Pathology Images, DICOM, and LIS/PACS Integration. Harry Solomon, GE Healthcare Co-Chair, DICOM WG-20 / HL7 Imaging Integration WG

Transcription

1 Pathology Images, DICOM, and LIS/PACS Integration, GE Healthcare Co-Chair, DICOM WG-20 / HL7 Imaging Integration WG

2 Disclosure Employee, GE Healthcare 2 Pathology Informatics 2012

3 Topics Brief overview of DICOM DICOM Standard for pathology imaging Specimen information model Whole Slide Imaging Management of pathology imaging LIS / PACS Integrating lab workflow IHE 3 Pathology Informatics 2012

4 OVERVIEW OF DICOM 4 Pathology Informatics 2012

5 DICOM The International Standard for Medical Imaging and related information (NEMA PS3, ISO 12052) Images, waveforms, associated structured data (image processing & display, measurements and assessments) Workflow management in the imaging department Service-based network protocol over TCP/IP; media interchange One of the most widely deployed healthcare messaging standards in world billions of DICOM images in use Available free at dicom.nema.org 5 Pathology Informatics 2012

6 Key features of DICOM Focus on needs of clinical medical imaging Object-oriented, persistent information objects Tagged data elements, binary encoding Client-server network services, service negotiation Image compression by encapsulation of JPEG Conformance Statements 6 Pathology Informatics 2012

7 Persistent Information Objects DICOM image objects include pixels and context information Patient, exam, equipment, protocol, etc. Each object has a globally unique ID (UID) ISO 9834 Object identifier OID in dotted decimal notation Once created, an object is unchangeable (mostly) Can be replicated in multiple systems (with same UID) Annotations are in separate objects May be added later on different system with different context 7 Pathology Informatics 2012

8 The DICOM Information Hierarchy Imaging Context DICOM organizes objects into a hierarchy of information entities Patient, Study, Series, Instance 1:n relationship between entities at higher and lower levels Represents a simplified model of real world concepts and activities Patient Information Study Information Series Information Image (Instance) Information Sufficient for pragmatic needs of routine clinical imaging Study ordered procedure; Series performed protocol step Additional refinement in workflow information model 8 Pathology Informatics 2012

9 DICOM Image Information Object Definition DICOM Composite Information Model Hierarchy Patient Information Patient Module Patient Name Patient ID Patient Sex Patient Birthdate Study Information Series Information Image (Instance) Information Modality Image Module General Image Module General Series Module Multiframe Module General Study Module Image Plane Module Frame of Reference Module VOI LUT Module Patient Study Module Contrast/ Bolus Module General Equipment Module Study Unique ID Accession Number Study Date/Time Study Description Referring MD Image Pixel Module SOP Common Module Rows/Columns Bits per Pixel Photometric 9 Pathology Informatics 2012

10 Part of a DICOM object (0008,0005) CS 30 ISO 2022 IR 13\ISO 2022 IR 87 (0008,0008) CS 22 ORIGINAL\PRIMARY\AXIAL (0008,0016) UI Patient Information Study Information Series Information Image (Instance) Information (0008,0018) UI (0008,0020) DA (0008,0021) DA (0008,0022) DA (0008,0030) TM (0008,0031) TM (0008,0032) TM (0008,0050) SH (0008,0060) CS 2 CT (0008,0070) LO 8 TOSHIBA (0010,0010) PN 8 Doe^John Tags in increasing numeric order Value length always an even number Attributes related to modules and information model levels all jumbled up (0010,0020) LO (7FE0,0010) OW ff ff ff ff 00 0f 4c 4a Pathology Informatics 2012 Items in italics are encoded in binary

11 Image Compression Pixel data can be monochrome, color (RGB or YCbCr), or palette color (monochrome colorized through LUT) Multi-spectral stored in multi-planes; presentation control in development Pixel data can be native DICOM Uncompressed, similar to TIFF Pixel data can be compressed using standard compression schemes, and compressed stream put in pixel data element JPEG, JPEG-LS, JPEG2000 (each lossy or lossless) MPEG2 Run-Length Encoding (Packbits) Private compression schemes can also be used 11 Pathology Informatics 2012

12 DICOM annotation principles Annotations are conveyed in information objects separate from the original image Annotations may be created much after the image acquisition, and in a completely different environment Include their own creation context Multiple annotation objects can reference the same image Selection of an annotation object for display implicitly invokes display of the referenced image 12 Pathology Informatics 2012

13 Annotation types Presentation States display controls, including multi-object blending Structured Reporting image-based measurements and assessments Segmentation classification of ROIs Real World Value Mapping quantitation of pixel values 13 Pathology Informatics 2012

