Dual Energy CT:
Physics Principles
Disclosures
Uri Shreter and Robert Senzig, GE Healthcare
Thomas Flohr and Bernhard Schmidt, Siemens
Medical Solutions
Norbert J. Pelc, Sc.D.
Departments of Radiology and Bioengineering
Stanford University
Motivation
• Material specificity
• Improved tissue characterization
“Two pictures are taken of the same slice, one at 100
kV and the other at 140 kV... areas of high atomic
numbers can be enhanced... Tests carried out to date
have shown that iodine (Z=53) can be readily
differentiated from calcium (Z=20)”.
G.N. Hounsfield, BJR 46, 1016-22, 1973.
Research support: NIH grant EB006837, GE
Healthcare, the Lucas foundation
This lecture includes off-label use of CT scanners
OUTLINE
• Physical principles of multi-energy x-ray
measurements
• Dual energy CT
processing
obtaining dual-energy measurements
scanning
• Strengths and limitations
energy E1
E2
water
mb (g/cm2)
bone
unknown amounts of
two known materials
100.0
E1
I01 I02
E2
energy E1
10.0
water
mass attenuation coefficient (cm2 /g)
I01 I02
mass attenuation coefficient (cm2 /g)
unknown amounts of
two known materials
cortical
bone
E2
water
1.0
mb (g/cm2)
bone
0.1
10
20
50
100
200
100.0
E1
water
cortical
bone
1.0
•
•
0.1
10
20
50
100
200
photon energy (keV)
photon energy (keV)
I1 = I01 e -(µ/ρ)w1mw + (µ/ρ)b1mb
I2 = I02 e -(µ/ρ)w2mw + (µ/ρ)b2mb
solve for mw and/or mb
I1 I2
E2
10.0
dual energy projection methods
I1 I2 mb = A{ ln(I01/I1) - (µw1/µw2)(ln(I02/I2)}
scale for lost
bone signal
makes the water contribution
at E2 match that at E1
material analysis with
absorptiometry
• 2 energies
DEXA
subtract
water
2 materials
• can we generalize this? N energies for N
materials?
• limitation: two strong interaction mechanisms
Single energy
Dual
Energy
Radiography
Bone image
“Bone minic tissue” image
Compton scattering and photoelectric absorption
Each has ~ same energy dependence for all elements
Basis material decomposition
Basis material decomposition
1000
I0
100
Cu
O
Ca
Cu
Ca'
10
Ca
.04 M grams of Cu
.61 M grams of O
I0
M grams of Ca
=
I
I
Indistinguishable at any x-ray energy above their K-edge
1
.61*O + .04*Cu
O
(K-edge methods are not covered here)
0.1
0
20
40
60
80
100
120
140
basis material decomposition
• Barring a K-edge:
µ(E) = a*Compton(E) + b*Photoelectric(E)
2 fundamental parameters characterize material behavior
electron density, effective atomic number
basis material decomposition
• Barring a K-edge:
µ(E) = a*Compton(E) + b*Photoelectric(E)
2 fundamental parameters determine material behavior
electron density, effective atomic number
• any material can be modeled as a weighted sum of two
other materials
µ(E) = α* µi(E) + β* µj(E)
basis material decomposition
common bases: aluminum and plastic
• in any projection measurement, we can only isolate two
materials
OUTLINE
• Physical principles of multi-energy x-ray
measurements
• Dual energy CT
processing
obtaining dual-energy measurements
scanning
• Strengths and limitations
Dual-energy processing
• reconstruct images in the normal manner,
and combine HU images
easy to implement
• combine projection data prior to
reconstruction
somewhat more difficult
requires aligned projections
enables “exact” beam hardening correction
Dual-energy processing
• material selective images
basis material images
material specific or cancelled images
“virtual non-contrast” scans
weighted subtractions of the two energies
processing amplifies noise
• monoenergetic images
weighted sums of the two energies
can be high SNR, depending on the weighting
Pre-reconstruction processing
low energy
projections
calibration
high energy
projections
nonlinear
combination
“aluminum”
projections
“plastic”
projections
Potential for beam hardening streak-free images
80kVp
can incorporate accurate
beam hardening
correction
basis material images
CT recon
“aluminum”
“plastic”
image
image
linear
combination
Monochromatic CT from projection-based recon
Image based
Water
Aluminum
140kVp
Projection based
Water
Aluminum
Monochromatic
material selective images
monoenergetic images
Projection based MD reduces beam hardening
final
image(s)
adapted from Lehmann et al: Med Phys 8, 659-67, 1981.
Courtesy of Uri Shreter, GE Healthcare
Potential impact on Cardiac IQ +
Perfusion
Polychromatic
Monochromatic CT from projection-based recon*
80kVp
140kVp
Heart Chamber Phantom, 8.3%
L = 0, W = 350 HU
Material separation
Water
Iodine
Monochromatic
Monochromatic CT – keV
tuned
Natively eliminates beam
hardening CT # shifts
Courtesy of Uri Shreter, GE Healthcare
Pre-reconstruction processing
low energy
projections
calibration
high energy
projections
nonlinear
combination
“aluminum”
projections
linear
combination
final
image(s)
Two known materials in a voxel
55 keV
80 keV
optimal combination
(“mixed” image)
iodine CNR=7.9
iodine CNR=3.8
iodine CNR=10
water SNR=67
water SNR=71
iodine image
water image
SNR=3.4
SNR=37
iodine contrast
higher, negatively
correlated noise
“plastic”
projections
CT recon
“aluminum”
“plastic”
image
image
Courtesy of R. Senzig, GE Healthcare
“water” contrast
material selective images
(noisy)
monoenergetic images
(can be low noise)
adapted from Lehmann et al: Med Phys 8, 659-67, 1981.
