AD
Dual-Energy
al Energ CT Based on A Double
Do ble Layer
La er
Detector
* All clinical images are courtesy of
Hadassah Medical Center, The Hebrew
University, Jerusalem
Ami Altman, Ph.D., and Raz Carmi Ph.D.,
CT BU, PHILIPS Healthcare
Content
1. The double-layer detector principle and operation
2 Advantages
2.
Ad
t
and
dd
drawbacks
b k off the
th Double-Layer
D bl L
approach
h
3. Material Decomposition method
4 The
4.
Th Double-Layer
D bl L
Energy
E
spectra
t compared
d to
t 80/140 kVp
kV spectra
t
5. The Effect of large noise in the Low_E image on material
decomposition
6. “Spectral resolving power” and simulated results to compare various
Dual-Energy CT method
7 D
7.
Decomposing
i specific
ifi materials
t i l from
f
mixtures,
i t
and
d quantitative
tit ti
Iodine maps
8. Clinical applications and results
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2
The Double-Layer Detector, Principle and Operation
A 0.150-mm side-looking photodiode array
y a 1.0-mm Tungsten
g
layer
y
shielded by
X-Rays Coming from top
0.030 mm optical glue
Top Scintillator,
Inter-Layer Filter
~50%
50%
Low Energy Raw data
1.0 mm
0.080 mm reflecting paint
Bottom
Scintillator:
Y
2-mm GOS
~50%
50%
E1 image
+
High Energy Raw data
E2 image
X
=
Weighted combined Raw data
1.
2.
3.
4.
CT image
For optimal performance the effective atomic number of the top scintillator
is small without sacrificing light output (better than GOS)
Top Scintillator thickness has been optimized for best energy separation
and low-energy image noise
The thin filter material and thickness has been optimized to attenuate < 3%
of the intensity entering the detector, and yet, significantly increase the
energy separation.
Bottom scintillator is GOS, the thickness of which set to absorb 99.5% of
the High-Energy spectrum (note that light collection is sideways)
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3
Advantages and Drawbacks of The Double Layer Approach
Main Advantages
1
1.
Si lt
Simultaneous
and
d equi-directional
i di
ti
l sampling
li off the
th scanned
d body
b d in
i the
th 2 energy bands
b d
2.
Enables both projection-based and attenuation-space (image-space) material decomposition
3.
The high
g energy
gy tail at the Low-Energy
gy Spectrum,
p
, enables low-noise at the Low-Energy
gy images
g
even for large patients. This has a significant advantage in the material spectral decomposition,
compensating for the larger overlap between the two spectra (see next slides)
4.
Enables a single-source dual energy CT with unlimited FOV for both axial and spiral scans, at all
protocols.
protocols
5.
Can work in a conventional CT mode by multiplexing (analog MUX) the two layers at each detection
pixel
6.
Very simple side-looking photodiode arrays that enable any expansion of the detector array at all
directions
7.
Work at normal CT dose, with a potential for significant dose reduction (high light output of front
scintillator)
Drawbacks:
1.
Energy overlap is larger than scanning with two kVp values due to the High-Energy tail at the
Low-Energy Spectrum (80/140). However, this has also an advantage, as explained in (2) above
2.
Requires more readout channels, and one more layer of scintillators, adding to DAS cost (partially
compensated by simpler and inexpensive photodiode arrays)
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4
Material Analysis Method With Dual Energy Spectral CT, Attenuation Space
NOTE that the attenuation coefficient (at CT energy range) is linear
with the density (concentration) for a specific effective atomic number
and energy (away from K
K-Edge)
Edge)
μ Z ,E
Z
Z3
≅ A⋅ ⋅ ρ + B ⋅ 3 ⋅ ρ
E
E
1.
On a µ-Space map, each material, characterized by its “effective atomic number”, is represented
along a straight line, the angle of which depends on its “effective Z” for a given energy set
2.
Angular difference between the representing lines of two specific materials with given atomic
number depends on the mean-energy difference between the two spectra
3.
