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Supplement 188: Multi-energy Supplement 188: Multi-energy

Supplement 188: Multi-energy - PowerPoint Presentation

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Supplement 188: Multi-energy - PPT Presentation

CT Imaging DICOM Working Group 21 Computed Tomography Rationale Multienergy CT MECT uses multiple energies from the XRay beam spectrum conventional CT uses a ID: 783955

material image mat energy image material energy mat acquisition multi specific map ray density removed sequence pixel type images

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Presentation Transcript

Slide1

Supplement 188:

Multi-energy CT Imaging

DICOM Working Group 21

Computed Tomography

Slide2

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/DisplaysRe-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 techniquesMinimize interpretation/measurement risks when legacy displays present MECT images

2

Slide3

Virtual Mono-energetic Image (VMI)

Color Overlay ImageColor Blending Image

Effective Atomic Number (Z) Image

Electron Density Image

Color Map Image

Multi Energy Imaging

Material Quantification

Family

Material

Visualization

Family

Standard CT Image

Objective Image

Family

Material-Specific Image

Iodine Map;

Bone Density

Overview

Fractional Map Image

Value based Map

Image

Material-Modified Image

Gout crystals

Highlighted;

Partially-Suppressed

Material-Removed Image

Virt

.

Non-Contrast;

Virt

. Non-Ca;

CT IOD

Other IOD

Slide4

X-Ray Source

Generate different energies:KVP SwitchingDetector

Filters

Other Parameters

Discriminate different energies:Multiple LayersPhoton CountingMulti-energy

CT Acquisition

Mechanisms

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

Scanned Object

Slide5

Objective Images

Virtual MonochromaticEffective Atomic NumberElectron DensityDescribed in ME CT Characteristics Sequence

Data Acquisition

Decomposition to

Base ComponentsDescribed in ME CT Processing SequenceDescribed in

ME CT Acquisition Sequence

A1

A2

M1

M2

Mn

An

Generation of Diagnostic images

Datasets

Processing Steps

Slide6

Material Images

Data Acquisition A1A2

Described in

ME CT

Processing SequenceDescribed in ME CT Acquisition SequenceDescribed in ME CT Characteristics SequenceMaterial Quantification FamilyM1

M2

Mn

Material Visualization

Family

Decomposition to

(and/or Classification of)

two or more Materials

An

Generation of Diagnostic images

Datasets

Processing Steps

Slide7

Material Images

M1M2Material-Specific Image

May be ignored or not described

M1

M2

Mn

Conventional CT or VMI Image

Material Visualization Image

Remove

Suppress

Highlight

Recalculate

Mn

Fractional Map Image

Material-Removed Image

Examples:

:

Iodine Map

Bone (Ca) Density Map

Example

:

Virtual Non-Contrast or Virtual Non-Calcium : REMOVED

Example

:

Tendon Enhancement: HIGHLIGHTED

Slide8

Material Maps Images

Material A = 0-15Material B = 10-20Material C = 18-50Contains 20% of material A

0.2

Fractional Map:

4

Value based Map:

20

0

10

15

Material A

B

C

D

Slide9

“Visualization” Images:

Color OverlayThe 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.

Blended Image

Structural Image

Overlay Image

Slide10

CT IOD Structure

Multi-energy CT Acquisition attribute (YES/NO) added to CT Image ModuleMulti-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 SequenceME X-Ray Source Sequence (1-n)ME X-Ray Detector Sequence (1-n)ME Path Sequence (2-n)CT Exposure MacroCT X-Ray Details MacroCT Acquisition Details Macro

CT Geometry

Macro

Multi-energy CT Characteristics MacroMonochromatic Energy Equivalent (for Virtual Monochromatic Image)Other image-specific attributesMulti-energy CT Processing Sequence (Type 3, 1 item)Decomposition Method, AlgorithmDecomposition Material Sequence (2-N items, one for each base material)Other decomposition attributes10

Slide11

Organization Structure – Path Scheme

11CT IODCT Image ModuleME CT Acquisition

ME CT X-Ray Source Seq.

ME CT Detector Seq.

ME CT Characteristics

ME CT

Processing

ME CT Path Seq.

CT X-Ray Details Seq.

CT Exposure

CT Acquisition Details

CT Geometry

General Image Module

Real-World Value Mapping

Slide12

Enhanced CT IOD Structure

Enhanced CT Image IOD Module:Multi-energy CT Acquisition attribute (YES/NO) – new attribute addedEnhanced Multi-energy CT Image Acquisition IOD Module (new, conditional):ME X-Ray Source SequenceME X-Ray Detector SequenceME Path SequenceEnhanced CT Image Functional Group Macros (added, conditional):Multi-energy CT ProcessingMulti-energy CT Characteristics12

Slide13

New Image Types

Image Type (Value 4)Recommended Rescale

Type

Description

VMI

HU

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.

MAT_SPECIFIC

HU, MGML

a Material-Specific Image.

Each real-world value mapped pixel value represents a property of a specific material such as attenuation, concentration or density.

MAT_REMOVED

HU, HU_MOD

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_FRACTIONAL

PCT

a

Material-Fractional

Image. Each pixel represents a

fraction of

1 of a material.

EFF_ATOMIC_NUM

Z_EFF

an Effective Atomic Number Image. Each pixel represents Effective Atomic Number

ELECTRON_DENSITY

ED, EDW

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

).

MAT_MODIFIED

HU_MOD

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_VALUE_BASED

US

a

Value-Based Map

Image.

Each pixel represents a values indirectly describing identified material(s).

Slide14

Examples for Rescale Type assignments

14Multi-energy Image FamilyRecommended Rescale Type

Image Type Value 4

Intercept

Slope

RWV First & Last Values mapped

RWV Intercept

RWV Slope

RWV LUT Label

RWV Measurement Units

Objective Image Family

 

 

 

 

 

 

 

 

Virtual Monoenergetic Image

HU

VMI

-1024

1

0/4095

-1024

1

VMI

hnsf’U

Effective AN (Z)

Image

10^-2 Z_EFF

EFF_ATOMIC_NUM

0

1

0/4000

 

0

0.01

EFF_ATOMIC_NUM

NewCode2-02

Electron Density Image

 

 

10^-2

ED

ELECTRON_DENSITY

0

1

0/4000

0

0.01

ELECTRON_DENSITY

10*23/ml

10^-3

EDW

ELECTRON_DENSITY

0

1

0/4000

0

0.001

ELECTRON_DENSITY

ratio

Material Quantification Family

 

 

 

 

 

 

 

 

Material-Specific Image

10^-2

MGML

MAT_SPECIFIC

(0) – (-10)

1

0/4000

-3

0.01

MAT_SPECIFIC

mg/cm3

HU

MAT_SPECIFIC

-1024

1

0/4095

-1024

1

MAT_SPECIFIC

hnsf’U

Material-Removed

Image

 

HU

MAT_REMOVED

-1024

1

0/4095

-1024

1

MAT_REMOVED

hnsf’U

HU_MOD

MAT_REMOVED

-1024

1

0/4095

-1024

1

MAT_REMOVED

NewCode2-03

Fractional Map Image

10^-1 %

MAT_FRACTIONAL

0

1

0/1000

0

0.1

MAT_FRACTIONAL

%

Value-based Map Image

US

MAT_VALUE_BASED

0

1

0/100

0

1

MAT_ VALUE_BASED

US

Slide15

Contacts

Reinhard Ruf Chair WG-21 Siemens Healthineers reinhard.ruf@siemens.comShlomo Gotman Member WG-21 Philips Healthcare shlomo.gotman@philips.com