Dynamic Computational Modeling of Obstructive Sleep Apnea in Down Syndrome

唐氏综合症阻塞性睡眠呼吸暂停的动态计算模型

• 批准号: 8013356
• 负责人: Raouf S. Amin
• 金额: $ 96.28万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-17 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8013356
• 关键词: 3-Dimensional; Accounting; Adenoidectomy; Adult; Airway Resistance; Anatomy; Apnea; Child; Collaborations; Computer Simulation; Congenital chromosomal disease; Continuous Positive Airway Pressure; Data; Development; Diagnostic; Down Syndrome; Effectiveness; Elasticity; Functional disorder; Goals; Health; Hypercapnia; Hypoxemia; Image; Incidence; Infant; Interdisciplinary Study; Knowledge; Magnetic Resonance Imaging; Measurement; Measures; Medical; Methodology; Modality; Modeling; Nature; Nose; Obstructive Sleep Apnea; Operative Surgical Procedures; Outcome; Output; Patients; Population; Procedures; Public Health; Publishing; Refractory; Research; Sleep; Sleep Apnea Syndromes; Structure; Surgical Management; Techniques; Testing; Tissues; Tonsillectomy; United States; Work; abstracting; flexibility; improved; indexing; innovation; member; novel; pharyngeal critical pressure; predictive modeling; pressure; public health relevance; rapid growth; success; tool

DESCRIPTION (provided by applicant): Obstructive sleep apnea (OSA) occurs in 50-100% of patients with Down syndrome and can significantly cause and exacerbate medical problems in these patients. Current surgical management in these children is imperfect. There are variable surgical success rates for both first line surgery [palatine tonsillectomy and adenoidectomy (T&A)] as well as secondary surgeries performed if and when T&A fails. There is a critical need for a diagnostic modality that takes into account airway anatomy, tissue compliance, and collapsibility to be able to predict surgical outcome and improve surgical planning in these patients. Our central hypothesis is that upper airway flow-structure interaction (FSI) modeling using three-dimensional (3-D) computational simulations from dynamic MRI data can be used to predict surgical outcome for children with Down syndrome who have OSA despite previous T&A. The long-term goal is to improve surgical outcome of children with Down syndrome and OSA by creating an accurate FSI predictive model. Such a diagnostic tool would help tailor surgical procedures to be more effective as well as identify and avoid unnecessary (or unhelpful) surgical procedures. These created models then can also be adjusted and applied to other populations with OSA. Our specific aims include: 1) In children with Down syndrome with persistent OSA despite previous T&A, collect data characterizing upper airway anatomy, tissue compliance, and collapsibility; 2) Generate and validate individualized dynamic FSI models for each child in specific aim 1; and 3) Using the validated dynamic computational models, predict the success of surgical treatment on children with Down syndrome who have persistent OSA despite previous T&A. This work is innovative as it uses dynamic rather than static MR imaging data and applies a unique computational model that accurately captures the unsteadiness of the flow and accounts for the interaction between the airflow and the surrounding airway flexible structures. PUBLIC HEALTH RELEVANCE: The proposed research is relevant to public health because it seeks to create a diagnostic tool that will better predict the need and effectiveness of specific surgical procedures in the treatment of obstructive sleep apnea (OSA) in children with Down syndrome. Such a diagnostic tool would help tailor surgical procedures to be more effective as well as identify and avoid unnecessary (or unhelpful) surgical procedures. The creation of this diagnostic tool is important in children with Down syndrome because of the very high rate and refractory nature of OSA in these children but also the creation of the tool may also be applied and benefit other populations of children and adults with OSA, which constitutes a major health problem in the USA. (End of Abstract)

描述（由申请人提供）：50-100％的唐氏综合症患者发生阻塞性睡眠呼吸呼吸暂停（OSA），这些患者会大大引起并加剧医疗问题。这些儿童目前的手术管理是不完美的。第一线手术[palatine扁桃体切除术和腺样体切除术（T＆A）]以及T＆A失败时进行的次级手术都有可变的手术成功率。考虑到气道解剖结构，组织合规性和可折叠性以预测手术结局并改善这些患者的手术计划的临时方式迫切需要诊断方式。我们的中心假设是，使用动态MRI数据的三维（3-D）计算模拟的上呼吸道流动结构相互作用（FSI）建模可用于预测尽管先前T＆A的唐氏综合症儿童的OSA儿童的手术结果。长期目标是通过创建准确的FSI预测模型来改善唐氏综合症和OSA儿童的手术结果。这样的诊断工具将有助于量身定制外科手术程序，并识别和避免不必要的（或无助）手术程序。然后，这些创建的模型也可以通过OSA进行调整并应用于其他人群。我们的具体目的包括：1）尽管先前的T＆A，但在患有持久OSA的唐氏综合症的儿童中，收集了表征上呼吸道解剖学，组织合规性和可折叠性的数据； 2）在特定目标1中为每个孩子生成并验证每个孩子的个性化动态FSI模型； 3）使用经过验证的动态计算模型，可以预测尽管先前的T＆A，但对唐氏综合症的儿童进行了手术治疗的成功。这项工作具有创新性，因为它使用动态而不是静态MR成像数据，并应用了独特的计算模型，该模型可以准确地捕获流动的不稳定，并解释了气流与周围气道柔性结构之间的相互作用。公共卫生相关性：拟议的研究与公共卫生有关，因为它试图创建一种诊断工具，以更好地预测特定手术程序在治疗唐氏综合症儿童阻塞性睡眠呼吸暂停（OSA）方面的需求和有效性。这样的诊断工具将有助于量身定制外科手术程序，并识别和避免不必要的（或无助）手术程序。由于这些儿童中OSA的速度和难治性非常高，而且该工具的创建也可以应用于唐氏综合症的儿童，在唐氏综合症的儿童中的创建很重要，也可以应用于OSA的其他儿童和成人人群，这构成了美国的主要健康问题。 （抽象的结尾）