The statistical “line width”, namely, the distribution of points along it, depends on the separate
spectra image noise,
noise as well as on the overlap between the two spectra.
spectra
Basically, an “effective atomic number” spectrometer
Iodine
Conventional CT Image
zoom
µ_E_L
Low (HU)
μE-Low (HU)
Zeff_1
1 > Zeff
Zeff_2
2 > Zeff_3
Zeff 3
Zeff_1
Zeff_2
Zeff_3
Calcium
water
Water (E_low & E_high = 0 HU)
μE-High (HU)
µ_E_High (HU)
A phantom with different concentrations of
Calcium and Iodine contrast agent
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5
Double-Layer Detector - Energy Spectra With / Without
35-cm Water Absorber
Energy Windows Obtained In A Double‐Layer CT Detector
From a 140 kVp X Ray Tube Air Only
From a 140 kVp X‐Ray Tube, Air Only
900000000
Δ<E>=31 keV
800000000
700000000
The drawback becomes an advantage:
dN/d
dE
600000000
500000000
400000000
300000000
<E_Low >= 63 keV
200000000
<E_High >= 94 keV
100000000
0
0
20
40
60
80
100
120
140
X‐Ray Energy (keV)
Spectrum_Low_E
Spectrum_High_E
2. Compare with 600 mAs 80 kVp
scans on adults,
adults where images
are very noisy, reducing
significantly tissue & material
separation
Low and High Energy Spectra 35 cm Water Absorber
Low and High Energy Spectra, 35 cm Water Absorber
3500000
3000000
Δ<E>=26 keV
2500000
dN/dE
1. The high-energy tail in the
Low_E spectrum, enables good
IQ (low-noise),
(low noise) even for large
patients.
2000000
1500000
<High_E>=101 keV
1000000
<Low_E>=75 keV
500000
0
0
20
40
60
80
100
120
140
X‐Ray Energy (keV)
Spectrum_E_low
Spectrum_E_high
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6
Compare With Dual kVp, 80 VS. 140 kVp – Spectral Difference
(No extra filter on 140 kVp beam)
140 VS. 80 kVp Spectra in Air
The CT image noise, for the same mAs,
obtained in the 80 kVp image, with 35-cm
water cylinder, is 9 times larger than that of
the 140 kVp image!!
40000000
dN/dE (#
#/keV)
35000000
30000000
Δ<E>=18 keV
25000000
20000000
<E_low>=53 keV
15000000
10000000
<E_high>=71 keV
5000000
0
0
20
40
60
80
100
120
140
X-Ray Energy (keV)
140kVp_Specrum
80kVp_Specrum
80 VS 140 kVp Spectra - 36
36-cm
cm Water
ALSO: A reasonably-seemed protocol of
200mAs at 140 kVp + 650mAs at 80 kVp would
still result in 3 times more noise in the 80 kVp
image
g (for
(
35-cm water cylinder).
y
)
30000
dN/dE (#/k
keV)
25000
Δ<E>=27 keV
20000
15000
<E_high>=88 keV
This would reduce severely the material
separation capability
10000
<E_low>=61 keV
5000
0
0
50
100
150
X-Ray Energy (keV)
140kVp_Specrum
80kVp_Specrum
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7
The Effect of Higher Noise in The Low-Energy Image
10 mM/L Iodine, SD=10 HU both E_Low and E_High; Gaussian fit
12
to the noise:
Separation is possible
10
8
10
8
6
4
2
Equivalent
concentration of Ca
to get the same HU
70 mM/L
I di in
Iodine
i
Water
6
1140
1120
1100
1080
1060
Low HU 1040
E
4
2
1140
0
1120
1200
1100
1150
1080
1100
1060
1050
1040
1000 1000
High HU
1050
1100
1150
1200
E
10 mM I,
I SD=15 HU E
E_Low,
Low =10 HU E
E_High;
High; Gaussian fit to
the noise:
10 mM/L
Iodine in
Water
Separation is almost impossible
12
10
70 mM/L I
8
Iodine
6
10
8
6
4
2
Ca
4
1160
1140
1120
1100
1080
1060
1040
1020
Low HU
E
2
1150
1100
0
1200
1150
1200
1150
1100
1050
HighE HU
10 mM I
1100
1050
1050
1000
1000
This is why in any Tube-Based Dual Energy CT,
CT one might be
forced to use 100/140 kVp instead of 80/140 kVp (a use of
filter on the high kVp, improves the poor spectral separation
of the 100/140 kVp combination.)
