White matter microstructural biomarkers predict cochlear implant outcomes in adults with postlingual deafness

Although cochlear implantation (CI) has been used for decades to restore hearing in sensorineural deafness, accurately predicting individual outcomes remains challenging-particularly in adults with postlingual deafness, a population that has been relatively understudied. In our previous work, we showed that speech comprehension after 6 months of CI use is better predicted when preoperative grey matter volume and cortical thickness in regions supporting language and cognition are considered alongside preoperative residual hearing and audiovisual abilities. In the present study, we investigated whether preoperative diffusion-weighted imaging (DWI) metrics in subcortical white matter (WM) could account for individual variability in cochlear implant adaptation and enhance predictive accuracy. Thereto, we collected preoperative DWI and speech performance under auditory-only and audiovisual conditions in 65 adults with postlingual bilateral deafness. Improvement in speech comprehension with CI was evaluated at 6 and 12 months post-implantation. A whole-brain analysis revealed significant positive correlations between preoperative fractional anisotropy (FA) within a cluster in the left arcuate fasciculus and speech perception at 6 months in both auditory-only and audiovisual conditions. Incorporating FA from the arcuate fasciculus cluster into the multiple linear regression model developed in our previous study significantly improved prediction accuracy for CI outcomes at 6 months. We also identified FA clusters in the right inferior fronto-occipital fasciculus and the corpus callosum that showed positive relationships with audiovisual comprehension and mid-term cochlear implant performance. In contrast, mean FA values averaged across entire tracts did not show similarly strong associations with speech perception, as shown after tract reconstruction. Notably, sex modulated the relationship between age and FA values across multiple white matter clusters. These findings underscore the role of localized WM microstructural properties in shaping speech adaptation after CI. Identifying WM-based predictors of CI performance may aid clinicians in forecasting individual outcomes and tailoring rehabilitation strategies, particularly for patients at risk of delayed or limited benefit. Further research is needed to clarify the origins of regional FA variability.