From diagnostic imaging to image-based interventional planning of cerebral aneurysms
Using Cloud & HPC Infrastructures To Meet Computing Requirements for In-Silico MedicineHigh Performance Computing &Big Data Conference 2016Dr Susheel Varma, Chief Technology Officer, SSI FellowCenter for Computational Imaging & Simulation Technologies in Biomedicine CISTIBThe University of Sheffield, Sheffield, [email protected]
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From Aerodynamics to Vascular Dynamics
2D Rotational Angiogram
Virtual FFR using Computational Fluid Dynamics
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CellTissueOrganismOrgan Proteins
Complex Spatio-temporal Modelling
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Computational Imaging & PhysiologyDescriptive & predictive computational models of physiology and post-interventional disease courseNon invasive and in vivo visualization of biological structure & functionComputerized high-throughput quantification of structure & function from images and their fusionCISTIBBiomedicalImaging & SensingImage & SignalComputingPersonalisedModeling & SimulationSubject-specific biomedical simulationsVirtual deployment of medical devicesTraining systems for minimally invasive interventionsSubject-specific design or customization of medical devicesPre-operative interventional planningImage-based surgical and interventional guidanceEvaluation of targeted contrasts agentsVirtual imaging techniquesStructure & function quantification from medical imagesVisualization & fusion of multimodal imagingAdvanced diagnostic and prognostic imaging biomarkersQuantify impact of medical products on structure & function
CardiovasculareuHeartCerebrovascular@neurISTMusculoskeletalMySpine / MD-PaedigreeNeurodegenerationVPH-DARE@IT
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in silico Medicine (Precision Medicine)
is the direct use of computer simulation in the diagnosis, treatment, or prevention of a disease.Predict diseasePersonalise treatment
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10 INSIGNEO 2015
IMAGES/DATA
PROCESS
ANALYSIS
I.T.
CLINI CAL
OUTPUT10% RUPTURE RISK
PORTAL
NETWORKS
WORKFLOWS
CLOUD/HPC
In silico workflows are built using two parallel strands:In Silico workflows
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IMAGES/DATA
PROCESS
ANALYSIS
OUTPUT
NEUROLOGY (e.g. @neurIST)MRI SCANSEGMENTATIONRUPTURE RISK
IMAGES/DATA
PROCESS
ANALYSIS
OUTPUTBLOOD FLOW
CARDIOLOGY (e.g. euHeart)ANGIOGRAMSEGMENTATIONPRESSURE PROFILEFLUID DYNAMICS
IMAGES/DATA
PROCESS
ANALYSIS
OUTPUT
ORTHOPAEDICS (e.g MySpine)MR/CT SCANSEGMENTATIONDISC DEGENERATIONBENDING
I.T.
NETWORKS
CLOUD/HPC
WORKFLOWS
PORTAL
In Silico workflows for every medical domain
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Clinical Research Exemplars
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euHeart: Patient-Specific Cardiac Simulation Workflow
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euHeart: Patient-Specific Cardiac Simulation Workflow
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Image-based Computational Haemodynamics
DICOMInput: DICOMOutput: 3D imageDescription: Converts a DICOM image to VTK image
Volume RenderingInput: 3D imageOutput: 3D imageDescription: aneurysm and vessels Visualisation
Bounding BoxInput: 3D imageOutput: ROIDescription: volume selection
GAR SegmentationInput: Image,ROIOutput: surface meshDescription: vessels and aneurysm extraction
Mesh EditingInput: surface meshOutput: surface meshDescription: clipping vessels, cleaning surface (cell removal, closing holes, smoothing)
SkeletonizationInput: surface mesh.Output: skeleton.Description: necessary to set the boundary conditions
Aneurysm isolationInput: surface meshOutput: surface meshDescription: aneurysm isolation
Morphology DescriptorsInput: surface meshOutput: xml, vtk Description: surface, depth and ZMI calculation
Volumetric MeshInput: surface meshOutput: volumetric meshDescription: creates a volumetric mesh of the selected geometry
Flow SimulationInput: volumetric mesh, cclOutput: wall shear stress mapDescription: solves flow equations
Flow Simulation post-processingInput: wall shear stressOutput: .csv fileDescription: computes hemodynamic descriptors
CFD preprocessor
Input: xml, surface meshOutput: surface mesh, cclDescription: Defines hemodynamic model
Input: surface, 1D modelOutput: xml, vtkDescription: boundary conditions for CFDSelecting Boundary ConditionsNeck Selection
Input: surface meshOutput: surface meshDescription: aneurysm neck surface and dome selection
GIMIAS@neuFuseANSYS (ICEM)ANSYS (CFX)Manual interactionCommon operationsMorphological analysisHemodynamic analysis
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Image-based Computational Haemodynamics
Image acquisitionSegmentationSurface correctionVolumetric mesh generationComputational Fluid Dynamics modeling and simulationData analyses
Patient specificboundary conditions
OSIWSSStreamlines
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VPH-Dare@ITDementia
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Model of brain life course and ageing
World Alzheimer Report 2014 www.alz.co.uk/research
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Hypothetical model of biomarkers in AD
Jack CR Jr, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, Petersen RC, Trojanowski JQ. Hypotheticalmodelofdynamicbiomarkersof theAlzheimer'spathologicalcascade. Lancet Neurol. 2010 Jan;9(1):119-28.Petersen RC. Alzheimer's disease: progress in prediction. Lancet Neurol. 2010 Jan;9(1):4-5. Jack CR Jr1, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick TG, Pankratz VS, Donohue MC, Trojanowski JQ. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013 Feb;12(2):207-16.
