Your SlideShare is downloading. ×
OpenStack in Action 4! Susheel Varma - VPH-Share: Patient-Centred Multi-scale Cloud-enabled Scientific Workflows
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Saving this for later?

Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime - even offline.

Text the download link to your phone

Standard text messaging rates apply

OpenStack in Action 4! Susheel Varma - VPH-Share: Patient-Centred Multi-scale Cloud-enabled Scientific Workflows

180
views

Published on

Paris, 5th December 2013 : OpenStack in Action 4! organized by eNovance, brings together members of the OpenStack community.

Paris, 5th December 2013 : OpenStack in Action 4! organized by eNovance, brings together members of the OpenStack community.

Published in: Technology, Education

0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
180
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
12
Comments
0
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Reproducibility a principal driver of the scientific method
  • 2. Patient Centred Multi-Scale CloudEnabled Computational Workflows Dr Susheel Varma University of Sheffield
  • 3. in silico Medicine “…is the direct use of computer simulation in the diagnosis, treatment, or prevention of a disease.” Predict disease #OIA4        Paris,  France        04-­‐Dec-­‐13   Personalise treatment 3  
  • 4. Select  Workflow   Retrieve   ExisGng  Data   Transform     or  Infer  Data   Run   Workflow   Return   Results   Patient Data Workflow Inputs Workflow Outputs VPH-Share euHeart @neurIST Infostructure Co-ordinator: University of Sheffield, UK Personalised Model Patient Avatar Application Project No: 269978 Partners: Patient Centred Computational Workflows Knowledge Management Knowledge Discovery Data Inference Data Services: Patient/Population Compute Services HPC Infrastructure (Public / Private) Semantic Services Storage Services Cloud Platform (DEISA / PRACE) VPH OP ViroLab CYFRONET, PL Sheffield Teaching Hospitals, UK ATOS Origin, ES Kings College London, UK Empirica, DE CiNECA, IT Nine Health CIC, UK INRIA, FR IOR, IT Open Univ., UK Philips Elec., NL TU Eindhoven, NL Univ. Auckland, NZ Uv Amsterdam, NL UCL, UK Univ. Vienna, AT AATRM, ES FCRB, ES #SummerSchool    20-­‐Jun-­‐13   4  
  • 5. VPH-Share A0 Master Plan VPH Shar e Clien t ATM Master Interface Atomic Service Manager Atmosphere Cloud Platform Atomic Service Generic Invoker Data Browser Workflow Composer Semantic Services Visualisation Tools Service Registry … Silk, LinQuer Service … LOD Databases Multi-Ontology/ Archetype Search Services Data Buckets (C-DISC, CSV, …) Workflow Registry S P A R Q L D is c o v e B r r y o w s e S r e LD Databases RDB2RDF Service Generic Workflow Documen t Authentication Services libclou d provid er libclou d provid er Schema Crawler Workflow Execution Service Cloud Clients Atomic Service Registry Atomic Service Description Virtual Machine Template Registry Cloud Facade Proxy Controller a r c h Taverna Server MAFEventBus Monitoring Controller Atomic Service Deployment Wizard Database Services Integration Points AHE Services API AHE Runtime … Database 1 Query Services (SPARQL & SQL) Database n Query Services (SPARQL & SQL) Databases (SQLServer, …) … External Structured Data Providers REST API & HTML Service (Ruby) Sinatra & Passenger AMS Manag er (Java) OSGi bundle s Apach e Karaf … Database 2 Query Services (SPARQL & SQL) … Domain Model (Ruby) App State Objec t Scheduler / Optimizer Individual Relational Databases Mo ng oD Atmosphere Internal B Registry Allocation Management Service Data Publishing Suite (GUI) VoID VoID Document Document Database VoID Services AHE Engine App Regis try JBP M Workf low & Main Logic AHE Database Hibernate ORM Security Module Storage Module Data Reliability & Integrity Services External Data Storage Data Infrastructure Services Connector Module External HPC Platform Load Balancer Extension Points H S S A P t High PerformanceExecution Engine (AHE) R R e C U e C ri E n g ASIProxy Dashboard NOVA API Access & Control Frontend Network Worker Web Service Security Agent Compute Worker Web Service Wrapper Soaplab2, CXF, soap4r Remote