Predictive Modeling for Treatment of Upper Airway Obstruction in Young Children

描述（由申请人提供）：上呼吸道异常的婴儿和儿童有缺氧、呼吸功能不全和长期发病的风险。在这些疾病中遇到的多个水平的气道阻塞导致危及生命的空气交换困难，吞咽、生长和语言发育的协调问题。在这些气道疾病中，治疗通常由临床医生的经验和偏好指导，而不是基于标准化的生理或解剖度量。评估和确定这些上呼吸道异常的最佳管理的定量方法将是巨大的好处，改善临床护理和结果。新的研究工具现在可以测量计算流体动力学。这些流体-结构相互作用模型允许通过创建具有气流、壁剪切应力、压力分布和气道壁形状变化的计算测量的气道的虚拟模型来合并动态解剖学与生理测量。该计算模型可以被虚拟地修改以反映医疗干预、手术技术和正常生长，其可以预测气道壁顺应性、新气流模式、压力分布和其他生理变量的变化，以在干预之前产生预期的临床结果。当计算建模工具用于儿科上气道介入规划时，结果的改善是巨大的，特别是在复杂的临床情况下。出于模型开发的目的，我们专注于我们中心遇到的两种非常具体、常见、高风险的异常，即Pierre Robin序列和声门下狭窄。将研究关于上呼吸道生长和发育的规范数据。我们假设，模拟Pierre Robin序列和喉部病变（例如声门下狭窄）儿童上气道机械和空气动力学行为的功能计算模型可用作有效的诊断和治疗计划工具，减少初始治疗失败，避免未来可能不必要的并发症和干预。该提案的具体目标是：（1a）开发儿科上气道的功能计算模型，该模型可用于诊断和预测患有Pierre Robin序列和声门下狭窄的< 10岁儿童的治疗结果;将获得正常气道的数据和建模，以帮助开发描述老化气道的儿科气道解剖图谱;还将开发一个集成的虚拟儿科气道模型（1b）使用解剖和生理测量来验证功能计算模型，该模型评估了10岁以下皮埃尔罗宾序列和声门下狭窄儿童的上气道通畅性和气流限制，以及（2）将计算模型应用于正在评估Pierre Robin序列和声门下狭窄的儿童，并确定模型准确预测各种潜在干预对解剖和生理指标的结果的能力。

DESCRIPTION (provided by applicant): Infants and children with abnormalities of the upper airway are at risk for hypoxia, respiratory insufficiency and long term morbidity. Multiple levels of airway obstruction encountered in these disorders lead to life threatening difficulties in air exchange, problems with coordination of swallowing, growth, and speech development. In these airway disorders, therapy is typically directed by the clinician's experience and preference, rather than on normalized physiologic or anatomic metrics. Quantitative methods of evaluating and determining optimal management of these upper airway anomalies would be of tremendous benefit for improved clinical care and outcomes. New research tools can now measure computational fluid dynamics. These fluid-structure interaction models allow for the merger of dynamic anatomy with physiologic measures by creating a virtual model of the airway with computed measures of airflow, wall shear stress, pressure distribution, and airway wall shape change. This computational model can be virtually modified to reflect medical intervention, surgical techniques, and normal growth, which can predict changes in airway wall compliance, new airflow patterns, pressure distribution, and other physiologic variables to yield expected clinical results prior to intervention. Improvements in outcomes when computational modeling tools are used in pediatric upper airway intervention planning is enormous, particularly in complicated clinical scenarios. For purposes of model development, we focus on two very specific, commonly encountered, high risk anomalies encountered at our center, Pierre Robin sequence and subglottic stenosis. Normative data regarding growth and development of the upper airway will be studied. We hypothesize that a functional computational model that simulates the mechanical and aerodynamic behavior of the upper airway in children with Pierre Robin sequence and laryngeal lesions (e.g. subglottic stenosis) can be used as an effective diagnostic and treatment planning tool, reducing failures of initial treatment and avoiding potentially unnecessary future complications and interventions. Specific aims for this proposal are to: (1a) develop a functional computational model of the pediatric upper airway which can be used for diagnosis and to predict treatment outcomes in children < 10 years of age with Pierre Robin sequence and subglottic stenosis; data and modeling of normal airways will be obtained to help develop a Pediatric Airway Anatomical Atlas describing the aging airway; an integrated Virtual Pediatric Airway Workbench will also be developed (1b) validate the functional computational model using anatomic and physiologic measures that assess airway patency and airflow limitation in the upper airway in children < 10 years of age with Pierre Robin Sequence and subglottic stenosis and (2) apply the computational model to children being evaluated for Pierre Robin Sequence and subglottic stenosis, and determine the ability of the model to accurately predict results of various potential interventions on anatomic and physiologic metrics.