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Population Data/Imaging
500k people100k imaged
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Biophysical Brain ModelInterpolated permeability tensors: Input to MPET
Mesh Generation Workflow
Philips Brain Segmenation
Diffusion Tensor Extraction
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Biophysical Brain Model
Vardakis JC, Tully BJ, Ventikos Y. Exploring the efficacy of endoscopic ventriculostomy for hydrocephalus treatment via a multicompartmental poroelastic model of CSF transport: a computational perspective. PLoS One. 2013 31;8(12):e84577.
Source: http://www.3dscience.com/Individual / Population ProfilesAnatomical ProfileTissue Types &PropertiesGeneticProfile
Environment / Lifestyle ProfilesSystemic BCAlterationsMolecular AlterationsGeneticAlterations
CellularProfile
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Environmental & Lifestyle Factors
Source: Environmental Threats to Healthy Aging. http://www.agehealthy.org/
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VPH-DARE@IT in a nutshellSection name
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Multiscale Multifactorial Multiparadigm Modelling Platform
Human health dataclinicalpopulationenvironmental
Mechanistic ModellingTop-down
Phenomenological ModellingBottom-upStatistical associationsConnectivity networksBiophysical FE ModelsMetabolic PathwaysBiosignals Modelling
personalised environment &informationpersonal & environmentaldata
Platforms for Biomedical Research &Clinical Decision Supporthealthcareresearchcitizensmechanisticpredictions &biomarkersphenomenological inferences & associations
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VPH-DARE@IT Partners
The University of Sheffield VTT Technical Research Centre of FinlandESI Group S.A Advanced Simulation & Design GmbH Empirica Gesellschaft fr Kommunikations und Technologieforschung mbH Universitetet i Oslo Erasmus Universitair Medisch Centrum RotterdamHirslanden Klinik Philips Medical Systems Nederland BV Eidgenssische Technische Hochschule ZrichKings College, London Philips Technologie GmbH Sheffield Teaching Hospital NHS Foundation Trust University College London It-Suomen yliopisto University of Maastricht Kinematix (Tomorrow Options Microelectronics S.A.)Imperial College of Science, Technology and Medicine EIBIR Gemeinntzige Gmbh zur Frderung der Erforschung der Biomedizinischen Bildgebung
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VPH-ShareResearch As A Service
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INSIGNEO 2015
Cloud Platform(Public / Private)
Patient DataWorkflow InputsWorkflow Outputs
Semantic Services
Patient Centred In Silico Workflows
Patient AvatarApplicationsInfrastructureHPC Infrastructure(DEISA / PRACE)Personalised ModelKnowledge DiscoveryData InferenceCompute ServicesStorage ServicesKnowledge ManagementData Services:Patient/PopulationeuHeart@neurISTVPH OPViroLab
Select WorkflowRetrieve Existing DataTransform or Infer DataRun WorkflowReturn Results
Outreach
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Single point of entryApplicationRepositoryRich library of biomedical dataCloud PlatformVPH ApplicationsBuild new workflowsHigh Performance ComputingGuided search
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Single point of entryApplicationRepositoryRich library of biomedical dataCloud PlatformVPH ApplicationsBuild new workflowsHigh Performance ComputingGuided search
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VPH-Share Technology Architecture
ATMAtmosphere Cloud Platform
Atomic Service Deployment Wizard
MAFEventBus
Authentication Services
Workflow Execution Service
Workflow Registry
Atomic ServiceRegistry
Atomic ServiceManagerData Browser
Atomic ServiceGeneric InvokerMaster Interface
Cloud Facade
Visualisation Tools
Workflow Composer
VPH-Share Client
Generic WorkflowDocument
Atomic Service Description
CloudClients
libcloud provider
libcloud provider
Monitoring Controller
High PerformanceExecution Engine (AHE)
Extension Points
SPRUCE
HARC
Steering
AHE Services API
AHE Runtime
AHE Engine
App Registry
JBPM Workflow& Main Logic
AHE DatabaseHibernate ORM
App State Object
Storage Module
Connector Module
External Data Storage
External HPC PlatformSecurity Module
Allocation Management Service
AMS Manager (Java) OSGi bundlesApache Karaf
Scheduler / Optimizer
Algo n
Algo 1
REST API & HTML Service(Ruby) Sinatra & Passenger
Domain Model (Ruby)