Access Service Manager Driver VPH-Share Tool / App Hypervisor LOBCDER Federated Storage Access Q ue ue S ch ed ul er Request Manager Im ag es Virtual Resource System Cloud Storage Driver Data Volume Raw Operating System (Linux) Root Volume Atomic Service Instance Contents PSLoade r External Cloud Data Storage Connection Module Monitoring System Monitoring Agent (Munin) Data Resource Catalog Object Storage (Swift) P r A o c C c o x n y o u t O a n b t i j n e e c r t LOBCDER Data Federation Middleware Private Compute & Storage Cloud (OpenStack Example) Atmosphere Cloud Platform #OIA4        Paris,  France        04-­‐Dec-­‐13   5  
  • 6. Multi-Scale Scientific Workflows #OIA4        Paris,  France        04-­‐Dec-­‐13   6  
  • 7. Multi-Scale Challenges •  State Space Explosion •  Inverse Parameter Identification •  Parameter Sensitivity •  Incomplete Inputs •  Strong Spatio-Temporal Coupling •  Chaos and Unstablility •  Uncertainty Cascade #OIA4        Paris,  France        04-­‐Dec-­‐13   10  
  • 8. VPH-Share Flagship Workflows #OIA4        Paris,  France        04-­‐Dec-­‐13   11  
  • 9. Current  PracGce   Imaging   MulGmodal   RegistraGon   AcquisiGon     Conges(ve    H  eart  F  ailure                                                                     MulG-­‐scale  Models   Ontologies   Anatomical     FuncGonal     ComputaGonal     CellML   Geometry   Electrical/MR   EC  Cell   SoMware   OpenCMISS   SOFA   OPENFEM   LIFEV       Numerical       Ventricular  Flow   basis  reducGon,  POD     FEM,  FD,  ALE     ExcitaGon   Microstructure   Mechanics   VisualizaGon     GIMIAS   Parallel  CompuGng     AcGvaGon   FieldML   PETsc,     MUMPS     Data  assimilaGon     X-­‐Ray/MR   MoGon   Vasculature   Coronary  Flow   Perfusion   Modelling  tools  and    technologies     PaGent   Therapy   euHeart 16 Partners unscented  Kalmann   filtering  variaGonal   approaches         CMGUI   PaGent   € 19.05 million Jun 08 – Nov 12
  • 10. euHeart Simulation Workflow #OIA4        Paris,  France        04-­‐Dec-­‐13   13  
  • 11. euHeart Simulation Workflow #OIA4        Paris,  France        04-­‐Dec-­‐13   14  
  • 12. @neurIST Simulation Workflow Skeletoniza(on Input:  surface  mesh. Output:  skeleton. DescripGon:  necessary  to   set  the  boundary   condiGons Segmenta(on Volumetric  Mesh Input:  surface  mesh Output:  volumetric  mesh DescripGon:  creates  a   volumetric  mesh  of  the   selected  geometry Input:  surface,  1D  model Output:  xml,  vtk DescripGon:  boundary   condiGons  for  CFD     Input:  DICOM Output:  3D  image DescripGon:  Converts  a   DICOM  image  to  VTK   image Input:  Image,ROI Output:  surface  mesh DescripGon:  vessels  and   aneurysm  extracGon Input:  wall  shear  stress Output:  .csv  file DescripGon:  computes   hemodynamic  descriptors Mesh  Edi(ng CFD  preprocessor     Flow  Simula(on   post-­‐processing                 Medical   image Selec(ng  Boundary   Condi(ons Flow  Simula(on             Input:  surface  mesh Output:    surface  mesh DescripGon:  clipping   vessels,  cleaning  surface   (cell  removal,  closing   holes,  smoothing…) Input:  xml,  surface  mesh Output:  surface  mesh,  ccl DescripGon:  Defines   hemodynamic  model Neck  Selec(on Input:  volumetric  mesh,  ccl Output:  wall  shear  stress     map DescripGon:  solves  flow   equaGons     Input:  surface  mesh Output:  surface  mesh DescripGon:  aneurysm   neck  surface  and  dome   selecGon Morphology   Descriptors     Aneurysm   isola(on     #OIA4        Paris,  France        04-­‐Dec-­‐13   Input:  surface  mesh Output:  surface  mesh DescripGon:  aneurysm   isolaGon Input:  surface  mesh Output:  xml,  vtk   DescripGon:  surface,   depth…  and  ZMI   calculaGon Morphological   analysis   GIMIAS   Hemodynamic   analysis   ANSYS  (ICEM)   Common   opera(ons   @neuFuse   ANSYS  (CFX)   15   Manual  interacGon  
  • 13. PublicaGon   Data   Models,   Techniques,   Algorithms   Context   InvesGgaGon   Study   Assay   Provenance   AgribuGon   Credit   •  Gathered: scattered across different repositories/catalogues •  All necessary elements available and accessible maybe open •  Documented sufficiently well –  Explicitly Transparent: How, Why, What, Where, Who, When –  Comprehensive: Just Enough –  Comprehensible: Independent understanding •  Skills and resources to repeat –  Crowd sourced? Supercomputer? #OIA4        Paris,  France        04-­‐Dec-­‐13   16  
