Virtual growing child 5-dimensional functional models for treating respiratory anomalies
用于治疗呼吸异常的虚拟成长儿童 5 维功能模型
基本信息
- 批准号:10532776
- 负责人:
- 金额:$ 74.26万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-02-01 至 2024-11-30
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAddressAdultAftercareAgeAlgorithmsAnatomic ModelsAnatomyApplications GrantsArchitectureBirthChestChest imagingChildChildhoodClinicalClinical DataComplexDataDatabasesDeformityDevelopmentDimensionsDiseaseFaceGenderGoalsGrowthHealth Care CostsImageIncidenceJointsLifeLungMRI ScansMagnetic Resonance ImagingMeasurementMethodologyMethodsModelingNamesNormalcyOperative Surgical ProceduresOrthopedic ProceduresOutcomeOutcome MeasurePatient SelectionPatientsPopulationPopulation GroupPostoperative PeriodProceduresPulmonary function testsRegistriesRespirationRodScanningSpecialistSpecificitySpinalSpinal FusionSpirometryStructureSyndromeTechniquesTechnologyTestingThoracic DiseasesTidal VolumeTimeTranslatingVertebral columnVital capacityage groupclinical outcome measurescohortdeep learningdeep learning algorithmhealth assessmentinnovationnovelprospectivepulmonary functionradiological imagingrespiratorysurgery outcometreatment effectventilationvirtual
项目摘要
Thoracic Insufficiency Syndrome (TIS) is a group of serious disorders of the pediatric thorax resulting in an
inability of the thorax to support respiration or lung growth. TIS is associated with at least 28 pediatric
syndromes, with an estimated health care cost per patient that can easily exceed a million dollars. In TIS,
three-dimensional deformity of the thoracic components anatomically and functionally reduces the volume
available for ventilation. Pediatric specialists dealing with TIS currently face several serious challenges: (a) The
complex interplay among dynamic and growing thoracic structures and its influence on thoracic function and
growth are not understood at present. (b) The prime outcome measure for the corrective procedures has
remained the radiographic Cobb angle of the spine, a 60-year old metric with poor correlation with lung
dynamic function and limited true health assessment value. (c) A normative imaging database with functional
metrics describing dynamics and growth of the thoracic structures of the normal pediatric population does not
exist. Due to these hurdles, innovations in growth-modulating surgical techniques are difficult to achieve.
Supported by extensive preliminary results based on dynamic MRI (dMRI) of patients and normal subjects, the
overarching goal of this proposal is to develop novel dynamic functional metrics for TIS by establishing a
normative database of dMRI images and anatomic and functional models and metrics, and to translate these to
develop markers of TIS and of its corrective-surgery outcomes. The project has three aims. Aim 1: To develop
a new methodology called The Virtual Growing Child (VGC) consisting of 4 key components: a) To build a
normative database of dMRI images prospectively gathered from 200 normal children divided into 10 groups.
b) To build population anatomic models involving key thoraco-abdominal objects following an established
automatic anatomy recognition (AAR) technology and deep learning (DL) techniques. c) To develop and
validate joint AAR-DL algorithms to segment these objects in dMRI images of TIS patients. d) To build a
normative database of measurements derived from dMRI images describing normal thoracic architecture,
dynamic function, and growth. The database will also include a full battery of Pulmonary Function Testing data
and anthropometric measurements. Aim 2: To test retrospectively the utility of the VGC ensemble in deriving
markers of TIS and its surgical treatment effects on a cohort of 100 TIS patients. Aim 3: To retrospectively test
the utility of the VGC approach for planning surgery in 30 TIS patients by comparing VGC-guided surgical
planning to the current planning method. The post-operative key dMRI parameters of patients whose surgical
plan would have changed due to VGC data will be compared to those of patients whose plan did not change.
Expected outcomes: (i) A unique registry of thoracic dMRI of 200 normal pediatric subjects, segmented
objects, and the associated anatomic, dynamic, and developmental parameters. (ii) A validated VGC approach
for studying TIS which can also be utilized for studying other pediatric and adult thoracic disorders.
