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. 2024 Apr 12;34(4):bhae145. doi: 10.1093/cercor/bhae145

Early-stage use of hearing aids preserves auditory cortical structure in children with sensorineural hearing loss

Di Yuan 1,2, Elizabeth Tournis 3, Maura E Ryan 4,5, Ching Man Lai 6, Xiujuan Geng 7, Nancy M Young 8,9,10,✉, Patrick C M Wong 11,12,✉
PMCID: PMC11021813  PMID: 38610087

Abstract

Hearing is critical to spoken language, cognitive, and social development. Little is known about how early auditory experiences impact the brain structure of children with bilateral sensorineural hearing loss. This study examined the influence of hearing aid use and residual hearing on the auditory cortex of children with severe to profound congenital sensorineural hearing loss. We evaluated cortical preservation in 103 young pediatric cochlear implant candidates (55 females and 48 males) by comparing their multivoxel pattern similarity of auditory cortical structure with that of 78 age-matched children with typical hearing. The results demonstrated that early-stage hearing aid use preserved the auditory cortex of children with bilateral congenital sensorineural hearing loss. Children with less residual hearing experienced a more pronounced advantage from hearing aid use. However, this beneficial effect gradually diminished after 17 months of hearing aid use. These findings support timely fitting of hearing aids in conjunction with early implantation to take advantage of neural preservation to maximize auditory and spoken language development.

Keywords: amplification, auditory cortex, cochlear implant candidate, residual hearing

Introduction

Children with any degree of sensorineural hearing loss (SNHL) may face various challenges that can influence different aspects of development. Compared to children with typical hearing, these individuals are at a higher risk of experiencing delayed spoken language development (Stelmachowicz et al. 2004; Wake et al. 2005; Moeller et al. 2007; Lederberg et al. 2013), poorer academic performance (Daud et al. 2010; Kuppler et al. 2013), as well as difficulties in acquiring social skills in the hearing world (Peterson 2004; Toe and Paatsch 2010). For these reasons, universal newborn hearing screening has been implemented or recommended in many countries so that early intervention could be prescribed for families who see hearing as essential for their children's overall development (Kennedy et al. 2005; Fukushima et al. 2008; Gaffney et al. 2010; Ptok 2011).

Hearing aids (HAs) and cochlear implants (CIs) are two common medical interventions for SNHL when hearing loss is viewed as a deficit and hearing and spoken language are developmental goals. Children with mild-to-severe SNHL fitted earlier or with longer HA use exhibit improved speech and language performance (Tomblin et al. 2014, 2015). However, children with SNHL in the severe to profound range have limited access to sound through HAs, particularly in terms of speech audibility (Leal et al. 2016; Nickerson et al. 2019). Consequently, these children become candidates for cochlear implantation. While the practice is not universally adopted, some pediatric CI candidates may receive HAs and aural habilitation prior to the implantation procedure. However, even when children are diagnosed in infancy and fitted with HAs soon after diagnosis, implantation may not be applied in a timely manner. Early referral or family follow-through after referral may not occur, resulting in a longer period of HA use and older age at implantation. Under such circumstances, it remains largely unknown how the preoperative hearing experiences, such as HA use and residual hearing, impact speech and language development in children with severe to profound SNHL.

The benefits of early intervention, including HA fitting and CI activation, on spoken language development have consistently been supported by previous studies (Ching et al. 2018). For example, a multicenter study involving 350 children with bilateral hearing loss revealed that those who received CIs or HAs at an earlier stage exhibited better spoken language abilities at the age of 5 or 6 (Ching et al. 2017). In pediatric CI users, earlier preoperative HA fitting was associated with better post-CI outcomes, such as receptive vocabulary (Geers et al. 2007), speech intelligibility (Artières et al. 2009), comprehension of spoken language (Percy-Smith et al. 2013), and general language abilities (Nicholas and Geers 2006). However, prolonged use of HAs showed a negative impact on post-CI language comprehension, expression abilities (Niparko et al. 2010), and communication abilities (Hyde et al. 2011). Jallu et al. (2019) found that the beneficial effect of HAs diminished after 18 months for children with profound SNHL, whereas children with CIs showed significant improvement in speech perception and language development. Since early CI activation was associated with better speech and language abilities (Tobey et al. 2013; Dettman et al. 2016, 2021; Karltorp et al. 2020), prolonged duration of HA use may delay the crucial CI activation time, resulting in poor speech and language abilities. These findings imply a nonlinear relationship between the duration of preoperative HA use and postoperative language development in pediatric CI candidates. In addition, it is worth noting that other factors, such as residual hearing (Davidson et al. 2019), parental linguistic input (Quittner et al. 2013; Dilley et al. 2020; Holzinger et al. 2020), socioeconomic status (Perkins et al. 2013), and communication mode (Hall et al. 2019), also influence the speech and language development of children with hearing loss.

Furthermore, the effects of intervention can vary among children with different levels of hearing loss severity. Residual hearing, which is determined by pure tone audiometry and represented by pure tone thresholds, serves as an estimation of hearing loss severity. Ching et al. (2017) found that children with less residual hearing in their better ears obtained greater benefits from early HA fitting across a wide spread of aspects, including language, academic performance, social skills, and quality of life. No statistical significance was reported for the interaction effect between better-ear residual hearing and the time of HA fitting, though. In addition, Tomblin et al. (2020) investigated the impact of better-ear residual hearing (unaided hearing) and speech perception provided by HAs (aided hearing) on spoken language and academic outcomes in second- or fourth-grade children with mild-to-severe hearing loss. They found that better unaided hearing was associated with better spoken language abilities. Such an association between unaided hearing and spoken language ability was weaker in children with better aided hearing levels. These findings suggest that when HAs provide sufficient speech information to support spoken language development, the impact of unaided hearing on spoken language skills decreases. Thus, both the quality and quantity of HA use interact with residual hearing to influence spoken language development in children with hearing loss. However, compared to CIs, children with less residual hearing received less benefit from HAs than those with more residual hearing (Bittencourt et al. 2012). Leigh et al. (2016) reported a 75% chance of speech perception improvement for an ear with less residual hearing (pure tone threshold >60 dB HL) when using a CI compared to a HA.

