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The MammoGrid Project

The MammoGrid Project. - an EU FP5 funded project On behalf of the MammoGrid Consortium : CERN, Geneva; Mirada Solutions, Oxford; Universities of Oxford, Pisa, Sassari, West of England; University Hospitals, Cambridge (Addenbrooke’s) & Udine (Policlinico Universitario)

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The MammoGrid Project

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  1. The MammoGrid Project - an EU FP5 funded project On behalf of the MammoGrid Consortium: CERN, Geneva; Mirada Solutions, Oxford; Universities of Oxford, Pisa, Sassari, West of England; University Hospitals, Cambridge (Addenbrooke’s) & Udine (Policlinico Universitario) Tony Solomonides, UWE

  2. Key Staff University of Cambridge (Addenbrooke’s Hospital) Ruth Warren (Radiology) CERN Roberto Amendolia (Project Leader), Predrag Buncic (AliEn), Josè Galvez Mirada Solutions Ralph Highnam (SMFTM), David Schottlander (MAS) University of Oxford Mike Brady, Chris Tromans (Quality Control) University of Pisa Pasquale Delogu, Evelina Fantacci (CADe) University of Sassari Ubaldo Botigli, Piernicola Oliva (CADe) University of West of England, Bristol Florida Estrella, Tamas Hauer, David Manset, Dmitri Rogulin (DICOM, Grid) Richard McClatchey (Technical Director) Mohammed Odeh (User Requirements) Tony Solomonides (User Requirements, Database, Dissemination) Policlinico Universitario di Universita degli Studi di Udine Massimo Bazzocchi, Chiara Del Frate (Radiology) XIX NEC 15-20 September 2003

  3. Contents • Background & Motivation • Breast screening programmes • Mammography and its problems • Technologies & Grids • Mammographic tools • CRISTAL • AliEn • MammoGrid • Objectives • Methods • Conclusions & questions XIX NEC 15-20 September 2003

  4. Breast Cancer Screening • Breast cancer is a major problem: • 12% lifetime risk of breast cancer • 19% of cancer deaths are due to breast cancer • 24% of all cancer cases are breast cancers • in EU & USA 350,000 are diagnosed and 115,000 die annually • but 73% of diagnosed cases survive 5 years or more • Early diagnosis improves prognosis XIX NEC 15-20 September 2003

  5. Breast Cancer Screening - EU • UK: covers women 50 – 64; established in 1987; 1.3m women screened annually at 92 centres (230 radiologists) • Sweden, Finland, The Netherlands, Ireland, France and Germany have or are about to establish national programmes • Italy: depends on where you live; expertise and areas covered by screening programmes do not necessarily correlate • Variable availability and coverage in other countries XIX NEC 15-20 September 2003

  6. Breast Cancer Screening - UK • Low tech, ‘rapid, high-throughput’ screening • Basic frequency every three years • Ideally, a full ‘series’ taken at screening consists of two images (cranio-caudal and medio-lateral oblique) for each breast – four in all • Historically, only two CC images taken • A radiologist may have 40 seconds to study the series • A study in 2000 estimates a 6.4% contribution to reduced mortality to the screening programme; better treatments account for 14.9% • More ‘interval cancers’ than anticipated • Pressure is mounting to begin screening every 2 years XIX NEC 15-20 September 2003

  7. Breast Cancer Screening - Problems • Sensitivity and specificity – i.e. percentages of false negatives and false positives – are both unacceptable • In the US, 80% of biopsies are benign – error on the side of caution • A combination of computer-aided detection and radiologist screening improve performance significantly • There is a world-wide shortage of trained radiologists and radiographers (radiologic technicians) • The work is perceived as ‘boring but risky’; in US 12% of malpractice lawsuits are against radiologists • Over 20% of films are practically unavailable for re-use or comparison – misfiled, in transit or lost XIX NEC 15-20 September 2003

  8. Mammography - Problems • Image quality (brightness/visibility and contrast/distinction) are affected by tube kVp and mAs, screen and film characteristics and automatic exposure control • The interpretation of images is difficult, there are issues both about training and about experience • There are ‘good practice’ guidelines, but radiographers have some latitude in the decisions they make • In both UK and Italy quality control issues have arisen • Failure to record settings • Inconsistency of settings • Unusable images • MammoGrid is concerned with film-screen systems; the move to all-digital mammography is slow XIX NEC 15-20 September 2003

  9. What is MammoGrid? • EU project to prefigure a pan-European distributed databaseof mammographicimages using GRID Technologies. • Aim: To provide a demonstrator for use in epidemiological studies, quality control and validation of computer aided detection algorithms. XIX NEC 15-20 September 2003

