RESUMEN
Background: Patients with age-related hearing loss (ARHL) often struggle with tracking and locating sound sources, but the neural signature associated with these impairments remains unclear. Materials and methods: Using a passive listening task with stimuli from five different horizontal directions in functional magnetic resonance imaging, we defined functional regions of interest (ROIs) of the auditory "where" pathway based on the data of previous literatures and young normal hearing listeners (n = 20). Then, we investigated associations of the demographic, cognitive, and behavioral features of sound localization with task-based activation and connectivity of the ROIs in ARHL patients (n = 22). Results: We found that the increased high-level region activation, such as the premotor cortex and inferior parietal lobule, was associated with increased localization accuracy and cognitive function. Moreover, increased connectivity between the left planum temporale and left superior frontal gyrus was associated with increased localization accuracy in ARHL. Increased connectivity between right primary auditory cortex and right middle temporal gyrus, right premotor cortex and left anterior cingulate cortex, and right planum temporale and left lingual gyrus in ARHL was associated with decreased localization accuracy. Among the ARHL patients, the task-dependent brain activation and connectivity of certain ROIs were associated with education, hearing loss duration, and cognitive function. Conclusion: Consistent with the sensory deprivation hypothesis, in ARHL, sound source identification, which requires advanced processing in the high-level cortex, is impaired, whereas the right-left discrimination, which relies on the primary sensory cortex, is compensated with a tendency to recruit more resources concerning cognition and attention to the auditory sensory cortex. Overall, this study expanded our understanding of the neural mechanisms contributing to sound localization deficits associated with ARHL and may serve as a potential imaging biomarker for investigating and predicting anomalous sound localization.
RESUMEN
Background: Postoperative pain is the most common complication after tonsillectomy. We aimed to explore new parameters related to post-tonsillectomy pain, as well as to construct and validate a model for the preoperative evaluation of patients' risk for postoperative pain. Methods: Data collected from patients who underwent tonsillectomy by the same surgeon at Beijing Chaoyang Hospital from January 2019 to May 2022 were analyzed. Preoperative tonsil images from all patients were taken, and the ratios of the distance between the upper pole of the tonsil and the base of the uvula (L1 for the left side and R1 for the right side) to the width of the uvula (U1) or the length of the uvula (U2) were measured. The following six ratios were calculated: L1/U1, R1/U1, LR1/U1 (the add of L1 and R1, and then divide U1), L1/U2, R1/U2, LR1/U2 (the add of L1 and R1, and then divide U2). The post-tonsillectomy pain was recorded. In addition, machine learning (ML) algorithm and feature importance analysis were used to evaluate the value of the parameters. Results: A total of 100 patients were involved and divided into the training set (60%) and the validation set (40%). All six parameters are negatively correlated with post-tonsillectomy pain. The accuracy, sensitivity, and specificity of the model were 75.0%, 72.7%, and 77.8%, respectively. LR1/U1 and LR1/U2 are the most valuable parameters to evaluate post-tonsillectomy pain. Conclusions: We have discovered new parameters that can be measured using preoperative tonsil images to evaluate post-tonsillectomy pain. ML models based on these parameters could predict whether these patients will have intolerable pain after tonsillectomy and manage it promptly.