The effect of interventions and residual hearing also manifests in the brains of children with hearing loss. HAs and CIs preserve or restore brain function and structure that have been altered by hearing loss (Glick and Sharma 2017; Grégoire et al. 2022). Specifically, on the one hand, compared to children with normal hearing, those with hearing loss showed reduced speech- and auditory-evoked activations with respect to cortical auditory-evoked potentials measured by electroencephalography (EEG) (Sharma et al. 2013, 2015), and dynamic oxyhemoglobin changes in auditory, auditory association, and attention areas measured by functional magnetic resonance imaging (fMRI) (Propst et al. 2010). On the other hand, a near-infrared spectroscopy study demonstrated that 78% of pediatric CI users showed cortical responses to acoustic speech stimuli in the auditory cortex that were comparable to children with normal hearing (Sevy et al. 2010). Similar findings of cortical activation to acoustic stimuli in the auditory cortex were also found for pediatric CI and HA users in EEG studies (Korczak et al. 2005; Polonenko et al. 2019; Ni et al. 2021). Moreover, Yuan et al. (2023) examined the brain structure of 21 Chinese pediatric CI candidates before surgery. They found that children with more residual hearing exhibited a larger gray matter (GM) volume ratio (corrected by total intracranial volume) in the left auditory cortex. Besides, children with more residual hearing benefited more from a longer duration of HA in terms of a larger GM volume ratio compared to those with less residual hearing.

Cortical preservation is crucial for children with hearing loss as the preserved brain functions and structures are fundamental to auditory skills and spoken language development. In an fMRI study with 10 children with severe to profound hearing loss, researchers measured the children’s neural activity in the primary auditory cortex in response to auditory stimulations before CI (Patel et al. 2007). The number of activated pixels was positively related to the improvement of hearing threshold measured by pure tone audiometry after CI. In a subsequent fMRI study, Deshpande et al. (2016) assessed the language skills of 11 children after 2 years of CI. They found that the post-CI spoken language performance was positively related to the pre-CI auditory-evoked neural activation in the temporal–parietal–occipital junction, prefrontal cortex, and cingulate gyrus. In addition to brain function, brain structure has also been shown to predict post-CI outcomes. Feng et al. (2018) used the preoperative neuroanatomical features of children with SNHL to predict their speech perception improvement, as measured by Speech Recognition Index in Quiet (Wang et al. 2008), 6 months after CI. They calculated the multivoxel pattern similarity (MVPS) of the neuroanatomical density [i.e. the proportion of GM or white matter (WM) relative to all tissue types within a region] between children with SNHL and children with normal hearing. The MVPS measures the similarity of local spatial morphological patterns. In the context of children with SNHL, a higher similarity of neuroanatomical density indicates a better-preserved brain structure. Researchers found that better-preserved brain regions, including auditory association and cognitive areas, could precisely predict post-CI outcomes. These findings were supported in a subsequent diffusion tensor imaging study revealing that the better-preserved preoperative WM regions played a critical role in predicting speech perception abilities up to 6 months after CI (Geng et al. 2022). Furthermore, both Feng et al.’s (2018) and Geng et al.’s (2022) studies demonstrated that the models with only neural features performed better than those with non-neural features in predicting post-CI speech and language outcomes.

Therefore, this study aims to investigate how HA use and residual hearing impact the auditory cortex in children with severe to profound SNHL. Based on the findings of Yuan et al.’s (2023) study, this study extends the earlier investigation to a much larger sample of children (n = 103) in the United States. The purpose is to examine whether the interaction effect between the duration of HA use and residual hearing can be replicated in a population with a different cultural environment. It is known that the cultural environment has a significant impact on neural features (Han and Northoff 2008; Ge et al. 2023). In addition, instead of using the absolute amount of brain structure (GM volume), we calculated the neuroanatomical preservation (GM density similarity) using a group of children with normal hearing as a control to provide a comparative perspective for better generalization. Preservation is equated with less cortical structural alteration resulting from deficient auditory stimulation. Considering that longer duration of HA delays the timing of CI activation, we hypothesize that early-stage HA use contributes to the neuroanatomical preservation in the auditory cortex of children with severe to profound SNHL. However, this beneficial effect would diminish with prolonged HA use due to late CI activation. Moreover, children with less residual hearing benefit more from HA use at early stage.

Materials and methods

Participants

One hundred and three children (55 females) with SNHL who were being evaluated as CI candidates were included. Inclusion criteria were (1) congenital and nonprogressive bilateral SNHL, (2) spoken language used at home, (3) no additional disabilities expected to impact auditory cortical structures, and (4) no gross brain malformation. All children were fitted with HAs and received aural habilitation. All underwent high-resolution 3-T T1-weighted structural whole-brain MRI as part of their pre-CI evaluation. The duration of HA use was defined as the time between the HA fitting date (document in medical record or, if no available record, reported by parent) and the MRI scan date. The mean (SD, range) age at the time of MRI was 15.8 (11.5, 5~57) months. The mean (SD, range) age at HA fitting was 7.3 (7.9, 1~42) months. The mean time (SD, range) between HA fitting and MRI scan (i.e. duration of HA use) was 8.1 (8.5, 1~49) months. Moreover, residual hearing was assessed by unaided pure-tone average (PTA) at 500 Hz, 1 kHz, and 2 kHz for each ear. Mean (SD) PTA: both ears = 99.5 (12.9) dB HL; better ear = 96.2 (15.2) dB HL. Out of the total sample (n = 103), 4 (3.9%) children had moderately severe SNHL (56–70 dB HL), 22 (21.4%) children had severe SNHL (71–90 dB HL), and 77 (74.8%) children had profound SNHL (>91 dB HL). Mean (SD) PTA difference between the two ears was 6.7 (7.8) dB HL, with differences ranging from 0 to 41.7 dB HL. Among the participants, 18 exhibited symmetrical PTA (i.e. PTA difference of 0), while 44 had a lower PTA in the right ear, and 41 had a lower PTA in the left ear. Parents and guardians provided their understanding and written informed consent, which included permission to use the children’s MRI scans and clinical outcome data in this study.

