HealthGrid Infrastructures and Applications

1. HealthGrid Infrastructures and Applications Vicente Hernández Technical University of Valencia Institute of Applications of Advanced Information and Communications Technologies- ITACA

2. Contents • Introduction and Objectives. • Problems and Needs in eHealth. • The Grid as an Enabling Technology. • Current Actions in HealthGrids. • Conclusions. Demo Session - Biomed - CDSS

3. Terms and Concepts What do we Mean Here by “eHealth” and “HealthGrid”? Demo Session - Biomed - CDSS

4. Terms and Concepts: eHealth • eHealth Deals with Using Information and Communication Technologies to Develop an Intelligent Environment that • Enables Ubiquitous Management of Citizens’ Health Status, • Assists Health Professionals in Coping with some Major Challenges, • or Integrates the Advances in Health Knowledge into Clinical Practice. • Health Term is Considered in a Broad Sense. Demo Session - Biomed - CDSS

5. Terms and Concepts: HealthGrid • HealthGrids are Grid Services or Middleware Components that Deal with the Specific Problems that Medical Data Processing Involve. • Resources in HealthGrids are Databases, Computing Power, Medical Expertise and Even Medical Devices. • Health Grids Aim at Assisting Epidemiology and Individualised Healthcare: • Integrating Large Databases and Extracting Knowledge. • Execute Complex Simulations on Biomedical Models. • Process Large Genomic Databases. • Securely Exchange Medical Data and Share Applications for its Processing. Demo Session - Biomed - CDSS

6. What do Physicians Need? Problems and Needs in eHealth Demo Session - Biomed - CDSS

7. Problems and Needs in eHealth • Ubiquitous, Quick and Secure Transference of Information. • Medical Information is: • Large, Increasing in Size and Relevant on the Long-term. • Medical Data is Critically Confidential. • Legal Regulations at National Level Difficult the Integration of Large Repositories of Personal Data. • Consolidated Access • Interconnection of the Different Isles of Information (HIS, RIS, LIS, PACS, Primary Care IS, …). • Solve Incompatibilities on Data Format. • Data are Heterogeneous in Format and Nature. • Potentially Incomparable (Acquisition, Post-processing). Demo Session - Biomed - CDSS

8. Problems and Needs in eHealth • Large Computing Power is Needed • Medical Information is Huge. • Information Processing Requires Large Computing Resources. • Pervasive Access and Fault Tolerance • Medical Healthcare is Performed All Over the Clock, 7 Days a Week. • Fault Tolerance to All Other Critical Resources (Water, Light, Heating) is Considered. • New Applications • Computer-Aided Diagnosis. • Patient-Customized Therapy. • Large-scale Knowledge Discovery. • Large Scale Post-Genomics and Proteomics. Demo Session - Biomed - CDSS

9. The Grid as an Enabling Technology What are the Strengths of Health Grids? Demo Session - Biomed - CDSS

10. The Grid as an Enabling Technology • Driving Factors • Structure • Networks of Centres Cooperating in one Aim. • Staff Sharing Experiences and Even Exchanging Personnel. • Distributed Architecture of Grid Fits Healthcare Provision Structure. • The Concept of Virtual Organisation is Crucial in Grid and perfectly matches the Structure of Healthcare Users. • Infrastructure • High-Bandwidth Networks are Available Among Public and Private Healthcare Centres. • Open-minded • Used to Research and Advanced IT. • Concern on Patient’s Satisfaction. Demo Session - Biomed - CDSS

11. The Grid as an Enabling Technology • Driving Factors • Technological • Security is a Basic Technology on the Concept of Grid. • Interoperability and Resource Sharing are the main Aims of the Grid Concept. • Filters can be Executed Locally to Transform Data into an Homogeneous Format. • Local Administration is Preserved in the Grid. • Low Requirements on the User Side is Also Adequate. • Robustness with Data and Service Replication. • Economy • Service-Oriented Business is Optimal for Healthcare. • Better Use of Resources and Scalable Costs. • Free Maintenance Tasks. Demo Session - Biomed - CDSS

12. Grid for Health Today How are HealthGrids Initiatives Now? Demo Session - Biomed - CDSS

13. EGEE Project • Main EGEE Aim is to Deploy a Production Grid Infrastructure at International Level for Supporting eScience. • Applications on the EGEE Grid are Oriented to: • High Energy Physics. • Biomedicine and Medical IT. • Radiotheraphy Simulation: GATE. • Clinical Decision Support System: CDSS. • Biocomputing Portal and Molecular Docking and Analysis: GPS@, GridGRAMM, GROCK, XMIPP. • Medical Imaging: SiMRI 3D, gPTM3D, Pharmacokinetics. • Other Application Areas. • Earth Observation, Geology, Astrophysics. Enabling Grids for E-sciencEs Demo Session - Biomed - CDSS

14. The HealthGrid Association • A Non-Profit International Organisation Devoted: • To Contribute to the Structuring of the European Research Area for Health. • To Create Partnerships of Benefit to Both Higher Education and Scientific Research in the Field of the Health in its Broadest Sense, both within Europe and in the Rest of the World. • Coordinator of a White Paper for HealthGrids Available onhttp://www.healthgrid.org/download.php. • Organising a Yearly Conference on HealthGrids (last edition was in the Univ. of Oxford). Demo Session - Biomed - CDSS