胸廓关闭不全综合症(TIS)是一组严重的小儿胸部疾病,导致
胸部无法支持呼吸或肺部生长。 TIS 与至少 28 名儿童相关
综合症,估计每位患者的医疗费用很容易超过一百万美元。在TIS中,
胸部组件的三维畸形在解剖学和功能上减少了体积
可用于通风。处理 TIS 的儿科专家目前面临着几个严峻的挑战:(a)
动态和生长的胸部结构之间复杂的相互作用及其对胸部功能的影响
目前尚不了解增长。 (b) 纠正程序的主要结果措施是
仍然是脊柱的放射科布角,这是一个有 60 年历史的指标,与肺的相关性较差
动态功能和真实健康评估价值有限。 (c) 具有功能性的规范成像数据库
描述正常儿科人群胸部结构动态和生长的指标并不
存在。由于这些障碍,生长调节手术技术的创新很难实现。
基于患者和正常受试者的动态 MRI (dMRI) 的广泛初步结果的支持,
该提案的总体目标是通过建立一个 TIS 开发新颖的动态功能指标
dMRI 图像以及解剖和功能模型和指标的规范数据库,并将这些转化为
开发 TIS 及其矫正手术结果的标记。该项目有三个目标。目标一:发展
一种称为虚拟成长儿童 (VGC) 的新方法,由 4 个关键组成部分组成:
dMRI 图像的规范数据库前瞻性地收集了 200 名正常儿童,分为 10 组。
b) 按照既定的标准建立涉及关键胸腹部对象的群体解剖模型
自动解剖识别(AAR)技术和深度学习(DL)技术。 c) 开发和
验证联合 AAR-DL 算法来分割 TIS 患者 dMRI 图像中的这些对象。 d) 建立一个
源自描述正常胸部结构的 dMRI 图像的标准化测量数据库,
动态功能和生长。该数据库还将包括全套肺功能测试数据
和人体测量。目标 2:回顾性测试 VGC 集成在推导中的效用
TIS 标志物及其手术治疗对 100 名 TIS 患者的影响。目标 3:回顾性测试
通过比较 VGC 引导的手术,了解 VGC 方法在 30 名 TIS 患者中规划手术的效用
规划改为现行规划方法。手术患者术后关键 dMRI 参数
由于 VGC 数据将与计划未改变的患者的数据进行比较,因此计划可能会发生变化。
预期成果: (i) 对 200 名正常儿科受试者进行独特的胸部 dMRI 登记,并进行分段
对象,以及相关的解剖、动态和发育参数。 (ii) 经过验证的 VGC 方法
用于研究 TIS,也可用于研究其他儿科和成人胸部疾病。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Automatic lung segmentation in dynamic thoracic MRI using two-stage deep convolutional neural networks.
使用两级深度卷积神经网络在动态胸部 MRI 中自动进行肺部分割。
- DOI:10.1117/12.2612558
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Xie,Lipeng;Udupa,JayaramK;Tong,Yubing;McDonough,JosephM;Wu,Caiyun;Lott,Carina;Anari,JasonB;Cahill,PatrickJ;Torigian,DrewA
- 通讯作者:Torigian,DrewA
Regional diaphragm motion analysis via dynamic MRI.
通过动态 MRI 进行区域膈肌运动分析。
- DOI:10.1117/12.2611951
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Hao,You;Udupa,JayaramK;Tong,Yubing;Wu,Caiyun;McDonough,JosephM;Lott,Carina;Clark,Abigail;Anari,JasonB;Cahill,PatrickJ;Torigian,DrewA
- 通讯作者:Torigian,DrewA
Automatic labeling of respiratory phases and detection of abnormal respiratory signals in free-breathing thoracic dynamic MR image acquisitions based on deep learning.
基于深度学习的自由呼吸胸部动态MR图像采集中呼吸相位的自动标记和异常呼吸信号的检测。
- DOI:10.1117/12.2549983
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Sun,Changjian;Udupa,JayaramK;Tong,Yubing;Wu,Caiyun;McDonough,JosephM;Qiu,Catherine;Lott,Carina;Anari,JasonB;Torigian,DrewA;Cahill,PatrickJ
- 通讯作者:Cahill,PatrickJ
QdMRI: A system for comprehensive analysis of thoracic dynamics via dynamic MRI.
QdMRI:通过动态 MRI 综合分析胸部动力学的系统。
- DOI:10.1117/12.2612117
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Tong,Yubing;Udupa,JayaramK;Hao,You;Xie,Lipeng;McDonough,JosephM;Wu,Caiyun;Lott,Carina;Clark,Abigail;Anari,JasonB;Torigian,DrewA;Cahill,PatrickJ
- 通讯作者:Cahill,PatrickJ
4D image construction from free-breathing MRI slice acquisitions of the thorax based on a concept of flux.
基于通量概念,通过胸部自由呼吸 MRI 切片采集构建 4D 图像。
- DOI:10.1117/12.2550040
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Hao,You;Udupa,JayaramK;Tong,Yubing;Wu,Caiyun;Li,Hua;McDonough,JosephM;Torigian,DrewA;Cahill,PatrickJ
- 通讯作者:Cahill,PatrickJ
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Drew Torigian其他文献
Drew Torigian的其他文献
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{{ truncateString('Drew Torigian', 18)}}的其他基金
Virtual growing child 5-dimensional functional models for treating respiratory anomalies
用于治疗呼吸异常的虚拟成长儿童 5 维功能模型
- 批准号:
10308447 - 财政年份:2020
- 资助金额:
$ 74.26万 - 项目类别:
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