ct imaging using energy-sensitive photon-counting detectors

1

CT imaging

using energy-sensitive

photon-counting detectors

Katsuyuki “Ken” Taguchi, Ph.D.

[email protected]

Division of Medical Imaging Physics

Department of Radiology

Johns Hopkins University

Disclosure No financial interest

Research grants

Siemens Healthcare

Past relationships/grants

Former employee of Toshiba Medical Systems

Former Co-I of a project funded by Philips Healthcare

AHA, NIH R01 and SBIRs (DxRay)

Consultant

Life Saving Imaging Technology (LISIT) (Tokyo, Japan)

2 K. Taguchi (JHU) – AAPM, July 12-16, 2015

Vision 20/20 paper

Detector technology

Imaging technology

System technology

Potential clinical benefits

Med Phys 40(10), 100901 (19 pages) (2013)

K. Taguchi (JHU) – AAPM, July 12-16, 2015

2

Outline

Current CT detectors to higher dose exams

Low-dose CT by integrating 3 technologies

Photon counting detectors (PCDs)

Iterative reconstruction for PCDs (PIECE)

Joint estimation with tissue types (JE-MAP)

Whole-body prototype PCD-CT system

Other clinical merits of PCD-CT


Major problems of current CT

Relatively high-dose procedure

Insufficient contrast between tissues

CT images are not tissue-type specific

Pixel values, Hounsfield units or linear

atten. coeff., are not quantitative but

qualitative


Energy weighted integration

0.0E+00

5.0E+05

1.0E+06

1.5E+06

0 20 40 60 80 100 120 140Energy [keV]

Nu

mb

er

of

ph

oto

ns

n(E

)

Incident Transmitted Weighted by E


3

Energy binning for spectral CT

7

0

0.5

1

1.5

20 40 60 80 100 120

u(E, blood)

u(E, Gd)

u(E, dry_spine)

u(E, dry_rib)

u(E, iodine)

u(E, bismuth)

Gd-blood (0.26%)

I-blood (0.49%)

Bi-blood (0.49%)

Energy [keV]4020 8060 120100

0.0

0.5

1.0

Linear attenuation coefficient [cm-1]

Rib

Spine

Iodine-mixed blood

Gd-mixed blood

BiBi--mixed bloodmixed blood

Water

4020 8060 120100

Energy [keV]

0

Transmitted x-ray spectrum [A.U.]

0.00E+00

2.00E-04

4.00E-04

6.00E-04

8.00E-04

1.00E-03

1.20E-03

1.40E-03

20 40 60 80 100 120

Gd

Iodine

Blood onlyBismuthBismuth

Four materials would provide an

identical pixel value if scanned

with current CT

Transmitted spectra with 25 cm

water and 5 cm blood w/ or w/o

contrast agents


Strategy for low-dose CT

8

Technologies Relative amount of

dose reduction

Liver CT

(mSv)

Current CT system with FBP*1 N/A 10

Photon counting detectors (PCDs) 30–40 % 6–7

Iterative reconstruction for PCDs (PIECE) >35 % 3.9–4.6

Joint estimation with tissue types (JE-MAP) >35 % 2.6–3.0

Note 1. Dose for current CT with iterative reconstruction may be 6–8 mSv

Combine the following 3 technologies:

Note 2. Annual background radiation: 3.1 mSv



9


dose reduction

Liver CT

(mSv)









4

Photon counting detector

(PCD) Incident x-ray

Photon to charge

Charge measured, counted,

and stored digitally

- -

- -

Amplifier

Counting

processing

Courtesy of W. Barber, Ph.D. and J. Iwanczyk, Ph.D. (DxRay, Inc)


Detection mechanism

Time

Pulse height = photon energy

N2

N1 Threshold #1

Threshold #2

Threshold #3 N3

n1 = N1 – N2

n2 = N2 – N3

n3 = N3

11

Shaper

Preamp

Counter 2Digital output

Thresholds to pulse height comparators

DAC

Comparators

Counter 1Digital outputDAC

Counter NDigital outputDAC

… …Input

analog

pulses

“Spectral response (SR)”

12

A 90 keV photon

time

60 keV

time

30 keV “Charge sharing”

Incident x-ray photons (a) (c) (b) (d)

Anode

Sensor

5

“Spectral response (SR)”

13

Continuum:- Charge trapping- K-escape- Charge sharing- Compton scatter

0 20 40 60 80 100

Energy [keV]

Co

un

ts

Response to 59.5 keV photons (Am-241 source)

Photo peak

Noise floor

20 40 60 80 100

Energy [keV]120

Pro

bab

ility

[a.

u.]

Incident spectrum

Recorded spectrum

Incident x-ray photons (a) (c) (b) (d)

Anode

Sensor

Pulse pileup

14

Time

Pulse height (photon energy)

Time

Events on detector

Live

Dead

True pulses

Observed pulses

Pulse pileup spectrum

True

Recorded

Energy [keV]

Pro

babili

ty

Input count rate [Mcps]

Outp

ut

count

rate

[M

cp

s]

10 20 30 40 50 0

10

Paralyzable detector

( =20 ns)

Non-paralyzable detector

( =20 ns)

True 20

30

Count rate loss

Spectral distortion

Spectral response (SR): Charge sharing,

K-escape, Compton, etc.