15. Grid for Health Today How are Medical Grid Applications Now? Demo Session - Biomed - CDSS

16. Grid for Health Today • Health Grid Application Areas • Medical Imaging • Archive Federation (BIRN, GRID-IT, EMBRACE). • Mammography (NDMA, MAMMOGRID, eDIAMOND, GPCALMA). • Image Processing (DataGrid, EGEE-NA4). • Therapy • Radiotherapy Simulation (GATE, GEMSS-RADPT). • Pharmacological Simulation (GEMSS-Cophit). Demo Session - Biomed - CDSS

17. Grid for Health Today • Health Grid Application Areas • Biocomputation • Protein Simulation and Genetic Ontology. (BioGRID, GPS@, INFOGENMED, GenoGrid, myGRID…).. • Biomedical Simulation and Surgery Planning • Vascular. (CROSSGRID, GEMSS-BloodSim). • Maxillo-Facial. (GEMSS). • Cardiac Activity. (gCAMAEC). Demo Session - Biomed - CDSS

18. HealthGrid Activities-TUV Activities of the Techn. Univ. of Valencia (TUV) in the HealthGrid Area Demo Session - Biomed - CDSS

19. Data Grids • Storage and Processing of Medical Images on the Grid. • Virtualization of a Distributed Storage for Medical Images. • Integration of Components that Post-Processes (Rendering, Segmentation, Co-Registration) • Semantic Integration of Radiological Reports. • Searching and Progressive Transmission of Data. • Following Current Standards (DICOM, OGSA, WSRF). Demo Session - Biomed - CDSS

20. Peer-to-Peer Environments • A Peer-to-Peer Environment to Share Medical Images and Diagnostic Reports Providing Content-Based Searching. • The Objective is to Ease the Collection of Cases, Especially Those Regarding Infrequent Diseases or to Reach a Sufficiently Large Sample for Epidemiological Studies. • Although the Studies are Available on the Different Medical Centres, There are no Means to Access and Share The Information. • The Tools Enables Sharing Individual Studies, Joining the Own Resources of Each User. • It Implements Authentication, Automatic Anonimization, Distributed Searching, Progressive Transmission and User and Diagnoses Ranking. Demo Session - Biomed - CDSS

21. High Performance Post Processing • Rendering of Very Large Medical Images with Corporate Grids • Visible Human Project Dataset (1500 Slices). • The Volumetric Projection has a Large Requirement of CPU, but Also of Local Memory. • Grid Technology Enables Sharing the Resources (Memory and Processing Power) of the Computers Connected to a Network. • Co-Registration of Medical Images in the Grid • Distributed Storage of Abdominal MRI Volumes and Co-Registration using Deformable Methods. • Oriented to the Study of Pharmacokinetics. • Basic Grid Gain Per Study of Above 12, But Raising above 80 if Enough Resources. Demo Session - Biomed - CDSS

22. Clinical Decision Support System • Knowledge Management for the Diagnostic Support and the Epidemiology Analysis. • The Classification Engines are Being Implemented and Trained by External Multidisciplinary Research Groups Participating in Different Projects. • Target Areas in Work are Soft Tissue Tumours and Anaemia Classification. • The Grid Provides: • Support for Training and Classification of Databases. • Dynamic Cataloguing of the Available Classification Services. • The Application Runs on the EGEE Grid. << Siemens Best Paper Award of Healthgrid 2005 >> Demo Session - Biomed - CDSS

23. Drug Epidemiology • Development of Efficiency and Efficacy Studies of Treatments for Common Diseases in a Complete Population. • The Valencian Community Records all the Treatment and Diagnosis Actions Performed at Primary Care. • The Microbiological Surveillance Network Records the Microbiological Results of Laboratory Analysis. • The Knowledge of This Huge Database (4 Million Record per Day) is Not Exploited. • Performing Efficiency Studies will Provide a Real View of the Quality of Treatments and will Reduce Costs. • Tools • Data Mining, Knowledge Extraction Methods (Neural Networks, Genetic Algorithms, Probabilistic Classifiers,…). • Large Computational Cost for Training the Systems. • Work Started in Tuberculosis, Extendable to Other Pathologies. Demo Session - Biomed - CDSS

24. Conclusions Final Thoughts Demo Session - Biomed - CDSS

25. Conclusions • HealthGrids Must Pay Special Attention to Hospitals, were Data is Located. • A High Degree of Coordination is Needed. • Successful Applications Need the Commitment and Guidance of Medical Users. • To Foster the Development of HealthGrids Widely Usable Applications Acting as Success Stories are Needed. • Medical Imaging and Biocomputation are Application Areas in Health with a Large Chance of Success at Short/Medium Term. Demo Session - Biomed - CDSS

26. More Information Vicente Hernández Universidad Politécnica de Valencia Camino de Vera s/n 46022 Valencia, Spain Tel: +34-963877356 Fax. +34-963877359 E-mail: vhernand@dsic.upv.es Demo Session - Biomed - CDSS