  • 14. Accessible   Reusable   Capable   PublicaGon   Data   INSTRUMENTs   Samples,Specimens   Strains   Models,   Techniques,   Algorithms   Context   InvesGgaGon   Study   Assay   74%  /  26%   31%  /  8%   Provenance   AgribuGon   Credit   #OIA4        Paris,  France        04-­‐Dec-­‐13   17  
  • 15. Embodying a Patient Avatar #OIA4        Paris,  France    04-­‐Dec-­‐13   19  
  • 16. Patient Avatar •  A large virtual catalogue of every item of data, information & knowledge of •  •  Medical Devices Medical Images Patient History Patient; or Collection of patients (Avatars) Vital Signs Genomics •  It also needs to be shared securely, to be able •  •  To be Searched, Browsed & Analysed For Healthcare, Research & Education Proteomics Procedures Results #OIA4        Paris,  France        04-­‐Dec-­‐13   Histology 20  
  • 17. Patient Avatar – Goals •  Integrating fragmented data and knowledge into a single cohesive unit of data •  Creating a centralised repository with reliable population and patient data around which VPH tools and applications could be built •  Providing diagnostic or prognostic decision and treatment planning support using predictive models built around a patient-specific avatar •  Providing a comprehensive overview of a patient with missing data based on averages from population phenotype to explore and test ideas virtually #OIA4        Paris,  France        04-­‐Dec-­‐13   21  
  • 18. Current Access to Clinical Data Owner or Facilitator Description Number (records) Accessibility Sheffield Teaching Hospitals ACS data Clinical data, outcomes ~750 Philips Others on request Nine Health HES extract Data catalogues ~ 5 millon On demand FRCB Clinical data Ethics approved for entire record On demand AATRM Images ~ 6 million On demand @neurIST Image data CRIM data Derived data euHeart 3D Models Virolab Rule database Publication corpus ~100 (600) ~1400 ~300 216 cardiac ~90 other 4 Rule DBs ~1.2 GB VPH-OP Extensive clinical baseline data Images 281 Mixed #OIA4        Paris,  France        04-­‐Dec-­‐13   On demand Registered users Registered users On demand 22  
  • 19. Knowledge Management, Discovery & Semantic Services #OIA4        Paris,  France  04-­‐Dec-­‐13   23  
  • 20. Health Language Terminology Terminology Sets Mappings •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  •  SNOMED CT / CA extensions •  CDT ICD-9P&CM •  Multiple Languages ICD-10 •  Local Codes ICD-10-CM / PCS •  Nomenclature CPT-4 •  ICD-10 (GM/AM/CA) HL7 •  ICD-O HCPCS •  UK Admin Extension APC, DRG, MS-DRG •  UK Gap Extension LOINC •  HRG ICPC1&2 •  OPCS-4 DSM IV •  CCI MeSH •  Read 2 Pharmacy (FDB, Multum) – NDC •  Read 4-byte RxNorm •  SNOMED Facets Nursing (NIC, NOC, NANDA) •  Clinical Specialty Subsets LCD/NCD/NCCI Consumer Friendly Terminology (CFT) #OIA4        Paris,  France        04-­‐Dec-­‐13   •  •  •  •  •  •  SNOMED CT to ICD-9-CM SNOMED CT to ICD-10 SNOMED CT to OPCS-4 ICD-9-CM to SNOMED CT SNOMED CT to CPT CPT to SNOMED CT ICD-9-CM to ICD-10-CM/ PCS ICD-10-CM/PCS to ICD-9CM SNOMED to MeSH DSM IV to SNOMED ICD-9-CM Procedures to SNOMED HL7 to CHI Language to Language (e.g., English to Spanish) 24  
  • 21. Web of Semantically Linked Data #OIA4        Paris,  France        04-­‐Dec-­‐13   25  
  • 22. Clinical Information Systems Tabular Data Non-Tabular Data Data Publishing Suite Semantic Services Reference Data Patient Avatar RDF Graphs Pseudo Identifier (UID) Demographics Height Weight Vital Signs Heart Rate Blood Pressure Systolic Diastolic Aneurysm Related Health Event Risk Factors Aneurysm Imaging Study Medications Demographic Vital Signs Images Pseudo Identifier (UID) Demographics Height Weight Vital Signs Heart Rate Blood Pressure Systolic Diastolic Pulmonary Function Risk Factors Cardiac Imaging Study Medications Pseudo Identifier (UID) Demographics Height Weight Vital Signs Heart Rate Blood Pressure Systolic Diastolic Orthopaedic Health Event Gynaecological Information Bone Phenotype Imaging Study Medications Demographic Medications Risk Factors Vital Signs Parameter Estimation Uncertainty Propagation Genomic Data Lab Reports Physiological Envelope 2 3 4 1 #OIA4        Paris,  France        04-­‐Dec-­‐13   8 9 10 6 7 Computational Workflows and Services 26  
