Current status and recent innovations
Co-moderators:
Norbert J. Pelc, Sc.D.
Stanford University
Cynthia McCollough, Ph.D.
Mayo Clinic
Multi-Energy CT:
Current status and recent innovations
Basic concepts & current implementations
Norbert Pelc
Data and image analysis methods
Lifeng Yu
Clinical applications
Cynthia McCullough
Future directions
Taly Gilat Schmidt
Panel Discussion
Basic concepts & current implementations
Norbert J. Pelc, Sc.D.
Departments of Bioengineering and Radiology
Stanford University

Acknowledgements
Uri Shreter and Robert Senzig: GE Healthcare
Thomas Flohr, Bernhard Schmidt and Karl Krzymyk: Siemens
Healthcare
Ami Altman, Alex Ganin, Andy Mack, Efrat Shefer: Philips
Healthcare
Cynthia McCollough: Mayo Clinic
Research support:
GE Healthcare
Philips Healthcare,
Samsung Electronics
Motivation www.uhrad.com/ ctarc/ct153b2.jpg
Lower density or lower atomic number?
Motivation www.uhrad.com/ ctarc/ct153b2.jpg
Is the HU increase due to underlying tissue property or contrast agent?

Motivation
TN Sheth, et al, CARJ 56, 15, 2006.
Can we separate iodine and calcium, or reduce blooming?
Attenuation coefficients depend on photon energy
100
10 iodine
1
0.1
35 55 bone water
75 95 photon energy
115 135 use CT measurements at multiple energies to add material specificity
Motivation
“ Two pictures are taken of the same slice, one at 100 kV and the other at 140 kV...so that 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.

OUTLINE
• Physical principles of multi-energy x-ray measurements
• Implementations achieving spectral selectivity obtaining multi-energy measurements
• Summary
I
0 attenuation and
material identification
T measures product of  & T not very material specific
I = I
0 e  T
 T = ln(I
0
/ I)
I
01 energy E1 unknown thickness
two known materials
100.0 I
02
E2
10.0
E1 E2 water
1.0 water cortical
bone t b bone
0.1
10 20 50 photon energy (keV)
100 200
I
1
I
2
I
1
= I
01 e -(
 w1 t w
 +  b1 t b
)
I
2
= I
02 e -(
 w2 t w
 +  b2 t b
) solve for t w
and/or t b

dual energy x-ray absorptiometry
(DEXA)
2 energies 2 materials material analysis with absorptiometry
• 2 energies 2 materials
• can we generalize this? N energies for N materials?
• limitation: two strong interaction mechanisms
Compton scattering and photoelectric absorption
Barring a K-edge in the spectrum, the energy dependence of each is the same for all elements!! basis material decomposition:
• Attenuation of any material is ~ a weighted sum of photoelectric and Compton functions
• Any material can be modeled as a weighted sum of two other materials (basis materials)

Basis material decomposition
1000
100
Cu
10
Ca
1
O
.61*O + .04*Cu
0.1
0 20 40 60 80 100 120 140
O
Ca
Cu
Ca'
Basis material decomposition
I
0
I
0
.04 M grams of Cu
.61 M grams of O
= M grams of Ca
I I
Indistinguishable at any x-ray energy above their K-edge
Common “ basis functions ” : iodine and water, aluminum and plastic photoelectric and Compton

material analysis with absorptiometry
• 1 energy
constant thickness
• 2 energies
unknown thickness
• N energies
unknown thickness
• 2 energies
constant thickness
2 known materials
(constant thickness is a constraint)
2 known materials still only 2 known materials
(only 2 independent functions)
3 known materials
(constant thickness (CT voxel) is a constraint)

K-edges
100.0
10.0
1.0 water cortical
bone iodine
0.1
10 20 50 photon energy (keV)
100 200
Very specific material information low energy iodine image
SNR=3.4
Noise high energy water image
Iodine data ~
a • Data low
- b • Data high
  ~ a 2  low
 + b 2  high
 depends on:
- specific energies
- allocation of dose to the two measurements
SNR=37
Noise depends on dose allocation iodine image water image with 80/140 kVp dose allocation that maximizes iodine SNR
SNR=3.4 iodine image
SNR=37 water image
80 kVp dose, 140 kVp dose same total dose
SNR=1.3 SNR=34