For anatomical comparison, the brain neuroanatomy of the children with SNHL was compared to data on 78 children without hearing loss from the National Institutes of Health (NIH) MRI Study of Normal Brain Development (PedsMRI; https://pediatricmri.nih.gov/nihpd/info/index.html) (Almli et al. 2007). Considering the significant impact of age (Shaw et al. 2008; Giedd and Rapoport 2010), gender (Ruigrok et al. 2014), and socioeconomic status (Tooley et al. 2021) on brain structures, the control group was matched with the SNHL group in terms of age, sex, and household income (P > 0.05).

This study was approved by the Stanley Manne Children’s Research Institute’s Institutional Review Board.

MRI acquisition and analysis

The T1-weighted images of the children with SNHL were obtained on a 3-T Siemens scanner (MAGNETOM Skyra, Vida) using a magnetization-prepared rapid gradient-echo sequence or on a 3-T General Electric MR scanner (DISCOVERY MR750; SIGNA Architect) using a 3D brain volume (BRAVO) sequence. The scanning parameters were optimized to obtain a good signal-to-noise ratio (GE scanner: TE = 3.34~3.91 ms, TR = 8.58~9.44 ms, flip angle = 12°, matrix = 512 × 512, number of slices = 148~252, slice thickness = 1.2~2 mm, voxel size = 0.3 × 0.3 × 0.6~0.5 × 0.5 × 1.4 mm; Siemens scanner: TE = 2.38~3.54 ms, TR = 1490~2200 ms, flip angle = 8~9°, matrix = 192 × 192~512 × 512, number of slices = 108~224, slice thickness = 0.8~1 mm, voxel size = 0.8 × 0.8 × 0.9~1 × 1 × 1 mm). The T1-weighted images of the control group were downloaded from the NIH open-access database (TE = 10 ms, TR = 500 ms, flip angle = 90°, matrix = 256 × 192, 30~60 slices of 3-mm thickness, voxel size = 1 × 1 × 3 mm) (Almli et al. 2007).

The GM density maps of all the participants were obtained by conducting the following procedure in CAT12 toolbox (Gaser et al. 2022) implemented in Statistical Parametric Mapping 12 (SPM12) software (Penny et al. 2011). The intensity inhomogeneity correction and strong non-local means (SANLM) noise correction were conducted on T1-weighted images. A 13-month-old tissue probability template was generated by the CerebroMatic Toolbox (Wilke et al. 2017) and was used to guide the initial SPM segmentation. A medium level of local adaptive segmentation with a medium to strong level of myelin correction was applied before the final Adaptive Maximum A Posterior (AMAP) segmentation, which segments the images into GM, WM, and cerebrospinal fluid. A medium level of final clean-up was used to remove the remaining meninges and correct for partial volume effects. The segmented brain tissues for each participant were then spatially normalized by using a 13-month-old Diffeomorphic Anatomical Registration through an Exponentiated Lie Algebra (DARTEL) template generated by the CerebroMatic Toolbox (Ashburner 2007; Wilke et al. 2017). The scans were further smoothed with a 4-mm full-width at half-maximum Gaussian kernel.

To examine the similarity of GM density in local spatial morphological pattern between the two groups of children (SNHL and normal hearing), the MVPS analysis was applied using the CoSMoMVPA toolbox (Oosterhof et al. 2016). The GM density maps were firstly restricted with a mask created from the DARTEL template with the minimum probability value of 0.5. Then, the searchlight approach with a 4-voxel-radius sphere (217 voxels on average across regions) centered on each voxel was used to define the local spatial extent (Feng et al. 2018). Pearson correlation was used to calculate the local pattern similarity for each of the local spheres for each pair of individuals across the two groups. The r values were normalized by Fisher’s r to z transformation, and all the obtained z-maps for each child with HL were averaged. Finally, a similarity map was acquired to represent the GM similarity of each child with SNHL compared to children with typical hearing.

Four regions of interest (ROIs) (Fig. 1) were selected including the left and right Heschl’s gyrus (HG) and left and right superior temporal gyrus (STG) as defined by the University of North Carolina (UNC) infant 0-1-2 atlases (http://bric.unc.edu/ideagroup/free-softwares/unc-infacnt-0-1-2-atlases, Shi et al. 2011). The mean GM similarity (GM preservation) was calculated within each ROI and within HG or STG across two hemispheres for further analysis. One participant with GM preservation of the left HG that was 2.5 SDs below the mean value was excluded from HG analyses, resulting in 102 participants for analysis for left, right, and bilateral HG and 103 participants for analysis for left, right, and bilateral STG. In addition, bilateral thalamus (THA) as a non-sensory region was selected as a GM control region.

Fig. 1.

Fig. 1

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Axial view of cortical regions of interest (ROIs). Red regions represent Heschl’s gyrus; green regions represent the superior temporal gyrus. Blue regions represent the thalamus. The numbers represent the z coordinates of the Montreal Neurological Institute (MNI) coordinate system.

Statistical analysis

Multiple regression analysis was applied to examine the effect of PTA and duration of HA use on neuroanatomy. To examine the nonlinear relationship between duration of HA use and neuroanatomy, a quadratic term of duration of HA use (indicated by a superscript 2) was included in the regression model. The regression model was conducted with GM preservation as the dependent variable, and age, gender, household income, duration of HA use, duration of HA use2, PTA, duration of HA use × PTA, and duration of HA use2 × PTA as independent variables. Age, gender, and household income were controlled as covariates in the model. The interaction effects (marked with a “×”) examined whether the effect of duration of HA use on GM preservation holds across different degrees of residual hearing (PTA). PTA and duration of HA use were mean-centered for better interpretation of the interaction effect. An F test was used to examine the overall significance of the model, while the Wald test was used to examine the significance of each variable. Since the regression analysis was conducted for each ROI, the P value of the F test for each ROI was adjusted for multiple comparisons using the false discovery rate correction. The turning point of duration of HA use2 was calculated by Inline graphic while controlling the effect of other factors in the regression model. Inline graphic represents the coefficient of duration of HA use and Inline graphic represents the coefficient of duration of HA use2. This study is based on well-established hypotheses that enable us to be more targeted in our investigations. Therefore, we have limited the study to two ROIs (right, left, and bilateral for each) and one control region, minimizing the number of comparisons to be performed.