  • 23. Patient Avatar & Workflow Archetypes (a) Common Shared Archetype (b) @neurIST Workflow Archetype Patient Pseudoidentifier (PID) (a) Common Shared Archetype Demographics (a) Common Shared Archetype (a) Common Shared Archetype Personal & Social History Patient Pseudoidentifier (PID) Patient Pseudoidentifier (PID) Fitness & Lifestyle Patient Pseudoidentifier (PID) Demographics Demographics Employment Details Demographics Personal & Personal & Social History Vital Signs Social History Personal & Fitness & UseSocial History Fitness & Lifestyle SubstanceLifestyle Fitness & Details Employment Lifestyle Employment Details Employment Details Vital Signs Vital Signs Vital Signs Substance Use Substance Use Substance Use Aneurysm Related Health Event (b)@neurISTRisk Factors (b) @neurISTWorkflow Archetype Supporting Workflow Archetype (b) @neurIST Workflow Archetype Specimens (Blood, Tissue) Aneurysm Related Health Event Aneurysm Related Health Event Medications Related Health Event Aneurysm Supporting Risk Factors SupportingImaging Study Aneurysm Risk Factors Supporting Risk Factors Specimens (Blood, Tissue) Specimens (Blood, Tissue) Imaging Details Specimens Medications (Blood, Tissue) Medications Medications Aneurysm Imaging Study Aneurysm Imaging Study Aneurysm Imaging Study Imaging Details Imaging Details Imaging Details (c) euHeart Workflow Archetype Baseline History (c) euHeart Workflow Archetype (c) euHeart Workflow Archetype Cardiac HealthWorkflow Archetype (c) euHeart Event Lab Tests Baseline History Baseline History Medications History Baseline Cardiac Health Event Cardiac Health Event Cardiac Imaging Study Cardiac Lab Tests Health Event Lab Tests Imaging Details Lab Tests Medications Medications Medications Cardiac Imaging Study Cardiac Imaging Study Cardiac Imaging Study Imaging Details Imaging Details Imaging Details #OIA4        Paris,  France        04-­‐Dec-­‐13   (e) VPHOP Workflow Archetype Hand Grip Strength (e) VPHOP Workflow Archetype (e) VPHOP Workflow Archetype Orthopeadic Health Event (e) VPHOP Workflow Archetype Medications Hand Grip Strength Hand Grip Strength Tissue) Specimens (Blood, Hand Grip Strength Orthopeadic Health Event Orthopeadic Health Event Study Bone PhenotypeHealth Event Orthopeadic Imaging Medications Medications Medications Specimens (Blood, Tissue) Specimens (Blood, Tissue) Specimens (Blood, Tissue) Bone Phenotype Imaging Study Bone Phenotype Imaging Study Bone Phenotype Imaging Study (d) ViroLab Workflow Archetype Sexual Health (d) Subtype Information (d) ViroLab Workflow Archetype HIVViroLab Workflow Archetype (d) ViroLab Workflow Archetype Specimens SexualHealth Sexual Health Sexual Health HIV Subtype Information HIV Subtype Information HIV Subtype Information Specimens Specimens Specimens 27  
  • 24. Knowledge Management #OIA4        Paris,  France        04-­‐Dec-­‐13   28  
  • 25. Cloud-Enabled Computational Workflows #OIA4        Paris,  France        04-­‐Dec-­‐13   29  
  • 26. Cloud-Enabled Computation Workflows •  portal.vph-share.eu – Provides access to Clinical Data and Scientific applications and workflows •  Taverna Workbench – Provides Desktop tool for composition of Scientific Workflows with VPH-Share applications and data •  OnlineHPC.com – Allows the creation of Scientific Workflows composed of External and VPH-Share Applications and VPH-Share data •  Meta-Workflow Manager – Executes multiple Scientific Workflow Engines on the VPH-Share Platform •  Workflow Cloud Plugin – Allows execution of Scientific Web-Services and Application on multiple cloud platforms •  Command-Line Wrapper – Allows developers to wrap command-line applications into a (REST/SOAP) webservice via wsme and GIMIAS •  NoMachine RDP – Provides Remote Desktop services for applications that require user interaction #OIA4        Paris,  France        04-­‐Dec-­‐13   30  
