Improving Outcomes in Pediatric Obstructive Sleep Apnea with Computational Fluid Dynamics

利用计算流体动力学改善小儿阻塞性睡眠呼吸暂停的治疗效果

• 批准号: 10543171
• 负责人: Alister Bates
• 金额: $ 24.9万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10543171
• 关键词: 3-Dimensional; Acceleration; Adenoidal structure; Affect; Air; Air Movements; Air Pressure; Airway Resistance; Anatomy; Apnea; Artificial Intelligence; Award; Behavioral; Biomechanics; Biometry; Breathing; Cardiovascular system; Child; Childhood; Chronic; Clinical; Cognitive; Complement; Computer Models; Continuous Positive Airway Pressure; Data; Developmental Delay Disorders; Disease; Environment; Event; Face; Failure; Gases; Geometry; Goals; Growth; Heart Abnormalities; Hour; Image; Impairment; In Vitro; Individual; Inhalation; Ionizing radiation; Knowledge; Liquid substance; Lung; Machine Learning; Magnetic Resonance Imaging; Maps; Measurement; Measures; Medicine; Mentors; Metabolic; Methods; Modality; Modeling; Morbidity - disease rate; Motion; Noble Gases; Obstructive Sleep Apnea; Operative Surgical Procedures; Outcome; Patients; Pattern; Pediatric Hospitals; Phase; Physiology; Polysomnography; Postoperative Period; Pulmonology; Quality of life; Radiology Specialty; Research; Research Personnel; Resistance; Resolution; Respiratory Airflow; Shapes; Sleep; Sleep Apnea Syndromes; Sleep disturbances; Soft Palate; Structure; Surgeon; Techniques; Testing; Time; Tongue; Tonsil; Validation; Wing; Xenon; airway obstruction; candidate validation; career; career development; computerized tools; design; experience; imaging Segmentation; improved; improved outcome; in vivo; indexing; individual patient; neuromuscular; non-compliance; novel; pediatric patients; positive airway pressure; precision medicine; predictive modeling; predictive tools; pressure; reduce symptoms; respiratory; respiratory surgery; simulation; skills; soft tissue; success; surgery outcome; tool; virtual; virtual model; virtual surgery

This project aims to create a validated computational tool to predict surgical outcomes for pediatric patients with obstructive sleep apnea (OSA). OSA is a common condition, affecting 2.2 million children in the USA alone. It is characterized as upper airway obstruction during sleep, which causes disrupted sleep and leads to developmental delay, cardiovascular complications and impaired growth. The first line of treatment for children with OSA is to remove their tonsils and adenoids; however, these surgeries do not always cure the patient. Another treatment, continuous positive airway pressure (CPAP) is only tolerated by 50% of children. Therefore, many children undergo surgical interventions aimed at soft tissue structures surrounding the airway, such as tonsils, tongue, and soft palate, and/or the bony structures of the face. However, the success rates of these surgeries, measured as a reduction in the obstructive apnea-hypopnea index (obstructive events per hour of sleep), is surprisingly low. Therefore, there is a clear need for a tool to improve the efficacy of these surgeries and predict which of the various surgical options is going to benefit each individual patient most effectively. Computational fluid dynamics (CFD) simulations of respiratory airflow in the upper airways can provide this predictive tool, allowing the effects of various surgical options to be compared virtually and the option most likely to improve the patient’s condition to be chosen. Previous CFD simulations have been unable to provide information about OSA as they were based on rigid geometries, or did not include neuromuscular motion, a key component in OSA. This project uses real-time magnetic resonance imaging (MRI) to provide the anatomy and motion of the airway to the CFD simulation, meaning that the exact in vivo motion is modeled for the first time. Furthermore, since the modeling is based on MRI, a modality which does not use ionizing radiation, it is suitable for longitudinal assessment of patients before and after surgical procedures. In vivo validation of these models will be achieved for the first time through comparison of CFD-based airflow velocity fields with those generated by phase-contrast MRI of inhaled hyperpolarized 129Xe gas. Cincinnati Children’s Hospital is a world leader in the fields of pediatric pulmonary and sleep medicine and radiology, and is the ideal environment to conduct the proposed research and for the PI to develop the essential skills to have a successful career as an independent investigator. The PI has identified primary mentors in both technical and clinical fields, and a further mentoring team to assist with specific aspects of this project. Between them, they have experience in MRI, sleep medicine, pulmonary medicine, CFD modeling, airway surgery, radiology, and biostatistics, as well as career development through this award mechanism. Their knowledge strengthens and complements the PI’s background in computational modeling of the airways and airflow within. The successful award of this project would afford the PI the opportunity to establish himself as a world leader in airway biomechanics and to improve the quality of life for pediatric patients with OSA.

该项目旨在创建一个经过验证的计算工具，以预测儿科患者的手术结果， 阻塞性睡眠呼吸暂停（OSA）。OSA是一种常见的疾病，仅在美国就影响了220万儿童。是 其特征在于睡眠期间的上呼吸道阻塞，其导致睡眠中断并导致 发育迟缓、心血管并发症和生长受损。儿童治疗的第一线 治疗阻塞性睡眠呼吸暂停综合征的方法是切除扁桃体和腺样体;然而，这些手术并不总能治愈病人。 另一种治疗方法，持续气道正压通气（CPAP），只有50%的儿童能够耐受。因此，我们认为， 许多儿童经历针对气道周围的软组织结构的外科手术， 扁桃体、舌头和软腭，和/或面部的骨性结构。然而，这些成功率 手术，测量为阻塞性呼吸暂停低通气指数（每小时阻塞事件， 睡眠），是令人惊讶的低。因此，显然需要一种工具来提高这些手术的疗效 并预测各种手术选择中的哪一种将最有效地使每个患者受益。 上气道中呼吸气流的计算流体动力学（CFD）模拟可以提供这一点 预测工具，允许虚拟比较各种手术选项的效果， 以改善患者的状况。以前的CFD模拟无法提供 关于OSA的信息，因为它们基于刚性几何形状，或者不包括神经肌肉运动，这是一个关键 在OSA中。该项目使用实时磁共振成像（MRI）提供解剖结构， 将气道运动与CFD模拟相结合，这意味着首次对精确的体内运动进行建模。 此外，由于建模是基于MRI（一种不使用电离辐射的模态），因此它是合适的 用于手术前后患者的纵向评估。这些模型的体内验证 将首次通过比较基于CFD的气流速度场与生成的气流速度场， 通过吸入超极化129氪气体的相衬MRI。 辛辛那提儿童医院是小儿肺部和睡眠医学领域的世界领先者， 放射学，是理想的环境进行拟议的研究和PI发展的基本 作为一名独立调查员，拥有成功的职业生涯。PI已经确定了这两个领域的主要导师 技术和临床领域，以及进一步的指导团队，以协助该项目的具体方面。之间 他们在MRI、睡眠医学、肺部医学、CFD建模、气道手术方面都有经验， 放射学和生物统计学，以及通过这一奖励机制的职业发展。他们的知识 加强和补充PI在气道和气流计算建模方面的背景。 该项目的成功授予将使PI有机会确立自己作为世界领导者的地位， 气道生物力学和改善儿童OSA患者的生活质量。