To provide converging evidence for the effect of duration of HA use on GM preservation, we further examined the main and interaction effects using machine learning. On the one hand, the regression model provides straightforward interpretations of the coefficients, indicating the direction and magnitude of the relationship between the variables. On the other hand, machine learning with a cross-validation procedure sacrifices some interpretability in favor of improved performance by incorporating model selection, hyperparameter tuning, and estimating the model’s performance on different subsets of data (unseen data). This approach allows for a robust evaluation of its generalization capabilities. A nested k-fold cross-validation procedure with a supported vector regression (SVR) classifier was used for prediction (Smola and Schölkopf 2004). In the inner level with k − 1 folds, optimized parameters were selected by the grid search strategy. Then, the parameters were applied to the outer level to test the 1-fold independent samples. The predictability was measured by the Pearson correlation between the predicted values and the observations. The higher the correlation, the more accurate the predictive performance of the model. To test the significance of predictability, a permutation test was conducted by shuffling the observed data following the same nested k-fold cross-validation procedure. A null distribution was obtained by repeating the permutation test 1,000 times.

A two-tailed test was used for all analyses. Statistical significance was set at P <0.05 level for variables to be entered into the regression models. The regression analysis was performed using R-4.1.2 (R Core Team 2021) and machine learning was performed using Python 3.9.12 with the scikit-learn module (Pedregosa et al. 2011).

Results

Although analysis results for all ROIs of interest are presented in the tables and figures, for purposes of brevity and because it was the focus of the prior pilot study (Yuan et al. 2023), findings for the left HG are the primary focus here. The regression equation to predict GM preservation of the left HG was significant when bilateral PTA was tested, F(8,93) = 5.608, corrected P < 0.001, R2 = 0.325. A nonlinear relationship was found between duration of HA use and GM preservation (duration of HA use2: β = −0.373, P = 0.04, Table 1). This relationship was characterized by an inverted U-shaped pattern between duration of HA use and GM preservation, as depicted in Fig. 2A. Specifically, longer duration of HA use during the early stage, before the turning point of 17 months, was associated with better GM preservation. However, further use of HAs, specifically after 17 months, resulted in diminishing preservation of the left HG in children with SNHL. A significant interaction effect was found between the duration of HA use2 and PTA, indicating that the nonlinear relationship between duration of HA use and GM preservation varied among children with different degrees of bilateral PTA (duration of HA use2 × PTA: β = −0.341, P = 0.04, Table 1). Duration of HA use by children with higher PTA (less residual hearing) versus lower PTA has more impact on the degree of GM preservation, as indicated by a negative coefficient of the interaction term as well as a steeper curve for children with less residual hearing in Fig. 2B. Specifically, compared to children with more residual hearing, those with less residual hearing exhibited not only a rapid increase in GM preservation with a longer duration of HA use at the early stage but also a rapid decrease in GM preservation with further use of HA after the turning point.

Table 1.

Multiple linear regression models to assess the effect of duration of HA use and bilateral PTA.