  • 27. Cloud-Enabled Computation Workflows #OIA4        Paris,  France        04-­‐Dec-­‐13   31  
  • 28. CLIENT-­‐SIDE   SERVER-­‐SIDE   External   ApplicaGon   Taverna   Workbench   Clinical   Researcher   Taverna   Server   Workflow   Manager  API   VPH-­‐Share  plugin   VPH-­‐Share  plugin   Web  services   …   Cloud   Façade   GIMIAS  CLPs   VPH-­‐Share   Workflow   Taverna   On-­‐line   VPH-­‐Share  plugin   …   Web  services   Web-­‐based   Remote     Desktop   #OIA4        Paris,  France        04-­‐Dec-­‐13   AS   AS   AS   AS   AS   AS   AS  with     interacGon AS  without     interacGon STORAGE 32  
  • 29. VPH-Share HPC & Cloud Platform #OIA4        Paris,  France        04-­‐Dec-­‐13   33  
  • 30. Scientific Cloud Platform VPH Shar e Clien t ATM Master Interface Atomic Service Manager Atmosphere Cloud Platform Atomic Service Generic Invoker Data Browser Workflow Composer Semantic Services Visualisation Tools Service Registry … Silk, LinQuer Service … LOD Databases Multi-Ontology/ Archetype Search Services Data Buckets (C-DISC, CSV, …) Workflow Registry S P A R Q L D is c o v e B r r y o w s e S r e LD Databases RDB2RDF Service Generic Workflow Documen t Authentication Services libclou d provid er libclou d provid er Schema Crawler Workflow Execution Service Cloud Clients Atomic Service Registry Atomic Service Description Virtual Machine Template Registry Cloud Facade Proxy Controller a r c h Taverna Server MAFEventBus Monitoring Controller Atomic Service Deployment Wizard Database Services Integration Points AHE Services API AHE Runtime … Database 1 Query Services (SPARQL & SQL) Database n Query Services (SPARQL & SQL) Databases (SQLServer, …) … External Structured Data Providers REST API & HTML Service (Ruby) Sinatra & Passenger AMS Manag er (Java) OSGi bundle s Apach e Karaf … Database 2 Query Services (SPARQL & SQL) … Domain Model (Ruby) App State Objec t Scheduler / Optimizer Individual Relational Databases Mo ng oD Atmosphere Internal B Registry Allocation Management Service Data Publishing Suite (GUI) VoID VoID Document Document Database VoID Services AHE Engine App Regis try JBP M Workf low & Main Logic AHE Database Hibernate ORM Security Module Storage Module Data Reliability & Integrity Services External Data Storage Data Infrastructure Services Connector Module External HPC Platform Load Balancer Extension Points H S S A P t High PerformanceExecution Engine (AHE) R R e C U e C ri E n g ASIProxy Dashboard NOVA API Access & Control Frontend Network Worker Web Service Security Agent Compute Worker Web Service Wrapper Soaplab2, CXF, soap4r Remote Access Service Manager Driver VPH-Share Tool / App Hypervisor LOBCDER Federated Storage Access Q ue ue S ch ed ul er Request Manager Im ag es Virtual Resource System Cloud Storage Driver Data Volume Raw Operating System (Linux) Root Volume Atomic Service Instance Contents PSLoade r External Cloud Data Storage Connection Module Monitoring System Monitoring Agent (Munin) Data Resource Catalog Object Storage (Swift) P r A o c C c o x n y o u t O a n b t i j n e e c r t LOBCDER Data Federation Middleware Private Compute & Storage Cloud (OpenStack Example) Atmosphere Cloud Platform #OIA4        Paris,  France        04-­‐Dec-­‐13   34  
  • 31. Platform Architecture Admin   Modules  available  in  first  prototype   Developer   Data  and  Compute  Cloud  Planorm   ScienGst   Deployed  by  AMS  on  available  resources   as  required  by  WF  mgmt  or  generic  AS   invoker   VPH-­‐Share  Master  UI   AS  mgmt.  interface   Atomic  Service  Instances   VPH-Share Tool / App. AM   Service   Generic  AS  invoker   VM   templates   Workflow  descripGon   and  execuGon   Security  mgmt.  interface   ComputaGon   UI  extensions   DRI   Service   Data  mgmt.  interface   AS  images   101101   101101   011010   101101   011010   011010   111011   111011   111011   Available   Managed   cloud   datasets   infrastructure   Atmosphere  persistence   layer  (internal  registry)   Raw OS (Linux variant) LOB Federated storage access Web Service cmd. wrapper Web  Service  security  agent   Generic VNC server Generic  data  retrieval   Data  mgmt.   UI  extensions   Security   framework   LOB  federated   storage  access   Cloud  stack   clients   HPC  resource   client/backend   Custom  AS  client   Remote  access  to   Atomic  Svc.  UIs   #OIA4        Paris,  France        04-­‐Dec-­‐13   Physical   resources   35  