14 DICOM FOR PATHOLOGY IMAGING 14 Pathology Informatics 2012

15 DICOM and Pathology 1994 College of American Pathologists (CAP) organizes the CAP Image Exchange Committee for liaison with DICOM 1999 Adoption of DICOM image formats for Visible Light modalities, including photography, microscopy, and endoscopy 1999 DICOM strategic agreement with CAP to use SNOMED for clinical terminology 2005 Renewed engagement with pathology, establishing WG Publication of DICOM Supplement 122: Specimen Identification 2010 Publication of DICOM Supplement 145: Whole Slide Imaging 15 Pathology Informatics 2012

16 Visible Light (VL) Image Classes VL Photographic Image limited to 64k 2 pixels VL Microscopic Image field of view, cameraon-head, imaging target not necessarily slide VL Slide-Coordinates Microscopic Image adds FOV location on slide VL Whole Slide Microscopy Image tiled, multiple focal planes, multiple color channels 16 Pathology Informatics 2012

17 Specimen Imaging Information Model Basic DICOM Information Model Patient 1 n Has 1 Is source of Disambiguates specimen and container Container is target of image Equipment Modality 1 n Creates Study 1 Contains n Series 1 n Container may have more than one specimen Specimens have a physical derivation (preparation) from parent specimens Component Base, Coverslip n Has 1 Contains n Image 1 Is acquired on 1 Container Box, Block, Slide, etc. 1 Contains n n Specimen Physical object Is child of 1 1 When more than one specimen in an imaged container, each specimen is distinguished (e.g., by position or color-coding) Has n Preparation Step Collect, Sample, Stain, Process 17 Pathology Informatics 2012

18 Preparation steps example Part Collection in OR Specimen received in Pathology department Sampling to block Slide staining

19 The Whole Slide Problem Need image resolution comparable to optical microscope Need image access as rapid as microscope (pan, zoom, focus) 19 Pathology Informatics 2012 Yukako Yagi UPMC

20 Tiling and Multi-frame encoding Whole Slide Image divided into tiles Each tile encoded into a frame of multi-frame image object Per-frame metadata gives spatial location for each tile: X, Y, and Z (focal plane) Pixels may be JPEG compressed Multiple focal planes Multi-frame image object Patient, Study, Series Per-frame metadata Dimension data Pixel data

21 Access: Navigation and Zoom Need to rapidly access: High resolution image of small areas Facilitated by tilling Low resolution image of whole slide For overview and navigation Intermediate resolutions Smooth zooming Lower resolution images may be pre-computed in separate objects Hierarchical pyramid May add ~ 33% to size of data 22 Pathology Informatics 2012

22 Multi-spectral imaging 3 x 8-bit RGB Typical color image stored with RGB or YBR photometric interpretation 3 color values / pixel Multi-spectral image stored with MONOCHROME photometric interpretation 1 color value / pixel / color plane Multiple color planes may be stored in single image object Each frame references its optical path in per-frame header n x 16-bit multi-spectral 23 Pathology Informatics 2012

23 MANAGEMENT OF PATHOLOGY IMAGING 24 Pathology Informatics 2012

24 Pathology image storage Some LIS s can store isolated images (select JPEG snapshots) Generally not designed for robust bulk data storage and associated long-term storage management functionality Generally do not provide standard external (non-lis) access to images Not designed for whole slide images Will need integration of LIS with Picture Archiving and Communication Systems (PACS) 25 Pathology Informatics 2012

25 PACS for Pathology Off-the-shelf radiology / enterprise PACS Provide good long-term bulk data management Provide external standard access (DICOM and Web) Most can store VL single frame images But not designed for whole slide images If WSI is in plan, will need WSI-capable PACS PACS generally integrated with viewer application 26 Pathology Informatics 2012

26 LIS / PACS integration image link LIS needs to track images associated with case stored in the PACS Unique ID Access link somebody needs to derived dynamically from UID (acquisition system? LIS?) Similar requirements for EMR link to radiology PACS Launch image viewer from case review Included in Stage 2 Meaningful Use regulations (2014) Link notification from PACS in HL7v2 message OUL^R24 (order-based result), ORU^R23 (container-based result), or ORU^R01 (v2.3.1-compatible) 27 Pathology Informatics 2012

27 LIS / PACS integration order control Need bi-directional integration PACS matches incoming images to case, reconciles metadata Does PACS know about lab case accession ID? Scheduled study/case order information to PACS HL7v2 OML^O21 (lab order) / ORL^O22 (response) DICOM Study UID may be provided by LIS pre-adoption v2.9 OO_CR Pathology Informatics 2012

28 LIS / imaging integration specimen management LIS can provide significant support for automated lab processes, including imaging Barcode-based work process Case/specimen history tracking - important for imaging setup HL7 project on specimen unique identifier underway HL7v2 messaging for lab automation How to integrate DICOM imaging? Is it just another automated in vitro analyzer? 29 Pathology Informatics 2012