B S.E. Beta t P
Left HG Constant 0.821 0.043 18.874 <0.001
n = 102 Age 0.006 0.001 0.508 4.008 <0.001
R 2 = 0.33 Gender 0.066 0.022 0.259 2.955 0.004
P corr < 0.001 Household income <−0.001 <0.001 −0.028 −0.315 0.754
Duration of HA use −0.335 0.247 −0.263 −1.359 0.177
Duration of HA use2 −0.475 0.228 −0.373 −2.085 0.040
Bilateral PTA −0.001 0.001 −0.124 −1.348 0.181
Duration of HA use × bilateral PTA <−0.001 0.010 −0.003 −0.022 0.983
Duration of HA use2 × bilateral PTA −0.021 0.010 −0.341 −2.109 0.038
Right HG Constant 0.852 0.037 23.228 <0.001
n = 102 Age 0.003 0.001 0.336 2.537 0.013
R 2 = 0.27 Gender 0.049 0.019 0.239 2.614 0.010
P corr < 0.001 Household income <0.001 <0.001 0.021 0.225 0.822
Duration of HA use 0.070 0.208 0.068 0.335 0.739
Duration of HA use2 −0.217 0.192 −0.211 −1.131 0.261
Bilateral PTA −0.001 0.001 −0.072 −0.757 0.451
Duration of HA use × bilateral PTA 0.006 0.008 0.120 0.733 0.465
Duration of HA use2 × bilateral PTA −0.010 0.008 −0.196 −1.165 0.247
Bilateral HG Constant 0.837 0.035 24.089 <0.001
n = 102 Age 0.004 0.001 0.477 3.851 <0.001
R 2 = 0.36 Gender 0.057 0.018 0.276 3.232 0.002
P corr < 0.001 Household income <−0.001 <0.001 −0.007 −0.078 0.938
Duration of HA use −0.133 0.197 −0.128 −0.675 0.501
Duration of HA use2 −0.346 0.182 −0.332 −1.903 0.060
Bilateral PTA −0.001 0.001 −0.112 −1.244 0.216
Duration of HA use × bilateral PTA 0.003 0.008 0.057 0.373 0.710
Duration of HA use2 × bilateral PTA −0.015 0.008 −0.305 −1.936 0.056
Left STG Constant 1.042 0.043 24.329 <0.001
n = 103 Age 0.006 0.001 0.493 4.220 <0.001
R 2 = 0.43 Gender 0.042 0.022 0.153 1.908 0.059
P corr < 0.001 Household income <−0.001 <0.001 −0.211 −2.621 0.010
Duration of HA use 0.104 0.244 0.075 0.425 0.672
Duration of HA use2 −0.043 0.225 −0.031 −0.190 0.850
Bilateral PTA <0.001 0.001 0.032 0.382 0.704
Duration of HA use × bilateral PTA 0.007 0.010 0.104 0.722 0.472
Duration of HA use2 × bilateral PTA −0.009 0.010 −0.144 −0.972 0.334
Right STG Constant 1.110 0.047 23.505 <0.001
n = 103 Age 0.007 0.002 0.549 4.573 <0.001
R 2 = 0.39 Gender 0.033 0.024 0.115 1.391 0.168
P corr < 0.001 Household income <−0.001 <0.001 −0.189 −2.283 0.025
Duration of HA use 0.205 0.269 0.139 0.763 0.447
Duration of HA use2 0.200 0.248 0.136 0.806 0.422
Bilateral PTA <−0.001 0.001 −0.030 −0.345 0.731
Duration of HA use × bilateral PTA 0.012 0.011 0.168 1.128 0.262
Duration of HA use2 × bilateral PTA 0.004 0.011 0.061 0.398 0.691
Bilateral STG Constant 1.078 0.042 25.828 <0.001
n = 103 Age 0.006 0.001 0.549 4.773 <0.001
R 2 = 0.44 Gender 0.037 0.021 0.139 1.758 0.082
P corr < 0.001 Household income <−0.001 <0.001 −0.209 −2.635 0.010
Duration of HA use 0.157 0.237 0.115 0.659 0.511
Duration of HA use2 0.084 0.219 0.062 0.383 0.703
Bilateral PTA <−0.001 0.001 −0.001 −0.017 0.987
Duration of HA use × bilateral PTA 0.010 0.009 0.145 1.021 0.310
Duration of HA use2 × bilateral PTA −0.002 0.009 −0.035 −0.241 0.810
Left THA Constant 1.860 0.047 39.720 <0.001
n = 103 Age 0.004 0.002 0.343 2.413 0.018
R 2 = 0.14 Gender −0.010 0.024 −0.041 −0.415 0.679
P corr = 0.073 Household income <−0.001 <0.001 −0.038 −0.384 0.702
Duration of HA use −0.152 0.266 −0.124 −0.571 0.569
Duration of HA use2 −0.277 0.245 −0.226 −1.130 0.261
Bilateral PTA −0.001 0.001 −0.069 −0.672 0.503
Duration of HA use × bilateral PTA <0.001 0.011 0.006 0.031 0.975
Duration of HA use2 × bilateral PTA −0.011 0.011 −0.188 −1.041 0.301
Right THA Constant 1.869 0.044 42.484 <0.001
n = 103 Age 0.002 0.001 0.205 1.408 0.162
R 2 = 0.10 Gender −0.002 0.022 −0.011 −0.109 0.913
P corr = 0.226 Household income <−0.001 <0.001 −0.089 −0.885 0.379
Duration of HA use −0.157 0.250 −0.139 −0.627 0.532
Duration of HA use2 −0.315 0.231 −0.279 −1.366 0.175
Bilateral PTA <−0.001 0.001 −0.014 −0.133 0.894
Duration of HA use × bilateral PTA −0.004 0.010 −0.066 −0.368 0.713
Duration of HA use2 × bilateral PTA −0.015 0.010 −0.271 −1.470 0.145
Bilateral THA Constant 1.864 0.044 42.104 <0.001
n = 103 Age 0.003 0.001 0.284 1.972 0.052
R 2 = 0.13 Gender −0.006 0.023 −0.027 −0.273 0.786
P corr = 0.125 Household income <−0.001 <0.001 −0.064 −0.644 0.521
Duration of HA use −0.155 0.252 −0.134 −0.613 0.541
Duration of HA use2 −0.296 0.232 −0.258 −1.276 0.205
Bilateral PTA <−0.001 0.001 −0.044 −0.420 0.676
Duration of HA use × bilateral PTA −0.002 0.010 −0.030 −0.168 0.867
Duration of HA use2 × bilateral PTA −0.013 0.010 −0.234 −1.281 0.203
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S.E., standard error; HG, Heschl’s gyrus; STG, superior temporal gyrus; THA, thalamus; HA, hearing aid; PTA, pure-tone average; Pcorr, corrected P.

Fig. 2.

Fig. 2

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The nonlinear effect of duration of HA use on gray matter preservation in the left Heschl’s gyrus. A) The main effect of duration of HA use2 on GM preservation in the left Heschl’s gyrus when considering bilateral PTA. B) The moderation effect of bilateral PTA. The left panel illustrates the effect of duration of HA use on GM preservation for children with more residual hearing (bilateral PTA < 81 dB HL, mean value minus 1 SD), while the right panel shows the effect of duration of HA use on GM preservation for children with less residual hearing (bilateral PTA > 111 dB HL, mean value plus 1 SD). C) and D) show the main effect and moderation effect of better-ear PTA, and more or less residual hearing based on better-ear PTA. Instead of showing the observed values, the figures show the partial residuals controlling the effects of variables besides the predictor. HG, Heschl’s gyrus; HA, hearing aid; GM, gray matter.

When bilateral PTA was tested, the regression equations to predict GM preservation were also significant for right HG, F(8,93) = 4.222, corrected P < 0.001, R2 = 0.266; bilateral HG, F(8,93) = 6.45, corrected P < 0.001, R2 = 0.357; left STG, F(8,94) = 8.686, corrected P < 0.001, R2 = 0.425; right STG, F(8,94) = 7.554, corrected P < 0.001, R2 = 0.391; and bilateral STG, F(8,94) = 9.287, corrected P < 0.001, R2 = 0.441. However, the noted effect of duration of HA use and bilateral PTA was not found in these ROIs. The regression equations to predict GM preservation were not significant for the control ROIs such as left THA, F(8,94) = 1.984, corrected P = 0.073, R2 = 0.144; right THA, F(8,94) = 1.357, corrected P = 0.226, R2 = 0.104; and bilateral THA, F(8,94) = 8.689, corrected P = 0.125, R2 = 0.126.

