Evaluation of Cerebral White Matter in Prelingually Deaf Children Using Diffusion Tensor Imaging

Abstract

This study compared white matter development in prelingually deaf and normal-hearing children using a tract-based spatial statistics (TBSS) method. Diffusion tensor imaging (DTI) was performed in 21 prelingually deaf (DEAF group) and 20 normal-hearing (HEAR group) subjects aged from 1.7 to 7.7 years. Using TBSS, we evaluated the regions of significant difference in fractional anisotropy (FA) between the groups. Correlations between FA values and age in each group were also analyzed using voxel-wise correlation analyses on the TBSS skeleton. Lower FA values of the white matter tract of Heschl's gyrus, the inferior frontooccipital fasciculus, the uncinate fasciculus, the superior longitudinal fasciculus, and the forceps major were evident in the DEAF group compared with those in the HEAR group below 4 years of age, while the difference was not significant in older subjects. We also found that age-related development of the white matter tracts may continue until 8 years of age in deaf children. These results imply that development of the cerebral white matter tracts is delayed in prelingually deaf children.

Assessing Cerebral White Matter Microstructure in Children With Congenital Sensorineural Hearing Loss: A Tract-Based Spatial Statistics Study

“…Therefore, it is not surprising to find motor tracts such as the corticospinal tracts showing higher AD and RD values in our cohort with CSNHL compared to the hearing children. Second, our relatively small sample size consisted of the children ranging from 4.1 to 13.5 years of age, which was different from some studies in the literature (Miao et al, 2013; Park et al, 2018). In addition, our study was limited by the fact that our two study groups were not matched by age with the CSNHL group being younger than the control group.…”

“…Our TBSS approach allowed for a broad characterization of between-group differences with stringent statistical corrections (Smith and Nichols, 2009). FA and MD are the two common diffusion indicators for DTI data, and they have been used to evaluate WM properties in various diseases, such as prelingual deafness and traumatic brain injury (Le Bihan et al, 2001; Hribar et al, 2014; Park et al, 2018). FA values are related to the WM microstructural integrity and directionality of axonal fibers within a voxel (Assaf and Pasternak, 2008).…”

“…This might be due to different analytical approaches with some studies using a whole-brain voxel-wise TBSS approach while others focusing on the specific regions of interests such as the auditory cortex. In addition, some studies adopted a combined approach using both the whole-brain TBSS and ROI methods, and some used a volumetric method to analyze the volumes of the auditory cortex (Emmorey et al, 2003; Park et al, 2018). For instance, a human study using a volumetric approach showed less WM in the HG leading to larger gray matter–WM ratio in the congenitally deaf adults compared to the hearing adults (Emmorey et al, 2003).…”

“…DTI is an established magnetic resonance imaging (MRI) method that measures the directionality of water diffusion in the brain and is more sensitive for detecting WM microstructural alterations than volumetric methods (Douaud et al, 2011). A prior DTI study found abnormal WM microstructure in adolescents with prelingual deafness, compared to healthy control adolescents (Park et al, 2018). Their study found lower fractional anisotropy (FA) values in the WM tract of the HG and inferior fronto-occipital fasciculus (IFOF), among other WM areas, in deaf children younger than 4 years but not in older children.…”

“…Prior studies of macrostructural differences in deaf people, compared to control participants without hearing loss, showed lower white matter (WM) volume but preserved gray matter volume in the auditory region, including the Heschl’s gyrus (HG) and the adjacent temporal lobe (Hribar et al, 2014). In addition to the reported WM macrostructural changes, there are also WM microstructural alterations in people with hearing loss (Kim et al, 2009; Miao et al, 2013; Park et al, 2018). However, less is known about the WM microstructural properties specifically in children with CSNHL.…”