Dual energy CT
effective Z > water
HUlow
Principle of Dual Energy CT – Image Based Evaluation
Each material is characterized by its „Dual Energy Index“
x80 and x140 are the Hounsfield numbers at 80 kV and 140 kV, resp.
line of identity: “water-like” materials
effective Z < water
-1000
HUhigh
-1000
HUlow/HUhigh
(and related metrics)
depend on effective Z
Material
DEI
Bone
0.1148
Liver
0.0011
Lung
-0.0021
Soft Tissue
-0.0052
Skin
-0.0064
Proteins
-0.0087
Fat
-0.0194
Gall fluid
-0.0200
Dual energy CT can measure chemical composition!
Courtesy of B. Krauss, B. Schmidt, and Th. Flohr, Siemens Medical Solutions
atomic number and density as
material parameters
Three known materials
dual energy CT
water
• tissue specificity? applications being
investigated
kidney stone characterization
fat or iron in the liver
plaque characterization
• image segmentation
bone or plaque removal
identifying ligaments or tendons
bone
HUlow
iodine
bone and iodine
in water
Can calculate both iodine and bone.
Requires known mixing properties
and consistent water density
water +
iodine
water +
bone
identity
HUhigh
mb = A{ HUlow - (Μ 1,I/ Μ2,I) HUhigh}
Kelcz et al: Med Phys 6, 418-25, 1979.
Three known materials
dual energy CT
Reliable separation requires large
(R1 - R2)2
calcium
iodine
where R = µhigh/µlow, depends on
material and energies
Works best for one high Z and one
lower Z material, and
very different x-ray energies
Spectral separation
• very critical for SNR efficiency, separation
robustness, etc.
• implementations
different kVp and/or filtration
layered detector
photon counting with energy analysis
Kelcz et al: Med Phys 6, 418-25, 1979.
Dual kVp, dual filtration
85 kVp
0.1 mm erbium
• switched filtration
improves separation
• different mAs helps
apportion dose
135 kVp
1.5 mm bronze
Lehmann et al: Med Phys 8, 659-67, 1981.
Energy discriminating, photon
counting detectors
Layered detector
• simultaneous dual energy sensing
• relatively poor spectral separation
broad spectrum
x-ray source
pulse
shaping
High enough count
rate is difficult to
achieve
two
(or more)
energy
bins
pulse
height
analysis
Carmi R, Naveh G, and Altman A: IEEE
NSS M03-367, 1876-78, 2005
Spectral separation
• very critical for SNR efficiency, separation
robustness, etc.
• implementations
photon counting with K-edge filter
photon counting with energy analysis
different kVp and filtration
different kVp
layered detector
better
spectral
separation
and
dose
efficiency
Dual energy implementations
• Sequential scans at different kVp
motion sensitivity > 50% Trot
higher motion sensitivity in helical mode
• Two sources at 90º on the same gantry
Siemens Definition
80 kVp & 140 kVp
Dual Source Challenge: Inconsistent scans
Moving Objects
Moving Phantom
Simulation
Coincident
Dual energy implementations
• Sequential scans at different kVp
motion sensitivity > 50% Trot
• Two sources at 90º on the same gantry
some motion sensitivity (~ 25% Trot)
Does not see movement
Dual Source system
• Switching kVp within a single scan1, 2
technically challenging with rapid gantry rotation
Courtesy of R. Senzig, GE Healthcare
Rapid kVp switching
Dual energy CT
1. Lehmann et al: Med Phys 8, 659-67, 1981.
2. Kalender et al, Med Phys 13, 334, 1986.
Dual energy implementations
• Sequential scans at different kVp
motion sensitivity > 50% Trot
• Two sources at 90º on the same gantry
some motion sensitivity (~ 25% Trot ?)
• Switching kVp within a single scan
• Energy discriminating detectors
layered detector, photon counting
Courtesy of Uri Shreter, GE Healthcare
better
immunity
to
motion
Strengths and limitations
• perfect beam hardening correction (pre-recon)
effective monoenergetic images
• extrapolation to high energies
more accurate RTP and N/M attenuation correction
• some material specificity (e.g., effective Z, DEI)
may provide disease specificity
improved image segmentation
Strengths and limitations
• virtual non-contrast image
perfectly registered and simultaneously acquired
Beware of noise propagation. Separate optimized scans
probably have lower total dose for same IQ
• isolate contrast media from calcified plaque
difficult, especially for small amounts of either
• molecular imaging?
I don’t think so
• “tomochemistry”
only with K-edge methods and relatively large concentrations
Thank You