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% 的唐氏综合症患者会出现阻塞性睡眠呼吸暂停 (OSA)，并且会严重导致和加剧这些患者的医疗问题。目前这些儿童的手术治疗并不完善。一线手术[腭扁桃体切除术和腺样体切除术 (T&A)] 以及 T&A 失败时进行的二次手术的手术成功率各不相同。迫切需要一种考虑气道解剖结构、组织顺应性和塌陷性的诊断方式，以便能够预测这些患者的手术结果并改进手术计划。我们的中心假设是，使用动态 MRI 数据的三维 (3-D) 计算模拟进行上气道流量-结构相互作用 (FSI) 建模，可用于预测尽管之前接受过 T&A 但仍患有 OSA 的唐氏综合症儿童的手术结果。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使外科手术更加有效，并识别和避免不必要（或无用）的外科手术。这些创建的模型也可以进行调整并应用于其他患有 OSA 的人群。我们的具体目标包括： 1) 对于患有唐氏综合症的儿童，尽管之前进行过 T&A，但仍患有持续性 OSA，收集表征上呼吸道解剖结构、组织顺应性和塌陷性的数据； 2) 为每个孩子生成并验证特定目标 1 的个性化动态 FSI 模型； 3) 使用经过验证的动态计算模型，预测尽管之前接受过 T&A，但仍患有持续性 OSA 的唐氏综合症儿童的手术治疗是否成功。这项工作具有创新性，因为它使用动态而不是静态的 MR 成像数据，并应用独特的计算模型，可以准确捕获气流的不稳定性并解释气流与周围气道柔性结构之间的相互作用。公共健康相关性：拟议的研究与公共健康相关，因为它旨在创建一种诊断工具，更好地预测治疗唐氏综合症儿童阻塞性睡眠呼吸暂停（OSA）的特定手术程序的需求和有效性。这样的诊断工具将有助于使外科手术更加有效，并识别和避免不必要（或无用）的外科手术。该诊断工具的创建对于患有唐氏综合症的儿童非常重要，因为这些儿童中 OSA 的发病率非常高且难治，而且该工具的创建也可以应用并造福于患有 OSA 的其他儿童和成人群体，这构成美国的一个主要健康问题。 （摘要完）