Water
8
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Spectral Resolving Power – An Objective Measure of the Material Decomposition Quality in Dual-E CT
Following conventions in 2D mass spectroscopy, and in a
combined
bi d Mass-TOF
M
TOF spectroscopy,
t
we define
d fi a “Spectral
“S
t l
Resolving Power”
10
8
6
4
2
1140
1120
1100
1140
1120
1080
1100
1060
1080
1060
1040
LowE HU
1040
1020
1000
1020
1000
HighE HU
Thus fit to the data from a standard phantom (with low
concentrations of Iodine and Calcium ((see previous
p
slide),
),
Two 2D Gaussian functions:
12
10
8
6
4
Than the Spectral Resolving power is defined:
2
0
1150
1100
1150
1100
1050
1050
1000
1000
950
950
RESOLVING_ POWER=
A+ B
∫ ( Gaussian# 1 U Gaussian# 2 )
2D
A
B
ile
of
Pr
Where A and B are the non overlapped volumes of the two
G
Gaussian
i functions
f
ti
, and
d the
th denominator
d
i t is
i the
th total
t t l volume
l
off
the union of the the two Gaussian functions
ne
Li
This takes in account all relevant factors: Image Noise, Mean
Energy
gy Difference,, patient
p
size,, spectra
p
overlap,
p, Mean Energy
gy of
each spectrum etc.
Note that the resolving power ≤ 1
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9
Simulations and Comparison Conditions
(GEANT4 [GATE] full CT Simulation)
1. Dual-Energy methods:
i.
Double-Decker Brilliance geometry and detector sizes with X-DFS, 2320
views, Single-Slice CT, axial 360-deg, scans 250 mAs, 140 kVp
ii. Dual-Source CT has been simulated using 2 scans with Brilliance geometry
and detector sizes with X-DFS, 2320 views, Single-Slice CT, axial 360-deg,
with 130 mAs at 140 kVp and 670 mAs at 80 kVp (Note that the dose per mAs
at 80 kVp is ~5.2 times less than in 140 kVp). Dual source CT has been
simulated with and without a Tin (Sn) filter (0.35 –mm thick).
iii. kVp Switching has been simulated with the same Brilliance geometry and
parameters as above, Using 1/8 scheme (1 view of 80 kVp every 8 views of 140
kVp), which is one of the best modes to overcome the sampling sparsity, with
130 mAs at 140 kVp and 670 mAs at 80 kVp (No Tin filter has been used)
iv. Photon Counting (for reference) 150 mAs (this the equivalent dose to ~250
mAs in Current Integration), 2 Energy Windows with no overlap has been
used. Same geometry and conditions as above
2.
Phantoms
i. 20-cm Water Cylinder with 4 test tubes as shown in slide 8
ii. 36-cm Water Cylinder with the same 4 test tubes
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10
Few Results Obtained From GEANT4 (GATE) Simulations *
Method
Spectral Resolving
Power:
Spectral
Resolving Power:
20-cm Phantom
36-cm Phantom
(10 mM/L I)
(10 mM/L I)
Comments
Dual-Source
0.61 ± 0.02
0.22 ± 0.02
80;140 kVp with Tin filter
Same dose for all
methods
Same dose for all
methods
Dual-Source
0.42 ± 0.02
0.30 ± 0.02
Energy separation is low ~19 keV with
th Ti
the
Tin filt
filter
0.54 ± 0.02
0.51 ± 0.02
All modes are possible for FOV up to
500mm
Fast kVp Switching 80;140 kVp (no
filter)
0.41 ± 0.02
0.21 ± 0.02
Cardiac questionable; Sparse sampling
affects both IQ and material decomp.;
Tin filter cannot be used, poor energy
separation
p
Fast kVp switching 100;140 kVp
0.22 ± 0.02
0.18 ± 0.02
Almost useless without a filter
Photon Counting CdTe, CdZnTe
0.75
0.66
2-Energy windows only;
100;140 kvp with Tin filter
Double-Decker Detector
1-mm Top ScintillatorÆ 0.025-mm
Tin Æ 2-mm GOS
80 kVp image noise is a serious
li it ti iin M
limitation
Medium-large
di
l
patients;
ti t
Hard to apply to gated\tagged CCTA;
Limited FOV
Assuming 10% energy resolution, and
no rate limit
*Attenuation & Beam Hardening corrections have been applied for all methods
(See R. Carmi, A. Altman, G. Naveh MIC IEEE 2005)
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11
Materials Decomposition (e.g. Contrast Agents) in Mixtures
µE1 ((HU))
1. Any material concentration varies along the
specific material spectral line (water at the origin in
HU scale)
Z1
2. Image locations with 2-material mixtures of Z1 and
Z2 (easily generalizeable to more than 2 materials)
can be quantified easily through simple vector
r r r
calculations
X
µE1
Z2
α
1α
1E1
W
X =α + β
β
µE2 (HU)
1β
3. Add adaptive diffusion filter and proper statistical
noise analysis to refine material separation
(assuming Gaussian noise in the spectral map)
µE2
1E2
Iodine + Carbon Iodine Calibration: 100% Iodine Image
1.