Atmosphere Internal RegistryMongoDBVirtual Machine Template Registry
Data Buckets(C-DISC, CSV, )Databases(SQLServer, )
External StructuredData Providers
DataPublishingSuite (GUI)
Schema Crawler
SPARQL
Discovery
Browser
Search
RDB2RDFService
LOD Databases
Silk, LinQuerService
LD DatabasesMulti-Ontology/Archetype Search Services
Taverna Server
Service Registry
Load Balancer
Proxy Controller
Data Reliability & Integrity Services
PSLoader
External Cloud Data StorageSemantic Services
VoID Document Database
Database 1 Query Services(SPARQL & SQL)
Database Services Integration PointsDatabase 2 Query Services(SPARQL & SQL)
Database n Query Services(SPARQL & SQL)
Individual Relational Databases
VoID Services
VoIDDocument
Atmosphere Cloud Platform
Monitoring System
Atomic Service Instance Contents
Raw Operating System (Linux)
LOBCDER Federated Storage AccessRoot Volume
VPH-Share Tool / App
Web Service WrapperSoaplab2, CXF, soap4r
Remote AccessService
Web Service Security Agent
Monitoring Agent (Munin)
Hypervisor
Driver
Manager
Compute Worker
Network WorkerObjectStorage(Swift)
Dashboard
Queue
Scheduler
ProxyAccountContainerObject
ASIProxy
Private Compute & Storage Cloud (OpenStack Example)
Data Volume
Data Resource Catalog
LOBCDER Data Federation Middleware
Data Stores
Connection Module
Request Manager
Access & Control Frontend
Virtual Resource System
Driver 1
Driver n
Cloud Storage Driver
Data Infrastructure Services
Images
NOVA API
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32#VPH2014 Trondhiem 09-Sep-14
Physicalresources
Atomic Service InstancesDeployed by AMS on available resources as required by WF mgmt or generic AS invoker
Raw OS (Linux variant)
LOB Federated storage access
Web Service cmd. wrapper
Generic VNC server
VPH-Share Tool / App.
DRIService
Atmosphere persistence layer (internal registry)
VM templates
AS images
Available cloudinfrastructureManageddatasets
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AMService
LOB federatedstorage access
Cloud stackclients
HPC resourceclient/backend
Data and Compute Cloud Platform
VPH-Share Master UI
AS mgmt. interfaceGeneric AS invokerComputationUI extensions
Data mgmt. interfaceGeneric data retrievalData mgmt.UI extensions
Remote access toAtomic Svc. UIs
Custom AS client
Workflow description and executionDeveloper
ScientistAdmin
Security mgmt. interfaceSecurityframework
Web Service security agent
Modules available in first prototype
Cloud/HPC Platform Architecture
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Tabular DataNon-Tabular DataClinical Information Systems
Data Publishing SuiteSemantic Services
Computational Workflows and Services1234891067
MedicationsVital SignsLab ReportsDemographicVital SignsImagesDemographicRisk FactorsGenomic DataParameterEstimationUncertaintyPropagationPatient Avatar
RDFGraphs
ReferenceData
PhysiologicalEnvelope
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ClinicalResearcherWorkflow Manager API
VPH-Share pluginTavernaServer
VPH-Share WorkflowCloudFaade
Web-basedRemote Desktop
AS without interactionAS with interactionCLIENT-SIDESERVER-SIDEASASASASASASExternalApplication
STORAGE
VPH-Share pluginTavernaWorkbench
Web servicesGIMIAS CLPs
VPH-Share pluginTavernaOn-lineWeb services
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VPH-Share Platform by Numbers
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VPH-Share Platform by Numbers4 Private Data CentersCYFRONET, KrakowUoS, SheffieldSTH, SheffieldUNV, Vienna800vCPU Cores, 32TB RAM, 200+ Applications (Baseline), 453 Applications (Peak)250TB+ Structured/Unstructured Data Storage150+ Scientific Applications [VMs -> Docker]50+ Scientific WorkflowsPublic Cloud Burst (Avg 2k CPUhrs/month)
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VPH-Share Platform by NumbersA variety of projects are already making use of VPH-Shares infrastructure services for running workflows and storing tools and data.
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ChallengesDistributed data lifecycle management is really hard!!Use the right level of metadata to avoid a collective prisoners dilemmaApply provenance metadata at all stages of the data pipelineInter- and intra-operability between clouds and HPCCommunity level push towards standardised access protocolDealing with batch & unbounded data streams (lifestyle)
We dont want to be in the business of build custom infrastructureWe want to be in the business of doing Science
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