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率的风险。在这些疾病中遇到的多个水平的呼吸道阻塞会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。在这些呼吸道疾病中，治疗通常是由临床医生的经验和偏好指导的，而不是根据标准化的生理或解剖指标进行的。评估和确定这些上呼吸道异常的最佳处理的定量方法将对改善临床护理和预后有极大的好处。新的研究工具现在可以测量计算流体力学。这些流体-结构交互模型允许将动态解剖与生理测量相结合，方法是通过计算气流、壁面剪应力、压力分布和气道壁形状变化的测量来创建气道的虚拟模型。这一计算模型可以进行虚拟修改，以反映医疗干预、手术技术和正常生长，它可以预测气道壁顺应性、新的气流模式、压力分布和其他生理变量的变化，从而在干预之前产生预期的临床结果。当计算建模工具被用于儿科上呼吸道介入计划时，结果的改善是巨大的，特别是在复杂的临床场景中。为了模型开发的目的，我们将重点放在我们中心遇到的两个非常具体的、常见的、高风险的异常，Pierre Robin序列和声门下狭窄。将研究有关上呼吸道生长发育的标准数据。我们假设，模拟Pierre Robin序列和喉部病变(例如声门下狭窄)儿童上呼吸道机械和空气动力学行为的功能计算模型可以用作有效的诊断和治疗计划工具，减少初始治疗的失败，并避免潜在的不必要的未来并发症和干预。这项建议的具体目标是：(1a)开发一个儿科上呼吸道的功能计算模型，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呼吸道解剖图谱；还将开发一个集成的虚拟儿科呼吸道工作台(1b)使用解剖学和生理学措施验证该功能计算模型，以评估儿童和lt的上呼吸道的呼吸道通畅性和气流限制；(2)将计算模型应用于接受Pierre Robin序列和声门下狭窄评估的儿童，并确定该模型准确预测各种潜在的解剖学和生理学指标干预的结果的能力。

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.