  • 32. Cloud Platform Architecture •  Developer   Admin   ScienGst   The platform provides a set of APIs for the VPH-Share Master Interface and other applications, enabling Atomic Services to be developed. VPH-­‐Share  Core  Services  Host   Cloud  Facade   (secure   RESTful  API  )   VPH-­‐Share  Master  Int.   Cloud  Manager   Atmosphere   Management   Service  (AMS)   Cloud  stack   plugins   (JClouds)   Development  Mode   Atmosphere   Internal   Registry  (AIR)   Generic  Invoker   Workflow  management                                ComputaGonal  Cloud  Site   External  applicaGon   Cloud  Facade  client   Customized  applicaGons  may   directly  interface  the  Cloud   Facade  via  its  RESTful  APIs   #OIA4        Paris,  France        04-­‐Dec-­‐13   Head   Node   Image  store   (Glance)   Worker   Worker   Worker   Worker   Node   Node   Node   Node   Worker   Worker   Worker   Worker   Node   Node   Node   Node   36  
  • 33. Accessible HPC Execution Platform —  Provides  virtualized  access  to  high  performance  execuGon  environments   —  Seamlessly  provides  access  to  high  performance  compuGng  to  workflows  that   require  more  computaGonal  power  than  clouds  can  provide   —  Deploys  and  extends  the  ApplicaGon  HosGng  Environment  –  provides  a  set  of  web   services  to  start  and  control  applicaGons  on  HPC  resources   Invoke  the  Web  Service  API  of   AHE  to  delegate  computaGon   to  the  grid   ApplicaGon   -­‐-­‐  or  -­‐-­‐   Present  security  token   (obtained  from  authenGcaGon   service)   ApplicaGon  HosGng  Environment   Auxiliary  component  of  the  cloud  planorm,  responsible  for  managing  access  to  tradiGonal  (grid-­‐based)  high   performance  compuGng  environments.  Provides  a  Web  Service  interface  for  clients.   AHE  Web  Services   (RESTlets)   GridFTP   WebDAV   Tomcat  container   Workflow   environment   -­‐-­‐  or  -­‐-­‐   End  user   QCG   CompuGng   Job  Submission  Service   (OGSA  BES  /  Globus   GRAM)   RealityGrid  SWS   User   access   layer   Resource   client   layer   Delegate  credenGals,  instanGate  compuGng  tasks,  poll  for   execuGon  status  and  retrieve  results  on  behalf  of  the  client   Grid  resources  running  Local  Resource  Manager   (PBS,  SGE,  Loadleveler  etc.)   #OIA4        Paris,  France        04-­‐Dec-­‐13   37  
  • 34. Unstructured Data Storage Ticket  validaGon  service   LOBCDER  host   (149.156.10.143)   Auth     service   WebDAV  servlet   REST-­‐interface   LOBCDER  service  backend   Core  component  host   (vph.cyfronet.pl)   GUI-­‐based  access   Resource  factory   Storage   driver   Storage   driver   EncrypGon   Resource   keys   (SWIFT)   catalogue   Atomic  Service  Instance   (10.100.x.x)   Mounted  on  local  FS   (e.g.  via  davfs2)   Amazon  S3   Storage   backend   •  •  •  SWIFT   storage   backend   Generic  WebDAV  client   Master  Interface  component   Data  Manager   Portlet   (VPH-­‐Share   Master  Interface   component)   Service  payload   (VPH-­‐Share   applicaGon   component)   External  host   VPH-­‐Share  federated  data  storage  module  (LOBCDER)  enables  data  sharing  in  the  context  of  VPH-­‐ Share  applicaGons   The  module  is  capable  of  interfacing  various  types  of  storage  resources  and  supports  SWIFT  cloud   storage  (support  for  Amazon  S3  is  under  development)   LOBCDER  exposes  a  WebDAV  interface  and  can  be  accessed  by  any  DAV-­‐compliant  client.  It  can  also   be  mounted  as  a  component  of  the  local  client  filesystem  using  any  DAV-­‐to-­‐FS  driver  (such  as  davfs2).     #OIA4        Paris,  France        04-­‐Dec-­‐13   38  
  • 35. Platform by Numbers •  4 Data centers –  CYFRONET, Krakow –  UoS, Sheffield –  STH, Sheffield –  UNV, Vienna •  •  •  •  •  •  80+ Cloud Hosts 100+ VMs baseline, 331 VMs Peak 50TB+ Data Storage 75+ Scientific Applications 25+ Scientific Workflows €70k Public Cloud Burst Funds #OIA4        Paris,  France        04-­‐Dec-­‐13   39  