29 DICOM imaging workflow control DICOM workflow management services for the imaging department Modality Worklist (MWL) scheduled work tasks Modality Performed Procedure Step (MPPS) work task status LIS / modality integration through mediator Interface engine or broker PACS WSI equipment wants slide processing history from LIS Slice thickness, stain, etc. can be used to select appropriate imaging protocol History included in DICOM image header for proper interpretation 30 Pathology Informatics 2012

30 INTEGRATED LAB WORKFLOW 31 Pathology Informatics 2012

31 Putting the pieces together Between DICOM and HL7 we have the building blocks for lab workflow integration Still need to bring them together into a comprehensive end-to-end workflow Lock down optionality inherent in standards Specific data element use and content Specific expected behavior by system actors in response to specific messages Required: workflow profile (implementation guide) specified by broad industry consensus 32 Pathology Informatics 2012

32 Integrating the Healthcare Enterprise An international public-private initiative ~450 members: 60 healthcare professional organizations; 17 government agencies; 7 SDOs; 55 provider, research and education organizations; 330 HIT and consulting companies Goal to improve patient care and provider efficiency by harmonizing electronic health information exchange Profiles approved standards to seamlessly pass health information among care providers on a local, regional and national level Developed through ~12 specialty domains Collaboration with regional and national deployment efforts (e.g., US ONCHIT, Canada Health Infoway, France DMP, etc.) 33 Pathology Informatics 2012

33 IHE Deliverables Domain committees (venue for collaboration) Integration Profiles (use cases - what needs to be done) Technical Framework (implementation guide - how to do it) Connect-a-thon (actually do it!) Public demonstrations (show it can be done!) Tools for acquiring conformant products (help users do it, too!) 34 Pathology Informatics 2012

34 Connect-a-thon Technical Framework Demonstrations 35 Pathology Informatics 2012

35 The IHE Value Proposition Users get a comprehensive, end-to-end workflow Uniting multiple systems and multiple standards Improving cost-effectiveness and quality of patient care Vendors can rely on other actors (from other vendors) providing critical information in a consistent manner Reducing development, validation, and integration costs Avoiding chicken-and-egg adoption problem Integration occurs proactively in controlled environment with defined timetable, not reactively at user site Common approach creates the market in which vendors can sell and users can buy with confidence 36 Pathology Informatics 2012

36 IHE Anatomic Pathology Workflow Profile IHE Anatomic Pathology Domain DICOM-based imaging workflow (modeled on radiology) LIS (Order Filler) responsible for integration with broker Does not account for non-dicom device integration APW 37 Pathology Informatics 2012

37 IHE Laboratory Analytical Workflow Profile IHE Lab Domain HL7-based IVD integration workflow Does not account for bulk data integration (imaging or other externally managed data) Does not explicitly include specimen processing history in subsequent work tasks LIS Order Filler Analyzer Manager LAW profile Analyzer IVD instrument LTW profile Pre/Postprocessor nonanalytical robotic device LDA profile LAS (or middleware) Analyzer Manager Automation Manager LAW profile Analyzer IVD instrument LAW profile middleware Analyzer Analyzer Manager LAW profile Analyzer IVD instrument LAW 38 Pathology Informatics 2012

38 Integrated workflow proposal Combines aspects of APW and LAW profiles Allows LIS to be agnostic to DICOM (through broker) Pre-adopts HL7 CR-726 for imaging parameters in HL7 work order step transactions Comprehensive mapping between HL7 and DICOM Specifies requirements on data repository separate from LIS Both DICOM and CDA repositories supported 39 Pathology Informatics 2012

39 Issues to be resolved during profile development (examples) Which of the workflow and storage alternatives are mandatory and which optional, and how to specify the optionality How to pass specimen preparation history, and whether this is mandatory on LIS How to specify standards-based tighter LIS-imaging integration (e.g., request for restaining is that a reflex test?) What standard mechanisms for access and/or export must CDA repository provide (e.g., RID and XDR/XDM Profiles) What transaction should be used for submission to CDA Repository HL7v2 MDM, or XDS Provide&Register, or both 40 Pathology Informatics 2012

40 Proposal timeline Submitted to IHE Anatomic Pathology To be discussed in tcon October 16 Prioritization of profiles to be complete in December Technical Framework Supplement developed in Spring 2013 Connectathon in January 2014 You are invited to participate in the development! 41 Pathology Informatics 2012

41 Isn t this all academic? My current LIS is certainly not ready for this We have no $$ to implement a new system All investment is being sucked in EHR for Meaningful Use Standards development leads general availability for deployment by ~5 years Required now for LIS vendors to build into next gen product This work provides a roadmap to assist your strategic planning 42 Pathology Informatics 2012

42 Some Midwest metaphors 43 Pathology Informatics 2012

43 Thank you