When the better-ear PTA was tested, the findings were consistent with the results obtained for bilateral PTA for the ROIs (Table 2, Fig. 2C and D).

Table 2.

Multiple linear regression models to access the effect of HA use and better-ear PTA.

B S.E. Beta t P
Left HG Constant 0.821 0.044 18.809 <0.001
n = 102 Age 0.006 0.001 0.507 4.001 <0.001
R 2 = 0.33 Gender 0.067 0.022 0.264 2.996 0.004
P corr < 0.001 Household income <−0.001 <0.001 −0.027 −0.304 0.762
Duration of HA use −0.282 0.224 −0.221 −1.257 0.212
Duration of HA use2 −0.411 0.200 −0.323 −2.060 0.042
Better-ear PTA −0.001 0.001 −0.122 −1.336 0.185
Duration of HA use × better-ear PTA 0.003 0.007 0.055 0.385 0.701
Duration of HA use2 × better-ear PTA −0.015 0.007 −0.310 −2.116 0.037
Right HG Constant 0.853 0.037 23.156 <0.001
n = 102 Age 0.003 0.001 0.332 2.517 0.014
R 2 = 0.27 Gender 0.050 0.019 0.245 2.667 0.009
P corr < 0.001 Household income <0.001 <0.001 0.017 0.187 0.852
Duration of HA use 0.077 0.189 0.075 0.406 0.686
Duration of HA use2 −0.202 0.169 −0.196 −1.199 0.234
Better-ear PTA −0.001 0.001 −0.089 −0.937 0.351
Duration of HA use × better-ear PTA 0.006 0.006 0.141 0.940 0.349
Duration of HA use2 × better-ear PTA −0.007 0.006 −0.189 −1.236 0.219
Bilateral HG Constant 0.837 0.035 24.019 <0.001
n = 102 Age 0.004 0.001 0.474 3.837 <0.001
R 2 = 0.36 Gender 0.058 0.018 0.282 3.287 0.001
P corr < 0.001 Household income <−0.001 <0.001 −0.008 −0.091 0.927
Duration of HA use −0.103 0.179 −0.098 −0.573 0.568
Duration of HA use2 −0.307 0.159 −0.294 −1.924 0.057
Better-ear PTA −0.001 0.001 −0.119 −1.332 0.186
Duration of HA use × better-ear PTA 0.004 0.006 0.103 0.738 0.462
Duration of HA use2 × better-ear PTA −0.011 0.006 −0.283 −1.980 0.051
Left STG Constant 1.042 0.043 24.234 <0.001
n = 103 Age 0.006 0.001 0.487 4.179 <0.001
R 2 = 0.43 Gender 0.041 0.022 0.151 1.870 0.065
P corr < 0.001 Household income <−0.001 <0.001 −0.208 −2.572 0.012
Duration of HA use 0.112 0.221 0.081 0.504 0.615
Duration of HA use2 −0.029 0.197 −0.021 −0.149 0.882
Better-ear PTA 0.001 0.001 0.060 0.712 0.478
Duration of HA use × better-ear PTA 0.006 0.007 0.109 0.828 0.410
Duration of HA use2 × better-ear PTA −0.008 0.007 −0.147 −1.095 0.276
Right STG Constant 1.112 0.047 23.420 <0.001
n = 103 Age 0.007 0.002 0.546 4.547 <0.001
R 2 = 0.39 Gender 0.034 0.024 0.116 1.400 0.165
P corr < 0.001 Household income <−0.001 <0.001 −0.193 −2.317 0.023
Duration of HA use 0.175 0.244 0.119 0.717 0.475
Duration of HA use2 0.169 0.217 0.115 0.779 0.438
Better-ear PTA <−0.001 0.001 −0.029 −0.332 0.741
Duration of HA use × better-ear PTA 0.008 0.008 0.145 1.074 0.285
Duration of HA use2 × better-ear PTA 0.002 0.008 0.042 0.305 0.761
Bilateral STG Constant 1.079 0.042 25.715 <0.001
n = 103 Age 0.006 0.001 0.544 4.735 <0.001
R 2 = 0.44 Gender 0.037 0.021 0.139 1.744 0.084
P corr < 0.001 Household income <−0.001 <0.001 −0.210 −2.629 0.010
Duration of HA use 0.145 0.216 0.107 0.671 0.504
Duration of HA use2 0.074 0.192 0.055 0.387 0.699
Better-ear PTA <0.001 0.001 0.013 0.153 0.879
Duration of HA use × better-ear PTA 0.007 0.007 0.135 1.040 0.301
Duration of HA use2 × better-ear PTA −0.002 0.007 −0.047 −0.356 0.722
Left THA Constant 1.857 0.047 39.584 <0.001
n = 103 Age 0.004 0.001 0.342 2.411 0.018
R 2 = 0.15 Gender −0.009 0.024 −0.037 −0.373 0.710
P corr = 0.064 Household income <−0.001 <0.001 −0.032 −0.327 0.744
Duration of HA use −0.173 0.242 −0.140 −0.715 0.476
Duration of HA use2 −0.297 0.214 −0.241 −1.384 0.170
Better-ear PTA <−0.001 0.001 −0.056 −0.554 0.581
Duration of HA use × better-ear PTA <0.001 0.008 0.002 0.013 0.989
Duration of HA use2 × better-ear PTA −0.010 0.008 −0.215 −1.318 0.191
Right THA Constant 1.867 0.044 42.427 <0.001
n = 103 Age 0.002 0.001 0.208 1.435 0.154
R 2 = 0.11 Gender −0.002 0.022 −0.010 −0.101 0.920
P corr = 0.183 Household income <−0.001 <0.001 −0.083 −0.826 0.411
Duration of HA use −0.148 0.227 −0.131 −0.653 0.515
Duration of HA use2 −0.296 0.201 −0.262 −1.472 0.144
Better-ear PTA <−0.001 0.001 −0.029 −0.280 0.780
Duration of HA use × better-ear PTA −0.001 0.007 −0.016 −0.098 0.922
Duration of HA use2 × better-ear PTA −0.012 0.007 −0.287 −1.724 0.088
Bilateral THA Constant 1.862 0.044 42.029 <0.001
n = 103 Age 0.003 0.001 0.284 1.986 0.050
R 2 = 0.13 Gender −0.006 0.023 −0.024 −0.247 0.805
P corr = 0.101 Household income <−0.001 <0.001 −0.058 −0.585 0.560
Duration of HA use −0.160 0.228 −0.139 −0.703 0.484
Duration of HA use2 −0.296 0.203 −0.258 −1.464 0.147
Better-ear PTA <−0.001 0.001 −0.044 −0.432 0.667
Duration of HA use × better-ear PTA <−0.001 0.007 −0.007 −0.042 0.967
Duration of HA use2 × better-ear PTA −0.011 0.007 −0.256 −1.555 0.123
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S.E., standard error; HG, Heschl’s gyrus; STG, superior temporal gyrus; THA, thalamus; HA, hearing aid; PTA, pure-tone average; Pcorr, corrected P.

