Neural activity of the auditory cortex predicts speech recognition of patients with asymmetric hearing loss after cochlear implantation

Patients with asymmetric hearing loss show an asymmetry of glucose metabolism of the primary auditory cortex (PAC). We investigated whether this asymmetry could serve as an objective predictor for speech recognition with CI. Nine patients underwent (18)FDG PET prior to CI surgery. Average normalized (18)FDG uptake of 25% of voxels with highest uptake was calculated for the PAC employing a probabilistic atlas and cerebellar cortex as reference. Differences in glucose metabolism of the PAC were assessed by an asymmetry index (AI-PAC). We tested the correlation between outcome of CI surgery (6 months post implantation), AI-PAC and clinical predictors. Pre-operative AI-PAC showed a positive correlation with speech recognition with CI (significant for sentences and numbers; trend for monosyllabic words). With a pre-operative AI-PAC >= 4.2%, patients reached good CI outcome in sentence recognition of 59-90% and number recognition of 90-100% and less favorable CI outcome in monosyllabic word recognition of 25-45%. Age at symptom onset was significantly associated with all measures of speech recognition, while deafness duration was only associated with sentence recognition. AI-PAC allows for a reliable and quantitative pre-operative prediction of early improvement in speech recognition after CI. (18)FDG PET may be a valuable addition to the objective pre-operative assessment of CI candidates. Further studies in larger cohorts and with longer follow-up times are needed.

Automated summary

This study investigates whether the asymmetry of glucose metabolism in the primary auditory cortex can serve as an objective predictor for speech recognition after cochlear implantation (CI) surgery. The results show a positive correlation between pre-operative asymmetry index of glucose metabolism in the primary auditory cortex and speech recognition outcomes, indicating that pre-operative assessment using this index can predict the improvement in speech recognition after CI.