  • 36. Elephant in the Room •  Security & Privacy •  Legislation & Ethics •  Training •  Long Tail of Physicians and Care-takers •  P4 Medicine Journey •  Predictive •  Preventative •  Personalised •  Participatory #OIA4        Paris,  France        04-­‐Dec-­‐13   40  
  • 37. #OIA4        Paris,  France        04-­‐Dec-­‐13   41  
  • 38. <Thank  You!>   Dr Susheel Varma <susheel.varma@sheffield.ac.uk> VPH-Share - Scientific Workflows Coordinator Department of Cardiovascular Science The Medical School, The University of Sheffield Beech Hill Road, Sheffield S10 2RX UK T: +44 (0)114 271 2863 #OIA4        04-­‐Dec-­‐13   42  
  • 39. @neurIST Simulation Workflow •  •  •  •  •  @neurIST- Integrated Biomedical Informatics for the Management of Cerebral Aneurysms (http://www.aneurist.org) IST project funded within the EU FP6 Duration: 2006-2010 Budget: 17M€ Participants: 28 institutions –  –  –  Public and private, Industry, hospitals, academia, 12 European countries •  External collaborators: from USA, New Zealand, Japan) •  @neurIST main objective: @neurIST will transform the management of cerebral aneurysms by providing new insights, personalized risk assessment, and methods for the design of improved medical devices and treatment protocols.
  • 40. @neurIST Framework VPH-­‐Share  
  • 41. Two Workflows from @neurIST Selec(ng  Boundary   Condi(ons Volume   Rendering GAR   Segmenta(on Skeletoniza(on Input:  3D  image Output:  3D  image DescripGon:  aneurysm  and   vessels  VisualisaGon Input:  Image,ROI Output:  surface  mesh DescripGon:  vessels  and   aneurysm  extracGon CFD  preprocessor Flow  Simula(on             Input:  xml,  surface  mesh Output:  surface  mesh,  ccl DescripGon:  Defines   hemodynamic  model Neck  Selec(on Input:  DICOM Output:  3D  image DescripGon:  Converts  a   DICOM  image  to  VTK   image Input:  wall  shear  stress Output:  .csv  file DescripGon:  computes   hemodynamic  descriptors     Input:  surface  mesh. Output:  skeleton. DescripGon:  necessary  to   set  the  boundary   condiGons DICOM Input:  surface  mesh Output:  volumetric  mesh DescripGon:  creates  a   volumetric  mesh  of  the   selected  geometry Input:  surface,  1D  model Output:  xml,  vtk DescripGon:  boundary   condiGons  for  CFD Flow  Simula(on   post-­‐processing                     Volumetric  Mesh Input:  volumetric  mesh,  ccl Output:  wall  shear  stress     map DescripGon:  solves  flow   equaGons     Input:  surface  mesh Output:  surface  mesh DescripGon:  aneurysm   neck  surface  and  dome   selecGon Bounding  Box     Input:  3D  image Output:  ROI DescripGon:  volume   selecGon Mesh  Edi(ng     Input:  surface  mesh Output:    surface  mesh DescripGon:  clipping   vessels,  cleaning  surface   (cell  removal,  closing   holes,  smoothing…) Morphology   Descriptors     Aneurysm   isola(on     Input:  surface  mesh Output:  surface  mesh DescripGon:  aneurysm   isolaGon Input:  surface  mesh Output:  xml,  vtk   DescripGon:  surface,   depth…  and  ZMI   calculaGon Morphological   analysis   GIMIAS   Hemodynamic   analysis   ANSYS  (ICEM)   Common   opera(ons   @neuFuse   ANSYS  (CFX)   Manual  interacGon  
  • 42. Morphological Workflow •  Morphological, hemodynamic and structural analyses have been linked to aneurysm genesis, growth and rupture. •  Evidence indicating differences in morphology and flow between ruptured and unruptured aneurysms have been shown for reduced patient cohorts. •  Structural wall mechanics has been used to justify the growth and remodelling happening at the aneurysm level. +   images   Morphological analysis Morphological   descriptors   +  BC,     material   Haemodynamic analysis Hemodynamic   descriptors   +  BC,     material   Structural analysis Structural  descriptors   Confidence  in     physical  measures   +   Direct     diagnos6c  power   PracGcally,   morphological   characterizaGons    might   currently  have  the   highest  predic(ve   capabili(es  with  respect   to  the  other  analyses.  