Accurate quantification of
Iodine contrast agent in
Iodine+Carbon Mixtures
2.
Carbon-based polymer
mixed with Clinical Iodine
Contrast (Ultravist) have
been used
3.
Measured in the Dual-Layer
CT using a 25-cm Plexiglas
phantom diameter, with
inserts
51.8%
0%
1
2
2.3%
8
3
Carbon Image
7
Iodine
Calcium
100%
4
6.3%
Carbon
5
9.3%
6
0%
15.4%
CT image
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Dose/Noise Effect on Material Decomposition
I di iimages Energy
Iodine
E
M
Map
800 mAs
The same p
phantom,,
different scan dose
50 mAs
15 mAs
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13
Clinical Images, Obtained with A Dual-Layer Detector Spectral CT
2.
2
3.
A Philips Brilliance-64 with a Double-Layer Detector operates routinely in Hadassah Medical Center,
at the Hebrew University in Jerusalem.
D lE
Dual
Energy scans are performed
f
d att 140 kV
kVp with
ith conventional
ti
l dose,
d
≤ 250 mAs
A ffor all
ll protocols
t
l
All images are courtesy of Hadassah MC, and Dr. Jacob Sosna, Head of the CT unit there.
140 kV 250 mAs
Separation line
1.
Iodine
HU o
of E1
1.
2.
Calcium
3.
H 2O
HU of E2
Iodine-tagged blood well separated
from blood-vessel calcifications and
bones
Soft-tissue (muscles) are well
separated even from low
lowconcentrated Iodine regions
Different materials / tissues are
overlayed with colors on the
anatomic image
Soft tissue separation from Iodine contrast and from bones:
Soft Tissue
Iodine-tagged Blood
Calcium & Bones
Fat
Spectral Analysis Map
HU of E1
Calcium
Iodine
Soft tissue
Conventional CT Image
Spectral CT Image, Dual-E
HU of E2
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Virtual Non Contrast Image Generation
(for algorithms & methods see L. Goshen, A. Altman & R. Crami MIC2008 IEEE)
250 mAs
250 mAs
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Advanced Iodine Perfusion Maps, Tissues/Material Decomposition
Main Procedure:
Dual Energy
Images
Noise Removal,
preserving
Spectral Map
information
Noise
Level
Estimate
Raw energy map
1800
Noise free energy map
1800
1700
1700
1600
1600
1500
1500
1400
1400
1300
1300
1200
1200
1100
1100
1000
Estimate of
Material
Response
Vector
Iodine
Color
Map
Iodine Map
Generation
1000
900
900
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
A tiny lung nodule detected on an Iodine-map
Iodine map image
(b), obtained with a PHILIPS Dual-Energy CT
a
b
Note that on the conventional CT Image (obtained
simultaneously during the same scan), the LungN d l looks
Nodule
l k as a normall Iodine-Tagged
I di
T
d blood
bl d
vessel
Conventional CT
Spectral Iodine Maps
Conventional CT
Iodine Image
A detected non-Perfused
Lung Nodule (Tumor)
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Towards Prepless CT Colonoscopy with Dual-Energy CT
Nominal Virtual-Colonoscopy scan protocol and dose
a
b
The colon is partially
filled with stool and
b th Iodine
both
I di and
d
Barium contrast
agents
Corrupted
colon wall
d
c
Non-cleansed
residuals
Conventional-CT
electronic cleansing
with high
g and low HU
thresholds only
Electronic
cleansing
with dual-energy
analysis
11
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17
Towards Prepless CT Colonoscopy with Dual-Energy CT (cont.)