The figures show the effect of duration of HA use and PTA on preservation of left HG while controlling for the effects of age, gender, and household income. Note in Tables 1 and 2 that age contributed significantly to the prediction of GM for most ROIs as did gender for HG and STG. Male children showed better preservation compared to female children, while older children showed better GM preservation than younger children. Moreover, household income was also found to be a significant predictor of GM preservation at the STG. However, duration of HA use2 and the interaction between duration of HA use2 and PTA contributed additional significant prediction for left HG gray matter after controlling for the demographic factors.

To determine whether there is converging evidence that the effect of duration of HA use on GM preservation does not hold across different degrees of PTA, machine learning was applied to evaluate evidence for the interaction effect of duration of HA use and PTA on GM preservation of the left HG and to test the generalizability of our findings. Two models were built, one with and one without the interaction term of duration of HA use2 × PTA. The predictability for both models was significantly higher than that of the null distribution as tested by the two-sample t test, Ps < 0.001 (Fig. 3). When bilateral PTA was tested, the mean predictability was main = 0.44, interaction = 0.45, and null = −0.04. When better-ear PTA was tested, the mean predictability was main = 0.43, interaction = 0.45, and null = −0.04. Moreover, the predictability of the model with the interaction term was significantly higher than that of the model without the interaction term (P < 0.001).

Fig. 3.

Fig. 3

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Prediction of GM preservation in the left Heschl’s gyrus using machine learning (SVR). The models in panel A) were tested by bilateral PTA, and the models in panel B) were tested with better-ear PTA. The predictability of the M1 model (blue), with the interaction term duration of HA use2 × PTA, was significantly better than the M0 model (red) without the interaction term. Both M0 and M1 models were significantly better than the null distribution model (gray). The vertical lines indicate the mean value of the predictability.

Discussion

In the current study, brain MRI scans of children with congenital bilateral SNHL were compared to children with typical hearing in order to investigate the impact of auditory stimulation on neuroanatomy of the auditory cortex. The results indicated that early-stage HA use had a significant effect on preserving gray matter in the auditory cortex. However, this beneficial effect appeared to diminish with prolonged HA use, specifically after a duration of >17 months. Furthermore, children with less residual hearing were more affected by duration of HA use in terms of auditory cortex preservation. This study highlights the clinical importance of a parallel approach to pediatric cochlear implantation consisting of fitting HAs after diagnosis in conjunction with early referral for CI evaluation, even when PTA is consistent with profound SNHL. This approach takes advantage of neural preservation to maximize auditory skills and language outcomes. It may be especially beneficial for children not implanted in a timely manner due to many factors including parental acceptance of diagnosis or need for CI, and geographic and/or financial barriers to access pediatric implantation.

The potential of CI electrical stimulation to impact brain anatomy has been demonstrated by animal studies in which electrical stimulation enlarged the area of cortical activation in the primary auditory cortex of congenitally deaf cats (Klinke et al. 1999; Kral et al. 2001, 2002; Kral and Tillein 2006). The effect of HA use on cortical structures for children with congenital SNHL is largely unknown. The nonlinear change of gray matter preservation in the primary auditory cortex as a function of HA use duration is consistent with previous studies that have examined speech and language development in children with hearing loss. For example, earlier HA fitting, rather than longer HA use, was associated with better post-CI outcomes in children with hearing loss (Nicholas and Geers 2006; Geers et al. 2007; Niparko et al. 2010; Percy-Smith et al. 2013). These findings may suggest that a significant delay of implantation, which prolongs HA use for pediatric CI candidates, could have a detrimental effect on their spoken language development. Such a detrimental effect of prolonged HA use may result from the limited auditory input and inadequate comprehension of speech that HAs provide for children with severe to profound SNHL. Children with PTA <90 dB HL who were HA users showed comparable phonetic discrimination abilities as well as speech intelligibility with CI users (Fukuda et al. 2003; Rezaei et al. 2017). However, pediatric HA users with less residual hearing exhibited worse speech perception and speech production abilities compared to those with more residual hearing (Fukuda et al. 2003; Baudonck et al. 2010; Killan et al. 2022). These findings suggested that HA may not provide sufficient benefit to children with more severe hearing loss, aligning with the interaction effect between the duration of HA use and PTA found in our study. Furthermore, Jallu et al. (2019) found that pediatric HA users with profound SNHL did not experience benefit at the end of 18 months of HA use, whereas CI users showed significant improvement in speech perception and language development. Jallu et al.’s findings are consistent with ours regarding the turning point of HA benefit at 17 months.

For parents who choose spoken language as a primary developmental goal for their children who have severe to profound SNHL, early medical and behavioral interventions should be considered at the earliest possible time point to take advantage of the maximum benefit of neuroplasticity. Specifically, pediatric CI candidates can benefit from HA use within 17 months. Hence, it is crucial to have early HA fitting in parallel with CI evaluation to preserve the cortex during the interval period between diagnosis and CI surgery in order to enhance spoken language development. Even when the degree of loss is such that implant candidacy is certain, fitting of HAs enables preservation of cortex for a period of time that may be beneficial when timely implantation is not achieved. Diminished cortical preservation observed in our study after 17 months of HA use, especially for children with less residual hearing, highlights the need for early cochlear implantation. Our study does not support an arbitrary length of hearing aid use prior to CI. Instead, parallel use of HAs until implantation may provide a relative “safety net” to enable better outcomes for children for whom implantation may be delayed.

