Automated data curation to ensure model credibility in the Vascular Model Repository
Automated data curation to ensure model credibility in the Vascular Model Repository
批准号:
10175029
负责人:
Alison L Marsden
金额:
$33.03万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-12 至 2023-05-31
关键词:
3-DimensionalAdoptionAnatomic ModelsAnatomyBasic ScienceBlood VesselsBlood flowCardiacCardiovascular DiseasesCardiovascular ModelsCardiovascular systemClinicalClinical DataClinical SciencesCollaborationsCommunitiesComplexComputer softwareDataData ScienceData SetDatabasesDiagnosisDiseaseElectrophysiology (science)EnsureFeedbackFosteringFundingGoalsHigh Performance ComputingImageImage AnalysisIncentivesIntakeInterventionJointsLawsMachine LearningManualsMapsMechanicsMedical Device DesignsMedical ImagingMethodsModelingMusculoskeletalOperative Surgical ProceduresPatient riskPatientsPhysicsPhysiologicalProcessPublicationsRadiology SpecialtyRecording of previous eventsReproducibilityResearchResolutionResourcesRisk AssessmentRunningScienceSoftware EngineeringSource CodeSupervisionSystemTechniquesTimeTriageUncertaintyUnited States National Institutes of Healthautomated analysisbaseclinical applicationclinical carecomputing resourcesdata curationdata formatdata repositorydata resourcedeep learningexperiencegigabyteimaging Segmentationinnovationlarge scale datamodels and simulationnovelonline repositoryopen dataopen sourcerepositoryrespiratoryshape analysissimulationsoftware developmentstemsuccesssupercomputersupervised learningthree-dimensional modelingtreatment planningtrustworthinessunsupervised learningweb portal
中文摘要
心血管疾病的三维解剖建模与仿真(3D M&S)已成为
治疗计划、医疗器械设计、诊断和FDA批准的关键组成部分。全面、
精心策划的3-D M&S数据库对于实现重大挑战以及推进模型简化、塑造
分析,深入学习,为临床应用。然而,涉及3D M&S的大规模开放数据精选
面临独特的挑战;模拟是数据密集型的,基于物理的模型日益复杂
社区使用高分辨率、不同种类的求解器和数据格式,并进行模拟
需要大量高性能计算资源。手动管理大型开放数据存储库,同时
因此,确保内容得到核实和可信是一件棘手的事情。我们的目标是克服这些挑战
通过开发广泛适用的自动管理数据科学来确保模型的可信度和
3-D M&S,利用我们团队在CV模拟、不确定性量化、
成像科学,以及我们现有的开放数据和开源项目。我们的团队有丰富的经验
开发和管理开放数据和软件资源。2013年,我们推出了血管模型库
(VMR),提供120个公开可用的数据集,包括医学图像数据、解剖血管模型和
血流模拟结果,横跨众多血管解剖和疾病。VMR兼容
唯一提供最先进的基于图像的血流建模的完全开源平台--SimVculate
以及对CV仿真社区的分析能力。我们认为,新奇的管理科学将使
VMR可快速获取新数据,同时自动评估模型的可信度,从而创建独特的资源来
通过在3D M&S中的广泛应用来培养心血管疾病社区的严密性和重复性。
为了实现这些目标,我们提出了三个具体目标:1)开发和验证自动管理方法以评估
根据医学图像数据建立的特定于患者的解剖模型的可信度,2)自动化开发和验证
评估3D血流模拟结果的可信度的管理方法,3)发布数据管理套件
和扩展的VMR。这项拟议的研究具有重大意义和创新性,因为它将1)使
通过限制馆长在数据获取期间的干预来扩展存储库,利用与
2)提高模型在CV模拟社区中的可信度;3)应用新的监督和
评估解剖模型保真度的非监督方法,4)利用降阶模型快速
评估复杂的3D数据。这个项目汇集了一支独特的心血管模拟专家团队,
SimVial的开发者和VMR的创造者,一位专业的软件工程师和放射学
技术专家。我们将在我们推出和支持开源和开放的成功记录的基础上再接再厉
确保成功的数据资源。3D M&S的数据管理科学将对其他行业产生直接而广泛的影响
并最终影响心血管疾病的临床护理。
英文摘要
Three-dimensional anatomic modeling and simulation (3D M&S) in cardiovascular (CV) disease have become a
crucial component of treatment planning, medical device design, diagnosis, and FDA approval. Comprehensive,
curated 3-D M&S databases are critical to enable grand challenges, and to advance model reduction, shape
analysis, and deep learning for clinical application. However, large-scale open data curation involving 3-D M&S
present unique challenges; simulations are data intensive, physics-based models are increasingly complex and
highly resolved, heterogeneous solvers and data formats are employed by the community, and simulations
