment of strokes.…”

“…[2345678910111213] Indeed DTI provides unique quantitative information about brain tissue structure; with completely noninvasive mode while covering the entire brain. [12345678910111213141516171819] Consequently, diagonalizing the diffusion tensor allows calculating its eigenvalues and eigenvectors as well as sorted eigenvalues and eigenvectors. In such condition, the eigenvector corresponding to the largest eigenvalue is considered to represent the major diffusion direction within the concerned voxel.…”

“…Thus, mapping directions are made up of the principal eigenvectors which can be generated, providing a striking visualization of the white matter tracts and corresponding orientation. [1234567891011121314]…”