  10. MammoGrid Objectives • To evaluate current Grids technologiesand determine the requirements for Grid-compliance in a pan-European mammography database. • To implement the MammoGrid database, using novel Grid-compliant and Federated-Database technologies that will provide improved access to distributed data and will allow rapid deployment of software packages to operate on locally stored information. • To deploy enhanced versions of a standardization systemthat enables comparison of mammograms in terms of intrinsic tissue properties independently of scanner settings, and to explore its place in the context of medical image formats (DICOM). • To develop software tools to automatically extract image information that can be used to performquality controlson the acquisition process of participating centers (e.g. average brightness, contrast). • To develop software tools to automatically extract tissueinformation that can be used to perform clinical studies(e.g. breast density, presence, number and location of micro-calcifications) in order to increase the performance of breast cancer screening programs. • To use the annotated information and the images in the database tobenchmarkthe performance of the software described in points 3, 4 and 5. • To exploit the MammoGrid database and the algorithms to propose initial pan-European quality controls on mammographic acquisition and ultimately to provide a benchmarking system to third party algorithms. XIX NEC 15-20 September 2003

  11. MammoGrid Philosophy • Project concentrates on applying emerging GRID technology rather on developing it. • It plans to implement a ‘lightweight’ (but fully functional) GRID and study its usage in hospitals • It will draw heavily on other Grids projects e.g. DataGrid • It will deliver a prototype federated database of mammograms in hospitals in the UK and Italy • It will provide rapid feedback from the Hospital community • And will inform the next generation of health grids developments XIX NEC 15-20 September 2003

  12. Why a Mammography Database? Improved reliability of screening and early diagnosis requires: • better epidemiological understanding • improved diagnostic tools • enhanced quality control • continuous training • efficient management of data and records. • Need to establish research and training repositories that contain sufficiently large statistical samples: • MammoGrid-EU • NDMA-US • eDIAMonD-UK • GPCalma-Italy XIX NEC 15-20 September 2003

  13. Technologies • Mammography • SMF™ (Mirada) • CADe (CALMA) • DICOM (Medical Imaging Standard) • Distributed computation • CRISTAL Database (CERN/UWE) • AliEn GRID (CERN) XIX NEC 15-20 September 2003

  14. Standard Mammogram Form XIX NEC 15-20 September 2003

  15. The theory of SMF™ • Mirada’s Standard Mammogram Form (SMF™) measures the column of non-fatty tissue between the compression plate and the imaging surface. • SMF algorithm models the physics of image formation, including extrafocal radiation, scatter, grid effects, film-screen characteristics, etc. • The contribution of the imaging system is factored out. • The image is decomposed into fatty tissue and non-fatty tissue. • The new representation gives a numerical value for the amount of non-fatty tissue at any point on the image. XIX NEC 15-20 September 2003

  16. A normalized image XIX NEC 15-20 September 2003

  17. CMS Detector ECAL XIX NEC 15-20 September 2003

  18. ECAL Barrel XIX NEC 15-20 September 2003

  19. ECAL production Bogorodisk(Russia)Crystals LPNHE(France)Alveoli IPN Lyon(France)Electronics SIC (China)Crystals Parts Parts ENEA/INFN (Italy)Modules CERN (Switzerland)Modules & Supermodules • Parts are shipped between centres • Must control overall construction CEA/DAPNIA (France)Monitoring CERN (Switzerland)SM in testbeam CERN (Switzerland)ECAL in CMS XIX NEC 15-20 September 2003

  20. Integration via Meta-Objects CRISTAL 1 concept for integrated product (structure) and process (workflow) description XIX NEC 15-20 September 2003

  21. CRISTAL Object Layers CRISTAL 2 Kernel Architecture XIX NEC 15-20 September 2003

  22. CRISTAL • Data and metadata are versioned asynchronously • Flexibility to cope with and propagate end-users’ changes • Clear separation between object lifecycles of the domain: • Metadata: What has to be done • Data: What is being done • Data and metadata models are largely domain independent • ‘Design patterns’ have emerged from the process of abstraction • Large volume of data can be managed • Large distributed data processes can be tracked XIX NEC 15-20 September 2003

  23. DICOM Information Model XIX NEC 15-20 September 2003

  24. MammoGrid Object Model XIX NEC 15-20 September 2003

  25. Assessment Object Model XIX NEC 15-20 September 2003

  26. The MammoGrid Challenge • Building this repository is not trivial because: • Large numbers of exemplars are required. • Cases must be obtained from many geographically remote locations. • Data itself is large: 2 breasts × 2 views × 4K × 4K pix × 2 bytes = 128Mbyte per patient per visit, 1.5M women per year UK, ~ 200 Terabytes in UK alone, • Acquisition is highly variable, same image may look different depending on machine and parameters. How do you compare? • Patient privacy and data security are key. • Many relevant items of metadata. XIX NEC 15-20 September 2003