require significant high-performance computing resources. Manually curating a large open-data repository, while
ensuring the contents are verified and credible, is therefore intractable. We aim to overcome these challenges
by developing broadly applicable automated curation data science to ensure model credibility and
accuracy in 3-D M&S, leveraging our team’s expertise in CV simulation, uncertainty quantification,
imaging science, and our existing open data and open source projects. Our team has extensive experience
developing and curating open data and software resources. In 2013, we launched the Vascular Model Repository
(VMR), providing 120 publicly-available datasets, including medical image data, anatomic vascular models, and
blood flow simulation results, spanning numerous vascular anatomies and diseases. The VMR is compatible
with SimVascular, the only fully open source platform providing state-of-the-art image-based blood flow modeling
and analysis capability to the CV simulation community. We propose that novel curation science will enable the
VMR to rapidly intake new data while automatically assessing model credibility, creating a unique resource to
foster rigor and reproducibility in the CV disease community with broad application in 3D M&S. To accomplish
these goals, we propose three specific aims: 1) Develop and validate automated curation methods to assess
credibility of anatomic patient-specific models built from medical image data, 2) Develop and validate automated
curation methods to assess credibility of 3D blood flow simulation results, 3) Disseminate the data curation suite
and expanded VMR. The proposed research is significant and innovative because it will 1) enable rapid
expansion of the repository by limiting curator intervention during data intake, leveraging compatibility with
SimVascular, 2) increase model credibility in the CV simulation community, 3) apply novel supervised and
unsupervised approaches to evaluate anatomic model fidelity, 4) leverage reduced order models for rapid
assessment of complex 3D data. This project assembles a unique team of experts in cardiovascular simulation,
the developers of SimVascular and creator of the VMR, a professional software engineer, and radiology
technologists. We will build upon our successful track record of launching and supporting open source and open
data resources to ensure success. Data curation science for 3D M&S will have direct and broad impacts in other
physiologic systems and to ultimately impact clinical care in cardiovascular disease.
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DOI:
10.1115/1.4056055
发表时间:
2023-03-01
期刊:
JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME
影响因子:
1.7
作者:
[Pham,Jonathan, Wyetzner,Sofia, Marsden,Alison L. L.]
通讯作者:
Marsden,Alison L. L.
Branched Latent Neural Maps
分支潜在神经图
DOI:
10.1016/j.cma.2023.116499
发表时间:
2024
期刊:
Computer Methods in Applied Mechanics and Engineering
影响因子:
7.2
作者:
[Salvador, Matteo, Marsden, Alison Lesley]
通讯作者:
Marsden, Alison Lesley
DOI:
10.1002/cnm.3639
发表时间:
2022-10
期刊:
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
影响因子:
2.1
作者:
[Pfaller, Martin R., Pham, Jonathan, Verma, Aekaansh, Pegolotti, Luca, Wilson, Nathan M., Parker, David W., Yang, Weiguang, Marsden, Alison L.]
通讯作者:
Marsden, Alison L.
