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Whole Slide Imaging in DICOM

Whole Slide Imaging in DICOM. Harry Solomon GE Healthcare. WSI Supplements. Two DICOM Supplements developed by WG-26 Anatomic Pathology Supplement 145: Whole Slide Imaging Adopted August 2010 Supplement 122: Specimen Module Adopted June 2008. The Whole Slide Problem.

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Whole Slide Imaging in DICOM

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  1. Whole Slide Imaging in DICOM Harry Solomon GE Healthcare

  2. WSI Supplements • Two DICOM Supplements developed by WG-26 Anatomic Pathology • Supplement 145: Whole Slide Imaging • Adopted August 2010 • Supplement 122: Specimen Module • Adopted June 2008

  3. The Whole Slide Problem • Need image resolution comparable to optical microscope • Need image access as rapid as microscope (pan, zoom, focus) Yukako Yagi– UPMC

  4. Digital slides are huge • Sample size ~ 20mm x 15mm • Resolution of .25 μm/pixel (40X objective) • 80,000 x 60,000 pixels = 4.8 Gp • 24-bit color = 14.4 GB / slide • 40:1 compression = only 360 MB / typical slide Unless • Larger specimen • Higher resolution (100X objective) • Multiple focal planes • Multi-spectral imaging (16-bit / band) And • A typical study may be 10 slides

  5. Fixed Header Dimension data Pixel data Per-frame header Sup 145 Tiling and Multi-frame encoding • Whole Slide Image divided into tiles • Each tile encoded into a frame of multi-frame image object • Per-frame header givesspatial location for each tile: X, Y, and Z (focal plane) Multiple focal planes Multi-frame image object

  6. Z-planes (focal planes) • Z-planes are identified as nominal physical height of image focal plane above reference surface (μm) • Z-plane information is used for relative spatial positioning of image planes, and nominal inter-plane distance • An image plane may track variable specimen thickness / surface contour, but only one Z-value used ↑ Z Cover slip ↑ Z Specimen Slide substrate (glass)

  7. Z planes may track curved surface Z plane 1 Z plane 2 Z plane 3 Z plane 4 Tile 1 Tile 2 Tile 3 Tile 4 Tile 5 Tile 6 Tile 7 Tile 8 Viktor Sebestyén Varga – 3DHISTECH Ltd.

  8. Total Pixel Matrix Total Pixel Matrix Origin • Total pixel matrix origin at top left hand corner of imaged volume • Frame (tile) rows and columns align with total pixel matrix rows and columns • Frames limited to 216 columns and rows each • Total pixel matrix limited to 232 columns and rows Columns → Rows ↓ Frame Pixel Matrix Origin Total pixel matrix coordinates used for frame location and for annotation

  9. Sparse tiling • Slides may have substantial area with no specimen • Empty tiles may be absent from multi-frame image

  10. 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 bepre-computed • Hierarchical pyramid • May add ~ 33% to size of data

  11. Tiling and multi-frame at all hierarchical levels Single frame image Thumbnail Image Multi-frame image (single object) Intermediate Image Multi-frame image (single object)may include multipleZ-planes, color planes Baseline Image All image objects typically in 1 DICOM Series

  12. Localizer image “flavor” • Thumbnail image (single frame) plus navigation links to each frame at each resolution • Each tile of other resolution images has its corresponding area identified in thumbnail • Full description of target tiles • Object Unique ID and frame number • Resolution • Z-plane, color • Multiple target frames can overlap • Different resolution, Z-plane, color, etc. • Presentation and any interactive behavior is not defined in standard

  13. Optical paths • Each combination of light source, lenses, illumination method, detected wavelengths, etc. used in a scan is an optical path • Three primary mandatory attributes: • Illumination color or wavelength • Illumination method (e.g., transmission, epifluorescence , darkfield, differential interference contrast) • Detection color • Additional optional attributes for lenses, filters, prisms, etc. • Examples: • Full spectrum light, transmission, RGB color sensors • UV excitation, epifluorescence, 535 nm emission filter, monochrome sensor Illumination Method Illumination Filters Lens Lens Filters Sensor

  14. Multi-spectral imaging • 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 3 x 8-bit RGB n x 16-bit multi-spectral

  15. Standard DICOM mechanisms for annotation of WSI • Color Presentation State • Displayed Area Selection relative to WSI total matrix • Graphic and text annotation with sub-pixel location resolution, even with 8M columns or rows • Segmentation • Can be created pixel-by-pixel against selected frames of original image • 1-bit/source-pixel, or 8-bits/source-pixel • Display of segmentation implicitly invokes blending with source image • Structured Reporting • Captures measurements, clinical observations, analyses, and findings • Real World Value Mapping • Specifies a mapping of the stored pixel values of images into some real world value in defined units • Allows quantitative methods with monochrome images (original or derived)

  16. Interpretation Worklist by accession Pathology order Slide preparation history data LIS / APLIS Specimen accessioning data Modality Worklist Query by slide barcode Imaging task w/ slide preparation history data Imaging task completion w/ list of imagesand specimen IDs Images Images Images w/slide prep history PACS Images – X-ray, U/S, optical, etc. Anatomic Pathology Imaging Workflow Slide preparation Workstation Gross specimen accessioning Whole Slide Scanner Surgical or biopsy procedure

  17. Sup 122 Specimen Module • Support for pathology lab workflow, specimen-based imaging • Gross specimens, blocks, vials, slides • Image-guided biopsy samples • Specimen Module at image level of hierarchy • Identification, processing history (especially stains applied) • Modality Worklist can convey Specimen Module • Enables automated slide scanning devices to fully populate image header • Processing history can be used to set up acquisition (based on stain) • Modality Performed Procedure Step identifies imaged specimen • Allows LIS/APLIS to track images for specimens

  18. Specimen Imaging Information Model Disambiguates specimen and container Container is target of image Container may have more than one specimen Specimens have a physical derivation (preparation) from parent specimens When more than one specimen in an imaged container, each specimen is distinguished (e.g., by position or color-coding) Basic DICOM Information Model

  19. Enabling Transformation to Digital Pathology • Supplements 145 and 122 establish the foundation for a true market for digital imaging in anatomic pathology • Comparable in importance to the introduction of DICOM to radiology in 1993 • Enables quantitation and collaboration • In the next 5-10 years, we should expect a profound transformation of pathology from a highly manual process to a digital workflow • The use of the DICOM Standard across radiology, pathology, surgery, and radiation therapy opens the door to truly integrated data from screening to biopsy to diagnosis to treatment

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