Model-based Phenotyping of OSAS in Pediatric Obesity using Dynamic MR Imaging

使用动态 MR 成像对儿童肥胖中的 OSAS 进行基于模型的表型分析

• 批准号: 8013455
• 负责人: MICHAEL C K KHOO
• 金额: $ 87.66万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 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/8013455
• 关键词: Acoustics; Affect; Airway Resistance; Anatomy; Apnea; Arousal; Arts; Behavior; Breathing; Categories; Characteristics; Child; Childhood; Clinical; Computer Simulation; Data; Databases; Dependence; Disease; Exhibits; Frequencies; Gases; Guidelines; High Prevalence; Hypercapnia; Hypercapnic respiratory failure; Hypertrophy; Hypoxemia; Image; Individual; Knowledge; Lead; Magnetic Resonance Imaging; Measurement; Mediator of activation protein; Methodology; Metric; Modeling; Noise; Obesity; Obstruction; Obstructive Sleep Apnea; Overweight; Patients; Pattern; Periodicity; Phenotype; Physiological; Platelet Factor 4; Play; Polysomnography; Population; Prevalence; Recurrence; Reporting; Resolution; Role; Simulate; Sleep; Sleep Apnea Syndromes; Syndrome; Testing; Therapeutic; Time; Variant; Wakefulness; abstracting; airway obstruction; base; falls; improved; indexing; novel; obesity in children; public health relevance; respiratory; simulation

DESCRIPTION (provided by applicant): Obstructive sleep apnea syndrome (OSAS) and other forms of sleep-related breathing disorders (SRBD) occur at high prevalence rates in obese children. The pool of subjects with obesity- related SRDB display a large variation of polysomnographic and clinical characteristics. These may be classified broadly into the following 4 phenotypic categories: (a) primary snorers with no abnormalities of gas exchange, respiratory pattern or sleep disruption; (b) obstructive hypoventilation with hypercapnia or hypoxemia with near-normal respiratory or sleep patterns; (c) high arousal frequency without prominent gas exchange abnormality, obstructive apneas or hypopneas (includes upper airway resistance syndrome); (d) traditional OSAS with recurrent episodes of obstructive hypopnea and apnea. We hypothesize that this diversity in phenotypic behavior results from the existence of different underlying physiological mechanisms, and that a quantitative dynamic model would allow us to better delineate the mechanistic differences. To test this hypothesis, we propose to: (1) establish a database of information pertinent to upper airway and ventilatory control dynamics, derived from dynamic magnetic resonance imaging (MRI) and noninvasive physiological measurements obtained during wakefulness and sleep; (2) estimate from these data the key parameters of a closed-loop minimal computational model of SRBD and determine how these parameters differ across phenotypic categories; and (3) extend the existing computational model of SRBD using the novel information about upper airway dynamics derived from dynamic MRI. The extended computational model will be used to simulate ventilatory control dynamics during sleep, and metrics derived from these simulations will be compared against the corresponding indices derived from the observed characteristics of SRBD in the 4 phenotypic categories. In parallel, technological improvements will be made to the existing real-time MRI methodology in order to increase spatio-temporal resolution and decrease acoustic noise during imaging. The knowledge derived from this study may lead to a better understanding of the mechanisms through which the different phenotypes of SRBD occur in obese children, and could be useful in providing better guidelines for customizing therapeutic strategies to individual patients. PUBLIC HEALTH RELEVANCE: The prevalence of overweight and obesity in children has increased dramatically over the past two decades. A significant fraction of these obese children also have sleep-related breathing disorders. The proposed study combines computational modeling and state-of-the-art dynamic magnetic resonance imaging (MRI) of the upper airway and with physiological measurements to investigate why this subject population exhibits large variations in sleep and clinical characteristics. The knowledge derived from this study may provide improved guidelines for customizing therapeutic strategies to individual patients. As well, the technological improvements in real-time MRI methodology developed in this project will help to significantly advance dynamic upper airway imaging in general. (End of Abstract)

描述（由申请人提供）：肥胖儿童的阻塞性睡眠呼吸暂停综合征（OSA）和其他形式的与睡眠有关的呼吸障碍（SRBD）以高患病率出现。与肥胖相关的SRDB的受试者库表现出很大的多症状学和临床特征。这些可能会大致分为以下四个表型类别：（a）没有气体交换异常，呼吸模式或睡眠破坏的主要打孔器； （b）用高碳酸盐或低氧血症的阻塞性不足，呼吸或睡眠模式； （c）高唤醒频率，没有明显的气体交换异常，阻塞性呼吸暂停或呼吸症（包括上气道电阻综合征）； （d）传统的OSA，具有阻塞性呼吸症和呼吸暂停的复发发作。我们假设表型行为中的这种多样性是由于存在不同的潜在生理机制而产生的，并且定量动态模型将使我们能够更好地描述机械差异。为了检验这一假设，我们建议：（1）建立一个与上呼吸道和通气控制动力学有关的信息数据库，该数据库源自动态磁共振成像（MRI）和在清醒和睡眠期间获得的非侵入性生理测量； （2）从这些数据中估算了SRBD的闭环最小计算模型的关键参数，并确定这些参数在表型类别之间的不同之处； （3）使用有关动态MRI的上呼吸道动力学的新信息扩展了SRBD的现有计算模型。扩展的计算模型将用于模拟睡眠过程中的通气控制动力学，并将从这些模拟得出的指标与从4个表型类别中SRBD的观察到的特征得出的相应指数进行比较。同时，将对现有的实时MRI方法进行技术改进，以增加时空分辨率并减少成像过程中的声噪声。从这项研究中得出的知识可能会更好地理解SRBD在肥胖儿童中发生不同表型的机制，并且可以为提供更好的指导方针，以便为个体患者定制治疗策略。公共卫生相关性：在过去的二十年中，儿童超重和肥胖的患病率急剧增加。这些肥胖儿童中很大一部分也患有与睡眠有关的呼吸障碍。拟议的研究结合了上呼吸道的计算建模和最新动态磁共振成像（MRI），并结合了生理测量，以研究为什么该受试者在睡眠和临床特征上表现出很大的变化。从这项研究中得出的知识可能会为各个患者定制治疗策略提供改进的准则。同样，该项目中开发的实时MRI方法的技术改进将有助于一般可以大大推动动态的上呼吸道成像。 （抽象的结尾）