  • 43. Implementation in VPH-Share The @neurIST morphological workflow specification in Taverna:
  • 44. GAR Segmentation A  surface  mesh  represenGng  the  vascular  geometry  is  required  to   perform  the  @neurIST  morphological  and  hemodynamic  analyses   •  •  An automatic segmentation method based on Geodesic Active Regions (GAR) and an image standardization technique is used The method: –  eliminates most of the dependency on the operator, and on the specific imaging protocols and equipment used. –  is able to segment (extract the surface mesh) a region of interest with a size of 2563 voxels in 17+4 min (avg+std dev) on a PC (Intel quad-core, 2.4 GHz, 4GB memory). Medical  image   from  imaging  equipment   Surface  mesh   a<er  segmenta6on   Hernandez,  M.  et  al.  2007  Non-­‐parametric  geodesic  acGve  regions:  method  and  evaluaGon  for  cerebral  aneurysms  segmentaGon  in  3DRA  and  CTA.  Med.  Image  Anal.  11,  224–241.     Bogunovic,  H.  et  al.  2011  Automated  segmentaGon  of  cerebral  vasculature  with  aneurysms  in  3DRA  and  TOF  MRA  using  geodesic  acGve  regions:  an  evaluaGon  study.  Med.  Phys.  38,  210–222.  
  • 45. Mesh Editing A  surface  mesh  represenGng  the  vascular  geometry  is  required  to   perform  the  @neurIST  morphological  and  hemodynamic  analyses   •  The surface mesh obtained after the GAR segmentation needs to be manually manipulated by an operator to either remove or correct: –  some of the artifacts not belonging to the cerebral vasculature –  those parts of the geometry not relevant for the subsequent analyses (morphological or hemodynamic). P   O   Kissing  vessels   Surface  mesh   a<er  segmenta6on   Remove  cells   Close  holes   Surface  mesh  a<er  correc6on     and  aneurysm  isola6on  
  • 46. Several  morphological  measurements  are  based  on  the  aneurysm   sac,  to  idenGfy  it,  the  aneurysm  neck  is  required   •  User is asked to manually delineate the neck •  Unfortunately, automatic methods are not an option because there are: –  unacceptable differences in Neck  DelineaGon   cases among a large number of methods and manual selection of experts –  too complex vascular topologies where there is not even an agreement among experts about where the aneurysm neck is A u t o m a t   ic   vs   Manual  delinea6on   Surface  mesh  a<er  correc6on     and  aneurysm  isola6on   Too  large  differences  in  performance  and  lack  of  consensus   Too  complex  vascular  topologies   Manual  aneurysm     neck  selec6on  
  • 47. Morphological Descriptors Morphological  descriptors  of  various  complexity  are  automaGcally   extracted  and  stored  for  their  subsequent  analysis   •  Among the wide variety of existing morphological descriptors, @neurIST chose to compute: –  Basic size indices describing the aneurysm sac: aspect ratio, non-sphericity index, aneurysm volume and surface area. –  Complex indices describing the sac and a portion of the surrounding vasculature: Zernike moment invariants (volume and surface-based). depth   Basic  size  indices  describing  aneurysm  sac   neck   Complex  indices  (Zernike  moment  invariants)   Manual  aneurysm     neck  selec6on   @neurIST     morphological    descriptors   Ujiie,  H.  et  al.  1999  Effects  of  size  and  shape  (aspect  raGo).  Neurosurgery  45,  119–130.  /  Ma,  B.,  Harbaugh,  R.  E.  &  Raghavan,  M.  L.  2004  Three-­‐dimensional  geometrical  characterizaGon  of  cerebral  aneurysms.  Ann.  Biomed. Eng.  32,  264–273.  /  Raghavan,  M.  L.,  Ma,  B.  &  Harbaugh,  R.  E.  2005  QuanGfied  aneurysm  shape  and  rupture  risk.  J.  Neurosurg.  102,  355–362.   Pozo,  J.  M.  et  al.  2011  Efficient  3D  Geometric  and  Zernike  moments  computaGon  from  unstructured  surface  meshes.  IEEE  Trans.  Pagern  Anal.  Machine  Intell.  33,  471–484.    
  • 48. Morphological Analysis Workflow depth   Basic  size  indices  describing  aneurysm  sac   Medical  image   from  imaging  equipment   neck   @neurIST     morphological    descriptors   Complex  indices  (Zernike  moment  invariants)  
  • 49. @neurIST: Morphology Results