ArticleFrontiers in neuroscience2024
The value of synthetic MRI in detecting the brain changes and hearing impairment of children with sensorineural hearing loss.
Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Long-term follow-up of autologous nasal epithelial stem cell transplantation for congenital olfactory disorders in children.World journal of stem cells · 2025Article
- Technical development and In Silico implementation of SyntheticMR in head and neck adaptive radiation therapy: A prospective R-IDEAL stage 0/1 technology development report.Journal of applied clinical medical physics · 2025Article
- Optimizing prostate biopsy decision-making for patients with Prostate Imaging-Reporting and Data System (PI-RADS) ≥3 lesions: novel magnetic resonance imaging (MRI)-based nomograms.Quantitative imaging in medicine and surgery · 2024Article
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13 authors.
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Abstract
Introduction: Sensorineural hearing loss (SNHL) can arise from a diverse range of congenital and acquired factors. Detecting it early is pivotal for nurturing speech, language, and cognitive development in children with SNHL. In our study, we utilized synthetic magnetic resonance imaging (SyMRI) to assess alterations in both gray and white matter within the brains of children affected by SNHL. Methods: The study encompassed both children diagnosed with SNHL and a control group of children with normal hearing {1.5-month-olds ( Results: Neonatal hyperbilirubinemia (NH) and children with inner ear malformation (IEM) were associated with the onset of SNHL both at 1.5 and 3-month groups. At 3-month group, the moderate and severe subgroups exhibited elevated quantitative T1 values in the inferior colliculus (IC), lateral lemniscus (LL), and middle cerebellar peduncle (MCP) compared to the normal group. Additionally, WMV, WMF, MYF, and MYV were significantly reduced relative to the normal group. Additionally, SNHL-children with IEM had high T1 values in IC, and LL and reduced WMV, WMF, MYV and MYF values as compared with SNHL-children without IEM at 3-month group. LL-T1 and WMF were independent risk factors associated with SNHL. Consequently, a prediction model was devised based on LL-T1 and WMF. ROC for training set, validation set and external set were 0.865, 0.806, and 0.736, respectively. Conclusion: The integration of T1 quantitative values and brain volume segmentation offers a valuable tool for tracking brain development in children affected by SNHL and assessing the progression of the condition's severity.
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