Spectral separation and control
• very critical for SNR efficiency, separation robustness, etc.
• implementations different kVp and/or filtration detectors with energy discrimination
Principle of Dual Energy CT
Data acquisition with different X-ray spectra: 80 kV / 140 kV
Mean Energy :
56 kV 76 kV
Tube 1
Tube 2
Different mean energies of the X-ray quanta
Courtesy of B. Krauss, B. Schmidt, and
Th. Flohr, Siemens Medical Solutions syngo Dual Energy
- Principle of Dual Energy
SOMATOM Definition Flash
SPS= Selective Photon Shield
S S
1 1
: 80 kV
15 x 10 4
2 2
5 5
0 0 100
+ SPS
80 kV
140 kV
140 kV + SPS
150

Dual kVp, dual filtration
85 kVp
0.1 mm erbium
• switched filtration improves separation
• different mA helps apportion dose
135 kVp
1.5 mm bronze
Lehmann et al: Med Phys 8, 659-67, 1981.
NanoPanel Prism
Perfect alignment
Slide 6 – Learn More 1
Simultaneous alignment in time and space
X-Rays
Top Scintillator
Bottom
Scintillator:
2-mm GOS+
Side-looking photodiode array
Low Energy Raw data
High Energy Raw data
Combined Raw data
E1 image
E2 image
CT image
Full CT Image
Top scintillator
Effective atomic number small but does not sacrifice light output
Thickness optimized for energy separation and low-energy image noise
Bottom scintillator absorbs 99.5% of high-energy spectrum
The IQon Spectral CT is not yet CE Marked and not available for sale in all regions.
The IQon Spectral CT is pending 510(k) and not available for sale in the USA.
Layered detector
• relatively poorer spectral separation
• simultaneous dual energy sensing
Carmi R, Naveh G, and Altman A: IEEE
NSS M03-367, 1876-78, 2005

High
Voltage
Photon Counting Spectral CT
– Detector Principle
Absorbed single X-ray photon (CZT crystal: Cadmium Zinc Telluride)
Direct conversion material
Pixelated electrodes
Electronics
Discriminating thresholds
Counter 4
Counter 3
Counter 2
Counter 1
Charge pulse
Pulse height proportional to x-ray photon energy
Stored counts of all energy windows, for each reading time period
Counts
Photon energy
Direct- Conversion Detector efficiently translates X-ray photons into large electronic signals
These signals are binned according to their corresponding X-ray energies
Spectral separation
Separation and control of the spectra is important reduced noise improved material characterization improved dose efficiency
Achieved by choice of kVp (and mAs allocation) use of filtration performance of energy discriminating detectors
Spectral separation implementations
• ideal photon counting with K-edge filter
• ideal photon counting with energy analysis
• different kVp and filtration
• different kVp
• layered detector better spectral separation and dose efficiency

Data acquisition implementations
• Sequential scans at different kVp motion sensitivity > scan time
• Two sources at ~90º on the same gantry syngo Dual Energy
- Principle of Dual Energy
SOMATOM Definition Flash
Two X-ray tubes, 1st: 80 or 100 kVp, 2nd: 140 kVp
Dual Source Challenge: Inconsistent scans
Moving Objects
Moving Phantom
Simulation
Ideal
Does not see movement
Dual Source system
Courtesy of R. Senzig, GE Healthcare

Data acquisition implementations
• Sequential scans at different kVp motion sensitivity > scan time
• Two sources at ~90º on the same gantry some motion sensitivity (~ 25% T rot
)
• Switching kVp within a single scan 1, 2
1. Lehmann et al: Med Phys 8, 659-67, 1981.
2. Kalender et al, Med Phys 13, 334, 1986.
Rapid kVp switching
Dual energy CT
• Requires fast generator and detectors
• Dose allocation controlled by dwell time
• Difficult to switch filters
Courtesy of Uri Shreter, GE Healthcare
Data acquisition implementations
• Sequential scans at different kVp motion sensitivity > scan time
• Two sources at 90º on the same gantry some motion sensitivity (~ 25% T rot
)
• Switching kVp within a single scan
• Energy discriminating detectors layered detector, photon counting better immunity to motion

Summary of commercial systems
• Siemens: two sources, different kVp (80 or 100
/140) and filtration, direct control of mA
• GE: single source with rapid switching, same filter for both kVps, control mAs by dwell time
• Philips: dual-layer detector, usual kVp mAs control
• Lots of R&D work, especially on photon counting detectors