DOI:
10.1007/s10237-021-01519-4
发表时间:
2021-12
期刊:
BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
影响因子:
3.5
作者:
[Dong, Melody L., Lan, Ingrid S., Yang, Weiguang, Rabinovitch, Marlene, Feinstein, Jeffrey A., Marsden, Alison L.]
通讯作者:
Marsden, Alison L.
DOI:
10.1038/s41598-023-49942-0
发表时间:
2023-12-18
期刊:
Scientific reports
影响因子:
4.6
作者:
[]
通讯作者:
Computational Medicine in the Heart, Integrated Training Program
-
批准号:10556918
-
项目类别:
-
资助金额:$20.1万
-
财政年份:2023
-
负责人:Alison L Marsden
-
依托单位:
Preclinical testing of a 3D printed external scaffold device to prevent vein graft failure after coronary bypass graft surgery
-
批准号:10385132
-
项目类别:
-
资助金额:$34.51万
-
财政年份:2022
-
负责人:Alison L Marsden
-
依托单位:
SCH: INT: A Virtual Surgery Simulator to Accelerate Medical Training in Cardiovascular Disease
-
批准号:10412769
-
项目类别:
-
资助金额:$31.49万
-
财政年份:2019
-
负责人:Alison L Marsden
-
依托单位:
SCH: INT: A Virtual Surgery Simulator to Accelerate Medical Training in Cardiovascular Disease
-
批准号:10487534
-
项目类别:
-
资助金额:$26.32万
-
财政年份:2019
-
负责人:Alison L Marsden
-
依托单位:
SCH: INT: A Virtual Surgery Simulator to Accelerate Medical Training in Cardiovascular Disease
-
批准号:10259714
-
项目类别:
-
资助金额:$25.8万
-
财政年份:2019
-
负责人:Alison L Marsden
-
依托单位:
SCH: INT: A Virtual Surgery Simulator to Accelerate Medical Training in Cardiovascular Disease
-
批准号:10020975
-
项目类别:
-
资助金额:$26.53万
-
财政年份:2019
-
负责人:Alison L Marsden
-
依托单位:
Automated data curation to ensure model credibility in the Vascular Model Repository
-
批准号:10016840
-
项目类别:
-
资助金额:$33.05万
-
财政年份:2019
-
负责人:Alison L Marsden
-
依托单位:
Enabling reliable cardiovascular simulations via uncertainty quantification
-
批准号:9030537
-
项目类别:
-
资助金额:$38.84万
-
财政年份:2016
-
负责人:Alison L Marsden
-
依托单位:
Enabling reliable cardiovascular simulations via uncertainty quantification
-
批准号:9348646
-
项目类别:
-
资助金额:$38.84万
-
财政年份:2016
-
负责人:Alison L Marsden
-
依托单位:
Enabling reliable cardiovascular simulations via uncertainty quantification
-
批准号:9751081
-
项目类别:
-
资助金额:$38.84万
-
财政年份:2016
-
负责人:Alison L Marsden
-
依托单位:
Multiscale modeling for vein graft failure risk stratification in CABG patients
-
批准号:9331731
-
项目类别:
-
资助金额:$37.47万
-
财政年份:2014
-
负责人:Alison L Marsden
-
依托单位:
Multiscale modeling for vein graft failure risk stratification in CABG patients
-
批准号:9126335
-
项目类别:
-
资助金额:$37.25万
-
财政年份:2014
-
负责人:Alison L Marsden
-
依托单位:
Patient-specific simulations for thrombotic risk assessment in Kawasaki disease
-
批准号:8063023
-
项目类别:
-
资助金额:$18.27万
-
财政年份:2010
-
负责人:Alison L Marsden
-
依托单位:
Patient-specific simulations for thrombotic risk assessment in Kawasaki disease
-
批准号:7876583
-
项目类别:
-
资助金额:$22.2万
-
财政年份:2010
-
负责人:Alison L Marsden
-
依托单位:
海外基金