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Data Explosion in Medical Imaging

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A talk at The Fifth Elephant - a confrence on Big Data in Bangalore - July 2012

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Data Explosion in Medical Imaging

  1. 1. Data Explosion in Medical ImagingShourya SarcarSr. Engineering ManagerGE Healthcare@shouryasarcar
  2. 2. 1820Paris Rene Laennec , "immediate" auscultation with the unaided ear
  3. 3. 2010Handheld digital ultrasound stethoscope
  4. 4. Imaging 101
  5. 5. Digital X-Ray
  6. 6. Computed TomographyX-Ray technology, but in 3D !
  7. 7. Magnetic Resonance Imaging • Principal of magnetic spin • Great for soft tissue imaging
  8. 8. Positron Emission Tomography • Functional imaging • Radioactive bio-marker binds to cancerous cell PET-CT • Capture positron decay with a scintillation detector
  9. 9. Basic Imaging Chain The fancier the DAS, The larger the dataDigital Acquisition System Image ReconstructionAdd Patient Information
  10. 10. How BIG is that Image Data ? Header Primarily “Text” Few KB Pixel 1024 x 1024 16 bits per pixel 2 MB (tchah ! That’s not much)
  11. 11. They don’t come alone ! Header Header Header Pixel Header Pixel Header Pixel Header Pixel Header Pixel Pixel Pixel Images come in “Stacks”, a.k.a Volumes Series Slices
  12. 12. How BIG is that Image Data ? Full body PET CT Cardiac fMRIImages / set 600 3000 20000Size of 1 set 1.2 GB 6 GB 40 GBNo. of sets (typical) 4 6 8Exam Size 9 GB 36 GB 300 GB Sizes are approximations
  13. 13. How do we take that data home ? …and who does it belong to ?
  14. 14. To store and share digital data, we need a format and a protocol
  15. 15. And there was none until 1993 ! “And the whole earth was of one language and of one speech” ~ Genesis 11
  16. 16. DICOM:Digital Information andCommunication in Medicine 1985 1988 1993ACR-NEMA 1.0 ACR-NEMA 2.0 DICOM 3.0
  17. 17. DICOM Scope Medical Informatics Patient Bedside ... Monitoring Administrative HIS/RIS Lab Data ... Diagnostic Imaging Scope of DICOM
  18. 18. DICOM Standard 20 PS 3.1: PS 3.2: PS 3.3: Introduction and Overview Conformance Information Object Definitions parts PS 3.4: PS 3.5: Service Class Specifications Data Structure and Encoding PS 3.6: Data Dictionary PS 3.7: Message Exchange PS 3.8: Network Communication Support for Message Exchange + PS 3.9: Point-to-Point Communication Support for Message Exchange (Retired) PS 3.10: Media Storage and File Format for Data Interchange PS 3.11: Media Storage Application Profiles PS 3.12: Storage Functions and Media Formats for Data Interchange PS 3.13: Print Management Point-to-Point Communication Support (Retired) PS 3.14: Grayscale Standard Display Function PS 3.15: Security Profiles 161 PS 3.16: Content Mapping Resource PS 3.17: Explanatory Information PS 3.18: Web Access to DICOM Persistent Objectssupplements PS 3.19: Application Hosting PS 3.20: Transformation of DICOM to and from HL7 standards
  19. 19. DICOM Network:where is it in the network stack? Medical Imaging Application OSI upper layer Service boundary DICOM Application Entity OSI Association Control DICOM Service Element (ACSE) Upper Level Protocol OSI Presentation Kernel for TCP/IP OSI Session Kernel TCP/IP OSI Transport OSI stack TCP stack OSI Network IP LLC Standard Network Physical Layer (i.e. Ethernet, FDDI, ISDN, etc.)
  20. 20. The Stack has Evolved !OnceUpon aTime
  21. 21. How much disk space is needed for cardiac screening of Bangalore ? Back of the envelope calculations
  22. 22. Population of Bangalore : 7,000,000Cardiac Screening : 50%HDD / CT Cardiac : 20 GBI need some space : 70 PB
  23. 23. Some more size estimates Christian Medical College Vellore 60 TB 0.5 million exams / yr Clalit Healthcare Services, 250 TB 14-hospital network in Israel 4.5 million exams/yr (annually) Est. imaging data size in US – 2014 100 PBEst. imaging data size globally – 2020 35 ZB
  24. 24. Challenges of Large Imaging Data Archival Search Transfer
  25. 25. Lawmakers demand storage guaranteeMoms:“25 years after the birth of the last child”Mentally disabled:“20 years after the last contact or 8 yearsafter the patients death”Children:“Until the patient is 25” Storage Commitment built into DICOM
  26. 26. Huge Capacity requirements Huge CapEx Unpredictable TCO Hardware technology obso Space Data-center grade infra
  27. 27. Finding the needle in the haystack Simple search is a soft problem Index only the meta-data DICOM loves SQL
  28. 28. SQL Tables Relevant header infoHeader Header HeaderPixel Header Pixel Header Pixel Header Pixel Header Pixel Pixel Pixel Complete File Flat Files Power of SQL queries Insertion is fast, Read is fast Replicate tables Memory-mapped IO Better disaster recovery
  29. 29. Why move the data ?• Offline storage [Store/Fetch]• Reporting• Teleradiology / Remote reporting
  30. 30. Remote RadiologistOnsite Radiologist Internet Outpatient Imaging Center
  31. 31. Why move the data ?• Offline storage [Store/Fetch]• Reporting• Teleradiology / Remote reporting
  32. 32. Challenges of DICOM• DICOM is based on TCP/IP • Slow over large number of hops • FileCatalyst, CISCO WAAS• DICOM compression is not adequate • Lossy, Loseless• DICOM is not efficient on fault-tolerance • Dated retry mechanism, transmit in sets/series, not files
  33. 33. FOSS DICOM Tools and Images Viewers API OsiriX for MacLanguage Toolkit Santesoft for WinC/C++ GDCM, DCMTK Kradview for LinuxJava Pixel, dmc4chePerl DICOM.pmRuby Ruby DICOM Public DatasetsPython pydicomPHP Nanodicom ftp://medical.nema.org/medical/dicom/DataSets/C# DICOM# http://www.barre.nom.fr/medical/samples/

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