The value of synthetic MRI in detecting the brain changes and hearing impairment of children with sensorineural hearing loss

IntroductionSensorineural 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.MethodsThe study encompassed both children diagnosed with SNHL and a control group of children with normal hearing {1.5-month-olds (n = 52) and 3-month-olds (n = 78)}. Participants were categorized based on their auditory brainstem response (ABR) threshold, delineated into normal, mild, moderate, and severe subgroups.Clinical parameters were included and assessed the correlation with SNHL. Quantitative analysis of brain morphology was conducted using SyMRI scans, yielding data on brain segmentation and relaxation time.Through both univariate and multivariate analyses, independent factors predictive of SNHL were identified. The efficacy of the prediction model was evaluated using receiver operating characteristic (ROC) curves, with visualization facilitated through the utilization of a nomogram. It's important to note that due to the constraints of our research, we worked with a relatively small sample size.ResultsNeonatal 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.ConclusionThe 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

Predicting neurodevelopmental outcomes in extremely preterm neonates with low-grade germinal matrix-intraventricular hemorrhage using synthetic MRI

ObjectivesThis study aims to assess the predictive capability of synthetic MRI in assessing neurodevelopmental outcomes for extremely preterm neonates with low-grade Germinal Matrix-Intraventricular Hemorrhage (GMH-IVH). The study also investigates the potential enhancement of predictive performance by combining relaxation times from different brain regions.Materials and methodsIn this prospective study, 80 extremely preterm neonates with GMH-IVH underwent synthetic MRI around 38 weeks, between January 2020 and June 2022. Neurodevelopmental assessments at 18 months of corrected age categorized the infants into two groups: those without disability (n = 40) and those with disability (n = 40), with cognitive and motor outcome scores recorded. T1, T2 relaxation times, and Proton Density (PD) values were measured in different brain regions. Logistic regression analysis was utilized to correlate MRI values with neurodevelopmental outcome scores. Synthetic MRI metrics linked to disability were identified, and combined models with independent predictors were established. The predictability of synthetic MRI metrics in different brain regions and their combinations were evaluated and compared with internal validation using bootstrap resampling.ResultsElevated T1 and T2 relaxation times in the frontal white matter (FWM) and caudate were significantly associated with disability (p < 0.05). The T1-FWM, T1-Caudate, T2-FWM, and T2-Caudate models exhibited overall predictive performance with AUC values of 0.751, 0.695, 0.856, and 0.872, respectively. Combining these models into T1-FWM + T1-Caudate + T2-FWM + T2-Caudate resulted in an improved AUC of 0.955, surpassing individual models (p < 0.05). Bootstrap resampling confirmed the validity of the models.ConclusionSynthetic MRI proves effective in early predicting adverse outcomes in extremely preterm infants with GMH-IVH. The combination of T1-FWM + T1-Caudate + T2-FWM + T2-Caudate further enhances predictive accuracy, offering valuable insights for early intervention strategies

Adsorption Characteristics of Dodecamethylcyclohexasiloxane and Dodecamethylpentasiloxane from Landfill Leachate by Municipal Solid Waste under the Landfill Circumstance

The release of siloxane from landfill leachate has attracted wide attention. In this study, dodecamethylcyclohexasiloxane (D6) and dodecamethylpentasiloxane (L5) were chosen as the target pollutants to investigate the adsorption characteristics of cyclosiloxane and linear siloxane on municipal solid waste (MSW) under the landfill circumstance. The adsorption behavior could be well described by the Langmuir–Freundlich model, with a maximum adsorption capacity of 0.677 μg g−1 and 15.864 μg g−1 for L5 and D6, respectively. It seems that D6 has a stronger affinity to MSW compared with L5. The maximum adsorption was observed when the pH was 5.0 and 5.5 for D6 and L5. The optical temperature was 30 °C. The organic acid and inorganic ions in the leachate could restrict the adsorption to a low level. The results suggested that the adsorption of siloxane on MSW could be limited at the methanogenic and mature stages, which may promote the distribution of siloxane in the leachate. The results could help to understand the release behavior of siloxane from landfill leachate during the running of a landfill