Neural Prediction to Enhance Language Outcomes in Children with Cochlear Implant

神经预测可提高人工耳蜗植入儿童的语言效果

• 批准号: 10366962
• 负责人: PATRICK C M WONG
• 金额: $ 69.89万
• 依托单位: LURIE CHILDREN'S HOSPITAL OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-05 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10366962
• 关键词: Acclimatization; Address; Adopted; Affect; Age; Area; Attention; Auditory; Auditory area; Behavior Therapy; Brain; Brain scan; Chicago; Child; Child Language; Childhood; Clinical; Cochlear Implants; Cochlear implant procedure; Cognitive; Communication; Communication impairment; Data; Dependence; Development; Effectiveness; Enrollment; Future; Goals; Habilitation; Hong Kong; Household; Individual; Inferior; Investigation; Knowledge; Language; Language Development; Lead; Learning; Left; Longitudinal Studies; MRI Scans; Measures; Methods; Modeling; Operative Surgical Procedures; Oral; Outcome; Parents; Pattern; Performance; Prediction of Response to Therapy; Protocols documentation; Randomized Controlled Trials; Readiness; Reporting; Research; Research Personnel; Resources; Sensorineural Hearing Loss; Specificity; Standardization; Subgroup; Testing; Time; analytical method; auditory deprivation; base; bilingualism; brain magnetic resonance imaging; cost; cost effective; follow-up; frontal lobe; hearing impairment; implantation; improved; improved outcome; innovation; language impairment; language outcome; lexical; member; neurodevelopment; neuroimaging; normal hearing; outcome prediction; peer; personalized learning; phonology; precision medicine; prediction algorithm; predictive modeling; programs; relating to nervous system; research clinical testing; success; syntax; theories; tool; translational research program; treatment program

PROJECT SUMMARY/ABSTRACT Although cochlear implantation (CI) is the most effective method for managing severe to profound sensorineural hearing loss, children with CI as a group perform at about 15th percentile of their normal-hearing peers on language measures. Most intriguingly, their language outcomes are highly variable at the individual level, despite implantation at a young age. Using pre-surgical brain magnetic resonance imaging (MRI) scans, done as part of the routine clinical evaluation, as well as AI-enabled analytical methods, our research will construct neural predictive models to forecast individual-level language outcomes in English- and Spanish-learning children up to 4 years after surgery. The clinical utility of these models will also be evaluated by investigating the extent to which the models' prediction is associated with the degree to which a child responds to a program of intensive communication treatment. We hypothesize that during the 4 years immediately after surgery, young children with CI follow three stages of language development: 1) global attention to spoken language as the child acclimatizes to electric auditory input about language, 2) encoding of phonological patterns with sufficient information to develop auditory-based lexical representations, and 3) development of spoken language syntax to communicate orally in longer utterances. We also hypothesize that the integrity of brain networks associated with higher-order cognitive, auditory and syntactic processing differentially contributes to language outcomes across these three stages in monolingual English-learning children with CI (Aim 1). We further hypothesize that these networks are largely invariant for typologically similar languages during the first stage, but that the contribution of the auditory network would be prolonged and require higher-order cognitive networks to an even greater extent to language outcomes for Spanish-English bilingual children with CI (Aim 2). As part of our current R21 project, we have developed a standardized clinical evaluation and follow-up protocol across different CI centers that will facilitate the investigations required to achieve Aims 1 and 2. Aim 3 concerns the interaction between neural prediction of outcomes and behavioral treatment. The main CI center of this project will enroll monolingual English-learning children for an intensive, Parent-Implemented Communication Treatment (PICT) program, which is the only treatment program to date whose effectiveness has been supported by a randomized controlled trial. We will evaluate whether neural prediction of language outcomes is inversely related to the degree of language gains from PICT. Specifically, we hypothesize that the more severe the predicted language impairment based on our neural predictive algorithms, the more the child could benefit from PICT. Our translational research program will advance the field of communication disorders in technological, theoretical and clinical innovations. It will be among the first to demonstrate that a predict-to- prescribe approach to holistically treat hearing loss is feasible, cost-effective and can lead to optimization of language outcomes of all children with CI.

项目总结/摘要 虽然人工耳蜗植入术（CI）是治疗重度至重度感觉神经性聋最有效的方法， 听力损失，CI儿童作为一个群体，在听力正常的同龄人中， 语言措施。最有趣的是，他们的语言成绩在个人层面上是高度可变的， 尽管在很小的时候就被植入了使用术前脑部磁共振成像（MRI）扫描，完成 作为常规临床评价的一部分，以及人工智能支持的分析方法，我们的研究将构建 神经预测模型预测英语和西班牙语学习中的个人水平语言结果 手术后4年内的儿童。这些模型的临床实用性也将通过调查评估 模型的预测与儿童对节目的反应程度相关联的程度 密集的沟通治疗。我们假设在手术后的4年里， CI幼儿的语言发展经历了三个阶段：1）对口语的全面关注， 儿童适应关于语言的电听觉输入，2）语音模式的编码， 足够的信息来发展基于语义的词汇表征，以及3）口语的发展 语言语法，以更长的话语进行口头交流。我们还假设大脑的完整性 与高阶认知，听觉和句法处理相关的网络差异有助于 患有CI的单语英语学习儿童在这三个阶段的语言结果（目标1）。我们 我进一步假设，这些网络在第一个阶段对于类型相似的语言在很大程度上是不变的。 阶段，但听觉网络的贡献将延长，需要更高阶的认知 网络在更大程度上对西班牙语-英语双语儿童的语言结果有影响（目标2）。 作为我们当前R21项目的一部分，我们已经制定了标准化的临床评估和随访方案 在不同的CI中心，这将有助于实现目标1和2所需的调查。目标3 关注神经预测结果和行为治疗之间的相互作用。主要CI中心 这个项目的一部分将招收单语学习英语的儿童参加一个密集的，由家长实施的 沟通治疗（PICT）计划，这是迄今为止唯一的治疗方案，其有效性 已经得到了随机对照试验的支持。我们将评估是否神经预测语言 结果是负相关的程度的语言收益从PICT。具体来说，我们假设， 根据我们的神经预测算法，预测的语言障碍越严重， 我们的转化研究计划将推动沟通障碍领域的发展 技术、理论和临床创新。它将是第一批证明预测- 全面治疗听力损失处方方法是可行的，具有成本效益，并可导致优化 所有CI儿童的语言结果。