Consistent with the preliminary pilot study (Yuan et al. 2023), we observed an interaction effect between duration of HA use and residual hearing at the primary auditory cortex rather than the secondary cortex. We speculated that auditory input may have less influence on the secondary auditory cortex because HAs did not provide sufficient comprehension of speech. Therefore, there was less stimulation of the higher-level cortical areas necessary for speech perception. In addition, although the moderation effect of PTA on HG in the primary auditory cortex was present bilaterally as demonstrated by regression analysis (Tables 1 and 2), this effect was dominated by the left hemisphere. This finding may indicate a stronger neuroanatomical connection between bilateral stimulation and the left primary auditory cortex. It is worth noting that the majority of participants in this study had symmetric hearing loss, with an interaural difference <10 dB HL. Therefore, the bilateral PTA measurements could potentially be influenced by the better-ear PTA. Therefore, when we replaced the bilateral PTA with the better-ear PTA in both regression and machine learning models, we obtained the same findings.

Our study suggests a potential causal relationship between early auditory experience and brain structure. There are some limitations in our study. First, the measurements of residual hearing and duration of HA use are retrospective compared to brain scans, and data were not available regarding the amount of daily hearing aid use. Further studies are needed to examine the causal relationship by more strict experimental designs. Another limitation is the absence of baseline measures. The average time between birth and HA fitting was ~7 months, but there was a considerable amount of variability between subjects. Having baseline measures would have provided a more comprehensive understanding of the changes in brain structure over time. Moreover, the longer duration of HA use may be influenced by various factors, such as device type and environmental and family factors (Muñoz and Hill 2015). These factors may also impact the brain structure of children with hearing loss. Future studies should comprehensively examine the effects of these factors on both HA use and brain structure to gain a deeper understanding. Furthermore, other cortical structural features, such as WM volume, WM integrity, and cortical thickness, could be affected by hearing loss (Smith et al. 2011; Huang et al. 2015; Manno et al. 2021). Further studies could examine the impact of HA use and residual hearing on these cortical features, as well as explore their effects on other brain regions. Future studies could also examine how various forms of spoken language training may enhance the benefit of CI and HA use (Ingvalson et al. 2013, 2014; Antoniou and Wong 2015; Wong et al. 2017; Antoniou et al. 2016; Deng et al. 2018; Ingvalson and Wong 2013).

Conclusions

The use of hearing aids positively impacted structural preservation of the primary auditory cortex in pediatric CI candidates with bilateral severe to profound congenital SNHL. This effect was moderated by the degree of SNHL, with greater preservation of the primary auditory cortex observed in children with profound SNHL who had a longer duration of HA use. However, the beneficial effect of HAs on structural preservation was only observed during the early stage of HA use and gradually diminished after 17 months. These findings support the importance of timely fitting of HAs in conjunction with early implantation to take advantage of neural preservation to maximize spoken language development in children with severe to profound SNHL.

Contributor Information

Di Yuan, Brain and Mind Institute, The Chinese University of Hong Kong, 4F, Hui Yeung Shing Building, Shatin, N.T., Hong Kong SAR, China; Department of Psychology, The Chinese University of Hong Kong, 3F, Sino Building Shatin, N.T., Hong Kong SAR, China.

Elizabeth Tournis, Department of Audiology, Ann & Robert H. Lurie Children’s Hospital of Chicago, 225 E. Chicago Ave, Chicago, IL 60611, United States.

Maura E Ryan, Department of Medical Imaging, Ann & Robert H. Lurie Children’s Hospital of Chicago, 225 E. Chicago Ave, Chicago, IL 60611, United States; Department of Medical Imaging, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St,Chicago, IL 60611, United States.

Ching Man Lai, Brain and Mind Institute, The Chinese University of Hong Kong, 4F, Hui Yeung Shing Building, Shatin, N.T., Hong Kong SAR, China.

Xiujuan Geng, Brain and Mind Institute, The Chinese University of Hong Kong, 4F, Hui Yeung Shing Building, Shatin, N.T., Hong Kong SAR, China.

Nancy M Young, Division of Otolaryngology, Ann and Robert H Lurie Children’s Hospital of Chicago, 225 E. Chicago Ave, Chicago, IL 60611, United States; Department of Otolaryngology–Head and Neck Surgery, Feinberg School of Medicine, Northwestern University, 676 N St. Clair St, Chicago, IL 60611, United States; Knowles Hearing Center, Department of Communication Sciences and Disorders, Northwestern University, 2240 Campus Drive, Evanston, IL 60208-3540, United States.

Patrick C M Wong, Brain and Mind Institute, The Chinese University of Hong Kong, 4F, Hui Yeung Shing Building, Shatin, N.T., Hong Kong SAR, China; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, G/F, Leung Kau Kui Building, Shatin, N.T., Hong Kong SAR, China.

Author contributions

Di Yuan (Formal analysis, Methodology, Visualization, Writing—original draft), Elizabeth Tournis (Data curation), Maura Ryan (Data curation, Resources), Ching Man Lai (Data curation), Xiujuan Geng (Methodology), Nancy Young (Funding acquisition, Resources, Supervision, Writing—review & editing), and Patrick Wong (Conceptualization, Funding acquisition, Supervision, Writing—review & editing).

Funding

This work was supported by the National Institutes of Health R21DC016069 and R01DC019387.

Conflict of interest statement: Nancy M. Young does sponsored research with MED-EL Corporation and previously served on the US Surgical Advisory Board of MED-EL Corporation and Advanced Bionics Corporation. Nancy M. Young and Patrick C.M. Wong hold patent 11,607,309.

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