Innovations in Multi-energy CT Imaging for Enhanced Diagnostic Capabilities
Cutting-edge Multi-energy CT (MECT) imaging brings a paradigm shift by utilizing varied X-ray beam energies for tissue differentiation and quantification. The rationales, techniques, and objectives are outlined for seamless integration into existing systems, paving the way for improved diagnostic accuracy and efficient adoption across medical platforms.
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Supplement 188: Multi-energy CT Imaging DICOM Working Group 21 Computed Tomography
Rationale Multi-energy CT (MECT) uses multiple energies from the X-Ray beam spectrum (conventional CT uses a single (accumulated) X-Ray spectrum). This enables differentiation, quantification and classification of different types of tissues. Challenges: Existing CT and Enhanced CT IODs do not adequately describe MECT. MECT engineering mechanisms differ significantly across vendors (but fortunately the generated diagnostic images are mostly similar) Goals: Facilitate fast/easy adoption of MECT across modalities and PACS/Displays Re-use/mirror existing CT/Enhanced CT IOD content for compatibility Capture essential MECT details in IOD (acquisition, reconstruction and processing) Profile usage of existing CT/Enhanced CT IOD attributes for MECT techniques Minimize interpretation/measurement risks when legacy displays present MECT images 2
Overview Multi Energy Imaging Standard CT Image Material Visualization Family Material Quantification Family Objective Image Family Virtual Mono- energetic Image (VMI) Material- Specific Image Iodine Map; Bone Density CT IOD Other IOD Fractional Map Image Material- Modified Image Highlighted; Partially- Suppressed Color Overlay Image Effective Atomic Number (Z) Image Value based Map Image Gout crystals Color Blending Image Material- Removed Image Virt. Non- Contrast; Virt. Non-Ca; Electron Density Image Color Map Image
Multi-energy CT Acquisition Mechanisms Scanned Object X-Ray Source Detector Discriminate different energies: Generate different energies: Multiple Layers Photon Counting Filters Other Parameters KVP Switching Mechanisms to separate at least two energies include: Multiple Scans of the same area with different parameters Switch KVP during the rotation Multiple X-Ray Sources One source with Multi-Layer Detector One source with Photon Counting Detector
Objective Images Processing Steps Decomposition to Base Components Generation of Diagnostic images Data Acquisition Described in ME CT Acquisition Sequence Described in ME CT Processing Sequence Described in ME CT Characteristics Sequence Datasets Virtual A1 M1 Monochromatic M2 Effective Atomic Number A2 Mn Electron Density An
Material Images Processing Steps Decomposition to (and/or Classification of) two or more Materials Generation of Diagnostic images Data Acquisition Described in ME CT Acquisition Sequence Described in ME CT Processing Sequence Described in ME CT Characteristics Sequence Datasets Material Quantification Family A1 M1 M2 A2 Material Visualization Family Mn An
Material Images Examples:: - Iodine Map - Bone (Ca) Density Map M1 Material-Specific Image Fractional Map Image M2 May be ignored or not described Mn Example: - Virtual Non-Contrast or Virtual Non-Calcium : REMOVED Material-Removed Image M1 Conventional CT or VMI Image M2 Example: - Tendon Enhancement: HIGHLIGHTED Material Visualization Image Mn Remove Suppress Highlight Recalculate o o o o
Material Maps Images Fractional Map: Value based Map: Material A BCD 4 Material A = 0-15 0.2 10 20 Material B = 10-20 Contains 20% of material A 15 0 Material C = 18-50
Visualization Images: Color Overlay Overlay Image Blended Image Structural Image The blended image combines an overlay CT image highlighting a particular material (E.g. Iodine image, Effective Z image) with a monochromatic anatomical structure image. The new Multi-energy image format can be used as blending image together with a Standard CT image in the Blending Presentation States.