  27. GRID Seeking a solution for resource sharing & coordinated problem solving in dynamic, multi-institutional virtual organizations. Data GRID goal: “Enable a geographically distributed community of thousands to pool their resources in order to perform sophisticated, computationally intensive analyses on petabytes of data” XIX NEC 15-20 September 2003

  28. Layered Grid Technologies Data Abstraction • Data mining, visualisation, simulation, problem solving methods/environments … Knowledge Grid • Metadata, middleware, intelligent retrieval, information modelling, warehousing, workflow … Information Grid • Distributed databases, streaming, near-line storage, large objects, access mechanisms, data staging … Data Grid Data Control XIX NEC 15-20 September 2003

  29. AliEn Challenge AliEn = Alice Environment “Can we provide, building on top of available public domain and open source components and standards, a functional distributed computing infrastructure to the community of our users which will remain operational even if underlying technologies keep changing?” Geneva, May 2001 Instead of using Globus toolkit or waiting for DataGRID to deliver re-packaged version of Globus, we decided to try different path and use Web Services and related standards as a backbone of our GRID implementation. XIX NEC 15-20 September 2003

  30. AliEn Services in MammoGrid • Authentication • User’s credentials checked • Resource Broker • Job/algorithm scheduling • Storage Element • Data and file management • File transfer • Scheduled file transfers XIX NEC 15-20 September 2003

  31. Service Oriented Architecture XIX NEC 15-20 September 2003

  32. High Energy Physics vs. MammoGrid • MammoGrid relies heavily on technologies developed primarily in the field of high energy physics. • Similarities • Large number of big files • Files can be sensibly organized in directory tree • Need to replicate and move file copies between sites • Need to execute commands on the node which hosts data locally • Difficulties • Complexity of co-working in medical environment • Lack of trained IT personnel • Confidentiality XIX NEC 15-20 September 2003

  33. A GRID Infrastructure is ideal • To test image-based clinical hypotheses, databases must be: • Populated by large number of cases • Contain large files (1 mammogram ~ 32Mb) • Geographically distributed repositories • Heterogeneous database formats • Need to be accessible to co-workers • Development / validation of medical image analysis solutions demands: • Computationally expensive simulations • Repeated runs for optimal parameter tuning • Statistical test rigs • Remote execution and maintenance • Services (e.g. security) must be system-resident, invisible, generic XIX NEC 15-20 September 2003

  34. Healthcare Institute University Database Hospital Italy Local Query Local Query Local Query Local Query Query Result GRID Clinician’s Workstations Shared meta-data Local Analysis Local Analysis Local Analysis Local Analysis Analysis-specific data • Knowledge is stored alongside data • Active (meta-)objects manage various versions of data and algorithms • Small network bandwidth required Hospital UK Massively distributed data AND distributed analyses Federated System Solution XIX NEC 15-20 September 2003

  35. AliEn Virtual Organization XIX NEC 15-20 September 2003

  36. Multi-level Virtual Organization XIX NEC 15-20 September 2003

  37. Workstations Workstations Mirada WST (‘‘MAS’’) GRID VPN Udine CERN MammoGrid Data MammoGrid Data GridBox High Security Level MammoGrid Data MammoGrid Data GridBox GridBox Cambridge Oxford Mirada WST (‘‘MAS’’) Overall Grids Architecture GridBox XIX NEC 15-20 September 2003

  38. Stack of Grid Services XIX NEC 15-20 September 2003

  39. MammoGrid Transactions XIX NEC 15-20 September 2003

  40. MammoGrid Queries XIX NEC 15-20 September 2003

  41. Main Deliverables and Milestones • User Requirements Specification and Technical System Specification (published) • Packaged medical imaging workstation with interface to GRID, secure GRID box, (October 2003) • Grid compliant SMF software (December 2003) • Prototype GRID-compliant database and information infrastructure (March 2004) • Application software (under development) • Clinical Trials (late 2004 – end of project) XIX NEC 15-20 September 2003

  42. Conclusions and Further Research • Distributed Health informatics is an important application area for Grids technologies – Health Grids • Many similarities with High Energy Physics • MammoGrid user requirements specified, but need rapid feedback from the user community • Effective Grid deployment needed now • Many questions subject to further research: • How to resolve distributed queries ? • What role for meta-data ? • How to maintain secure, reliable data ? • MammoGrid: First results expected late 2003 XIX NEC 15-20 September 2003

  43. The MammoGrid Project Thank you

  44. XIX NEC 15-20 September 2003

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