Compare Mode
Conventional Electronic Dual Energy Electronic
Cleansing
Cleansing
Bowel is still full of stool
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18
Towards Prepless CT Colonoscopy with Dual-Energy CT (cont.)
Conventional
Electronic Cleansing
Dual Energy
gy
Electronic Cleansing
A false polyp caused by
residual stool
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19
Quantifying Composites of Tissues Mixtures, Soft-Plaque Characterization
Vulnerable
Plaque in
Carotids
Purple
indicates high lipidic
component in plaque
Lumen
Calcification
Soft Plaque
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Kidneys Stones Identification and Quantification
+
Brushite
+ Calcium Oxalate
y
=
monohydrated
Brushite
+ Cystine
+ Urique acid
Uric Acid
In-Vivo Kidneys Stone
analysis, using a Calibration
Phantom
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21
Simultaneous Multi-Phase Imaging Using Contrast Agents
Mix, injected in Separate times
1. Plaque-induced NWZ Rabbits, through cholesterol-rich diet
2. Early injection of targeted Iodine-Loaded nano-particles contrast agent,
highly up-taken by Macrophages (N1177 NPC, developed and
y NanoScan Imaging,
g g, Lansdale,, PA))
manufactured by
3. Late injection (hours) of Gd Contrast-Agent (Magnevist 280)
4 Scanning to image simultaneously both plaque and lumen
4.
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22
Demonstrating Material separation: Iodine vs. bone + gadolinium
A) N1177 (iodine) + gadolinium.
Scan 4 hours
Scan:
ho rs after N1177
injection and immediately
after gadolinium injection
B)) Material separation
p
with dual-energy
gy
spectral analysis shows the differentiation
between iodine to gadolinium and bone
B
A
bone and
gadolinium
iodine
Gadolinium contrast
material in the heart
Iodine nanoparticles
contrast
material in the spleen
Gadolinium contrast
material in the heart
Iodine nanoparticles contrast
material in the spleen
Note that the spleen is rich with Macrophages !
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23
A) N1177 (iodine nanoparticles)
Scan: 2 hours after injection
A
A first example showing possible plaque
in the aorta
B) N1177 (iodine) + gadolinium. C) Material separation with dual-energy
spectral analysis shows the differentiation
Scan: 4 hours after N1177
between iodine in the soft plaque and
injection and immediately
gadolinium in the aorta lumen
after gadolinium injection
B
C
139 HU
Iodine nanoparticles
captured in soft plaque.
Max. intensity after 2 h,
reducing
g after 4 h
soft plaque
(iodine)
122 HU
Gadolinium enhancement
of the aorta lumen
- can help in areas where
th lumen
the
l
walls
ll are less
l
clear
134 HU
gadolinium
bone and gadolinium
iodine
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24
A Second Example, Soft-Plaque Imaging Simultaneously with The Lumen
A) N1177 (iodine nanoparticles)
Scan: 2 hours after injection
A
B) N1177 (iodine) + gadolinium.
Scan: 4 hours after N1177
injection and immediately
after gadolinium injection
C) Material separation with dual-energy
spectral analysis shows the differentiation
between iodine to gadolinium and bone
B
bone
C
bone
bone and
gadolinium
iodine
Possibly some
captured iodine inside
plaque in the aorta walls
iodine nanoparticles
concentrated in the spleen
iodine nanoparticles
concentrated in the spleen
Possibly some captured
iodine inside plaque in
th aorta
the
t walls
ll and
d
gadolinium enhancement
of the aorta lumen
probably: plaque / lumen
(iodine / gadolinium) dif f erentiation
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25
25
Philips Healthcare, 2008
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