Larger, slower PCD

Pulse pileups

Smaller, faster PCD

Pulse height (photon energy)

True pulses

Observed pulses

Incident x-ray photons(a) (c)(b) (d)

Anode

Sensor


6


16


dose reduction

Liver CT

(mSv)









Image artifacts due to SR and PP

X-ray focus

PCD

Ray

PCD pixels

Energy, E

nt(E)

nR(E)

Energy, E

Energy, E

n0(E)

Object, x(E)nt(E)

Bowtie filters

y={y1, y2, y3, y4}

Observed spectrum

Recorded counts

x={x1, x2, x3, x4}

Reconstruct images


Image artifacts due to SR and PP

X-ray focus

PCD

Ray

PCD pixels

Energy, E

nt(E)

nR(E)

Energy, E

Energy, E

n0(E)

Object, x(E)nt(E)

Bowtie filters

y={y1, y2, y3, y4}

Observed spectrum

Recorded counts

x={x1, x2, x3, x4}

Reconstruct images

x2

18

[cm-1]

Photon energy [keV]

Photoelectric

K-edge(Iodine)

Compton Scattering

𝑥 𝐸 = 𝑤𝑚Ψ𝑚 𝐸

𝑚


7

PCD compensation

X-ray focus

PCD

Ray

PCD pixels

Energy, E

nt(E)

nR(E)

Energy, E

Energy, E

n0(E)

nt(E)Bowtie filters

y={y1, y2, y3, y4}

Observed spectrum

Recorded counts

Line integrals,Wj

𝑝 𝑦 𝑣

Estimate object v by maximizing the likelihood 19

PIECE = Physics-modeled Iterative reconstruction for

Energy-sensitive photon Counting dEtector

𝑣

PCD model

20

1: J. Cammin, Med. Phys. 41: 041905 (2014) 2: K. Taguchi, Med. Phys., 37: 3957 (2010)

3: K. Taguchi, Med. Phys., 38: 1089 (2011)

Transmitted spectrum

Spectral response

Pulse pileups

Recorded spectrum

Energy

Energy

𝑛𝑅 𝐸 = 𝑛𝑆𝑅𝐸 𝐸 𝑃𝑟 "𝑟𝑒𝑐" = 1

× 𝑃𝑟 𝑙 "𝑟𝑒𝑐" = 1 𝑃𝑟 𝐸 𝑙

𝑙

𝑛𝑆𝑅𝐸 𝐸 = 𝑎𝑆𝑅𝐸 𝐸, 𝐸𝑘 𝑛𝑡 𝐸𝑘

𝑘

𝒏𝑺𝑹𝑬 = 𝐴𝑆𝑅𝐸𝒏𝒕

or

Spectral response1

Pulse pileups2,3

l = # of photons piled up for one recorded count

Monte Carlo simulation study

for Siemens PCD

21

J. Cammin, presented at IEEE NSS/MIC 2014

20 40 60 80 100 120 140 160 1800

100

200

300

400

500

600

700

Energy (keV)

Counts

/keV

H2O, Al

P, unipolar

It = 25 mA

DLR = 0.9%

COVW

= 2.4%

measured

SRE+PPE((E))

SRE, DL

transmitted, DL

20 40 60 80 100 120 140 160 1800

2000

4000

6000

8000

10000

12000

14000

16000

Energy (keV)

Counts

/keV

H2O, Al

P, unipolar

It = 800 mA

DLR = 25.3%

COVW

= 1.5%

measured

SRE+PPE((E))

SRE, DL

transmitted, DL

Energy (keV)20 60 100 140

Energy (keV)20 60 100 140

Co

un

ts/k

eV

0

700

Co

un

ts/k

eV

0

DE only

SRE+DE

SRE+pileups

PCD data

16,000

DE only

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

0.0 20.0 40.0 60.0 80.0

CO

VW

(%)

deadtime loss ratio: 1-nrecorded/nt (%)

SRE+PPE, P, unipolar, no Gd

SRE x DL, P, unipolar, no Gd

SRE, P, unipolar, no Gd

trans x DL, P, unipolar, no Gd

trans, P, unipolar, no Gd

800 mA

200 mA

100-DE (%)

25 mA 800 mA

100 mm water, 3.5 mm Al, 0.9 mm Ti; 120 kVp;

pulse height analyzer; unipolar pulse

DE = Detection efficiency (%) COVw = Weighted coefficient of variation (%)

SRE+DE

SRE+pileups

PCD data

8

Evaluation of PIECE-1

22

CNR 6.0 CNR 6.0

CNR 4.9 CNR 4.1


23


dose reduction

Liver CT

(mSv)