CT IOD Structure Multi-energy CT Acquisition attribute (YES/NO) added to CT Image Module Multi-energy CT Image Module (new, conditional): Multi-energy CT Acquisition Sequence (Type 1, 1 item) Multi-energy CT Characteristics Sequence (Type 1C, 1 item) Multi-energy CT Processing Sequence (Type 3, 1 item) Multi-energy CT Acquisition Sequence ME X-Ray Source Sequence (1-n) ME X-Ray Detector Sequence (1-n) ME Path Sequence (2-n) CT Exposure Macro CT X-Ray Details Macro CT Acquisition Details Macro CT Geometry Macro Multi-energy CT Characteristics Macro Monochromatic Energy Equivalent (for Virtual Monochromatic Image) Other image-specific attributes Multi-energy CT Processing Sequence (Type 3, 1 item) Decomposition Method, Algorithm Decomposition Material Sequence (2-N items, one for each base material) Other decomposition attributes 10
Organization Structure Path Scheme CT IOD CT Image Module General Image Module ME CT Acquisition Real-World Value Mapping ME CT ME CT Processing Characteristics ME CT X-Ray Source Seq. ME CT Detector Seq. CT Exposure CT ME CT Path Seq. Geometry CT Acquisition Details CT X-Ray Details Seq. 11
Enhanced CT IOD Structure Enhanced CT Image IOD Module: Multi-energy CT Acquisition attribute (YES/NO) new attribute added Enhanced Multi-energy CT Image Acquisition IOD Module (new, conditional): ME X-Ray Source Sequence ME X-Ray Detector Sequence ME Path Sequence Enhanced CT Image Functional Group Macros (added, conditional): Multi-energy CT Processing Multi-energy CT Characteristics 12
New Image Types Image Type (Value 4) Recommended Rescale Type Description a Virtual Monochromatic Image. Each pixel represents CT Hounsfield units and is analogous to a CT image created by a monochromatic (of a specific keV value) X-Ray beam. VMI HU a Material-Specific Image. Each real-world value mapped pixel value represents a property of a specific material such as attenuation, concentration or density. a Material-Removed Image. Each pixel represents CT Hounsfield units however some pixel values may have been corrected for replacement of one material by another material. Image with one or more materials removed. MAT_SPECIFIC HU, MGML MAT_REMOVED HU, HU_MOD a Material-Fractional Image. Each pixel represents a fraction of 1 of a material. MAT_FRACTIONAL PCT an Effective Atomic Number Image. Each pixel represents Effective Atomic Number EFF_ATOMIC_NUM Z_EFF an Electron Density Image. Each pixel represents a number of electrons per unit volume (units 1023 /ml) or a relative ED/EDWater ratio (N/Nw). ELECTRON_DENSITY ED, EDW a Material-Modified Image. CT Image where pixel values have been modified to highlight a certain target material (either by partially suppressing the background or by enhancing the target material), or to partially suppress the target material. MAT_MODIFIED HU_MOD a Value-Based Map Image. Each pixel represents a values indirectly describing identified material(s). MAT_VALUE_BASED US
Examples for Rescale Type assignments Image Type Value 4 Intercept Slope RWV First & Last Values mapped RWV Intercept RWV Slope RWV LUT Label RWV Measurement Units Multi-energy Image Family Recommended Rescale Type Objective Image Family VMI -1024 1 0/4095 -1024 1 VMI hnsf U Virtual Monoenergetic Image HU EFF_ATOMIC_NUM 0 1 0/4000 0 0.01 EFF_ATOMIC_NUM NewCode2-02 Effective AN (Z) Image 10^-2 Z_EFF ELECTRON_DENSITY 0 1 0/4000 0 0.01 ELECTRON_DENSITY 10*23/ml Electron Density Image 10^-2 ED ELECTRON_DENSITY 0 1 0/4000 0 0.001 ELECTRON_DENSITY ratio 10^-3 EDW Material Quantification Family MAT_SPECIFIC (0) (-10) 1 0/4000 -3 0.01 MAT_SPECIFIC mg/cm3 Material-Specific Image 10^-2 MGML MAT_SPECIFIC -1024 1 0/4095 -1024 1 MAT_SPECIFIC hnsf U HU MAT_REMOVED -1024 1 0/4095 -1024 1 MAT_REMOVED hnsf U Material-Removed Image HU MAT_REMOVED -1024 1 0/4095 -1024 1 MAT_REMOVED NewCode2-03 HU_MOD MAT_FRACTIONAL 0 1 0/1000 0 0.1 MAT_FRACTIONAL % Fractional Map Image 10^-1 % MAT_VALUE_BASED 0 1 0/100 0 1 MAT_ VALUE_BASED US Value-based Map Image US 14
Contacts Reinhard Ruf Chair WG-21 Siemens Healthineers reinhard.ruf@siemens.com Shlomo Gotman Member WG-21 Philips Healthcare shlomo.gotman@philips.com