Joint estimation with tissue types

24

Sinogram

𝒚

𝐸

Characteristic coefficients

𝒘

Projection

noise

Tissue type

𝒛

K. Nakada, et al., IEEE MIC (2013); Med Phys (2015)

9



25

Sinogram

𝒚

𝐸


𝒘

Projection

noise

Geometry

Statistical relationship

Tissue type

𝒛

location

blood muscle

𝒛𝑖 = 𝒛𝑗 = blood

→ 𝛼 𝒘𝑖 − 𝒘𝑗2

𝒛𝑖 ≠ 𝒛𝑗

→ 𝛽

Smooth

Discontinuous

𝑤pe

𝑤cs

0.00

0.10

0.20

0.00 0.10 0.20 0.30 0.40

lung fat

livermuscle

Iodine-mixed

blood

spine

rib


26

Sinogram

𝒚

𝐸


𝒘

Projection

noise

Tissue type

𝒛

𝒘

location

𝒛 blood muscle

𝒛𝑖 = 𝒛𝑗 = blood

→ 𝛼 𝒘𝑖 − 𝒘𝑗2

𝒛𝑖 ≠ 𝒛𝑗

→ 𝛽

Smooth

Discontinuous


Geometry

Statistical relationship

27 @70keV, WW 400HU, WL -50HU

FBP

PML JE-MAP

Truth

K. Nakada, CERN wrokshop (2015)

10

28 @70keV, WW 400HU, WL -50HU

PML JE-MAP

FBP Truth

K. Nakada, CERN wrokshop (2015)


29 K. Nakada, et al., IEEE MIC (2013)

FBP

PML

JE-MAP

by 33%: PML JE-MAP

Noise reduction at FWHM=3 pixels

by 30%: FBP PML

by 53%: FBP JE-MAP


Photon counting low-dose CT

30

Current CT detectors lead to higher dose exams






dose reduction

Liver CT

(mSv)






11

Outline

Current CT detectors to higher dose exams






Other clinical merits of PCD-CT



Developed by Siemens, installed at Mayo Clinic Dual-source CT, EID for 50 cm, PCD for 27.5 cm

(225 m)2 pixel, 2 thresholds (staggered 4 thresholds)

128x106 counts/s/mm2 with 13.5% loss, 256x106 with 25.2% loss

Shading artifacts due to energetic cross-talks (not shown)

32

Cadavers In-vivo swines

Courtesy of Cynthia H. McCollough, Ph.D. (Mayo Clinic)

Clinical benefits of spectral CT

1) Contrast-to-noise ratio (CNR) and contrast of CT images, or doses of radiation & contrast agents

2) Quantitative CT imaging

3) Material- or tissue type-specific imaging

4) Accurate K-edge CT imaging

5) Simultaneous multi-agent imaging

6) Molecular CT with nanoparticles

7) Personalized medicine

33

Improvement of current CT images

New class of CT imaging

K Taguchi, Med Phys 40(10), 100901 (19 pages) (2013)

12

Molecular CT with nanoparticle contrast agents or probes

D. Pan, Angew Chem Int Ed 49: 9635-9639 (2010)

Bi

34

Imaging macrophages in atherosclerotic plaques

F. Hyafil, Nat Med 13(5): 636-641 (2007)

Conventional

Injection

Nano agent

Nano agent Conventional

agent

Nano agent

35

The use of PCDs and coded-aperture for

simultaneous absorption, phase, and differential phase contrast imaging

M. Das, AAPM 2015, TH-AB-204-07 (8:30 am)

36

Absorption Phase Diff. phase

Low-dose single scan followed by

a novel retrieval algorithm

5cm average breast tissue

1.5 mGy dose

6 energy bins, CdTe detector

13

Summary

Current CT detectors cause the major limitations of

CT images

PCDs address them and enable new applications





A few whole-body prototype PCD-CT systems

being evaluated at hospitals


Acknowledgment Kenji Amaya, Ph.D. (TITech)

Kento Nakada, B.Sc. (TITech)

Cynthia H. McCollough, Ph.D. (Mayo Clinic)

Jan S. Iwanczyk, Ph.D. (DxRay, Inc)

William Barber, Ph.D. (DxRay, Inc)

Neal E. Harsough, Ph.D. (DxRay, Inc)

Steffen Kappler, Ph.D. (Siemens Healthcare)

Thomas G. Flohr, Ph.D. (Siemens Healthcare)

Karl Stierstorfer, Ph.D. (Siemens Healthcare)

Eric C. Frey, Ph.D. (JHU)

Jochen Cammin, Ph.D. (JHU)

Somesh Srivastava, Ph.D. (JHU)

Benjamin M.W. Tsui, Ph.D. (JHU)

Current and former students and colleagues in DMIP and JHU


14

Shaper

Preamp

Counter 2 Digital output

Thresholds to pulse height comparators

DAC

Comparators

Counter 1 Digital output DAC

Counter N Digital output DAC

…

…

Input

analog

pulses

Clinical benefits of spectral CT 1) Contrast-to-noise ratio (CNR) and contrast of CT images,

or doses of radiation & contrast agents

2) Quantitative CT imaging

3) Material- or tissue type-specific imaging

4) Accurate K-edge CT imaging by >2 energy windows

5) Simultaneous multi-agent imaging



42

Sinogram

𝒚

𝐸


𝒘

Projection

noise

Tissue type

𝒛

𝒘

location

𝒛 blood muscle


ct imaging using energy-sensitive photon-counting detectors

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