CT imaging using energy-sensitive photon-counting detectors Katsuyuki Ken Taguchi, Ph.D. ktaguchi@jhmi.edu Division of Medical Imaging Physics Department of Radiology Johns Hopkins University No financial interest Research grants Siemens Healthcare Disclosure 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 Vision 20/20 paper Detector technology Imaging technology System technology Potential clinical benefits Med Phys 40(10), 100901 (19 pages) (2013) 1
Number of photons n (E) 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 4 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 5 Energy weighted integration 1.5E+06 1.0E+06 5.0E+05 0.0E+00 0 20 40 60 80 100 120 140 Energy [kev] Incident Transmitted Weighted by E 6 2
Energy binning for spectral CT Linear attenuation coefficient [cm -1 ] Transmitted x-ray spectrum [A.U.] 1.5 Rib Bismuth 1.40E-03 Blood only 1.20E-03 Iodine-mixed blood u(e, blood) 1.01 0.5 0.00 20 40 60 80 100 120 Energy [kev] 1.00E-03 u(e, Gd) u(e, dry_spine) Gd-mixed blood u(e, dry_rib) 8.00E-04 u(e, iodine) Gd u(e, bismuth) Bi-mixed blood 6.00E-04 Gd-blood (0.26%) I-blood (0.49%) Spine Bi-blood (0.49%) 4.00E-04 Iodine 2.00E-04 Water Four materials would provide an identical pixel value if scanned with current CT 0.00E+000 40 20 80 100 60 120 Energy [kev] Transmitted spectra with 25 cm water and 5 cm blood w/ or w/o contrast agents 7 Strategy for low-dose CT Combine the following 3 technologies: 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 Note 2. Annual background radiation: 3.1 msv 8 Strategy for low-dose CT Combine the following 3 technologies: 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 Note 2. Annual background radiation: 3.1 msv 9 3
Photon counting detector (PCD) Incident x-ray Amplifier Photon to charge Charge measured, counted, and stored digitally - - - - Counting processing Courtesy of W. Barber, Ph.D. and J. Iwanczyk, Ph.D. (DxRay, Inc) 10 Detection mechanism Thresholds to pulse height comparators Comparators DAC Counter 1 Digital output Input analog pulses Shaper DAC Counter 2 Digital output Preamp DAC Counter N Digital output Pulse height = photon Threshold #3 energy N 3 Threshold #2 N 2 n 3 = N 3 n 2 = N 2 N 3 Threshold #1 N 1 n 1 = N 1 N 2 Time 11 Spectral response (SR) Incident x-ray photons (a) (b) (c) (d) Sensor Anode A 90 kev photon 60 kev time 30 kev Charge sharing time 12 4
Probability Output count rate [Mcps] Counts Probability [a.u.] Spectral response (SR) Incident x-ray photons (a) (b) (c) (d) Sensor Anode Response to 59.5 kev photons (Am-241 source) Noise floor Continuum: Photo peak - Charge trapping - K-escape - Charge sharing - Compton scatter Incident spectrum Recorded spectrum 0 20 40 60 80 100 Energy [kev] 20 40 60 80 100 Energy [kev] 120 13 Pulse height (photon energy) Observed pulses True pulses Pulse pileup 30 20 Count rate loss Non-paralyzable detector ( =20 ns) True 10 Paralyzable detector ( =20 ns) 0 10 20 30 40 50 Input count rate [Mcps] Dead Live Time Pulse pileup spectrum True Recorded Time Events on detector Energy [kev] 14 Spectral distortion Spectral response (SR): Charge sharing, K-escape, Compton, etc. Larger, slower PCD Incident x-ray photons (a) (b) (c) (d) Sensor Anode Pulse pileups Smaller, faster PCD Pulse height (photon energy) Observed pulses True pulses 15 5
Strategy for low-dose CT Combine the following 3 technologies: 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 Note 2. Annual background radiation: 3.1 msv 16 Image artifacts due to SR and PP X-ray focus Bowtie filters n 0 (E) Object, x(e) Energy, E PCD n t (E) Ray PCD pixels Observed spectrum n R (E) n t (E) Energy, E Recorded counts y={y 1, y 2, y 3, y 4 } Reconstruct images Energy, E x={x 1, x 2, x 3, x 4 } 17 Image artifacts due to SR and PP x 2 X-ray focus Bowtie filters n 0 (E) x E = Object, x(e) m Energy, E PCD w m Ψ m E PCD pixels Ray [cm -1 ] n t (E) Observed spectrum n R (E) n t (E) Photoelectric Energy, E Compton Scattering Recorded counts K-edge(Iodine) y={y 1, y 2, y 3, y 4 } Reconstruct images Energy, E x={x 1, x 2, x 3, x 4 } Photon energy [kev] 18 6
COV W (%) Counts/keV Counts/keV 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 Counts/keV X-ray focus PCD compensation PIECE = Physics-modeled Iterative reconstruction for Energy-sensitive photon Counting detector PCD Line integrals, Bowtie v W j filters n 0 (E) n t (E) Ray PCD pixels Observed spectrum n R (E) n t (E) Energy, E Recorded counts y={y 1, y 2, y 3, y 4 } Energy, E p y v Energy, E Estimate object v by maximizing the likelihood 19 Energy Spectral response Pulse pileups Recorded spectrum Energy 1: J. Cammin, Med. Phys. 41: 041905 (2014) 2: K. Taguchi, Med. Phys., 37: 3957 (2010) 3: K. Taguchi, Med. Phys., 38: 1089 (2011) PCD model Transmitted spectrum Spectral response 1 n SRE E = a SRE E, E k n t E k k or n SRE = A SRE n t Pulse pileups 2,3 n R E = n SRE E Pr "rec" = 1 Pr l "rec" = 1 Pr E l l l = # of photons piled up for one recorded count 20 Monte Carlo simulation study for Siemens PCD 700 140.0 120.0 100.0 80.0 700 600 500 400 300 200 100 measured 16000 SRE+PPE( (E)) 16,000 SRE, DL 14000 transmitted, DL 12000 10000 8000 6000 4000 2000 20 40 60 80 100 120 140 160 180 0 Energy (kev) 0 0 20 60 100 140 Energy (kev) 200 ma 800 ma 25 ma 800 ma DE onlyh 2 O, Al P, unipolar I t = 25 ma SRE+DE DLR = 0.9% COV = 2.4% SRE+pileups W PCD data measured SRE+PPE( (E)) DE onlysre, DL transmitted, DL SRE+DE H 2 O, Al P, unipolar I t = 800 ma SRE+pileups DLR = 25.3% COV = 1.5% W PCD data 20 60 100 140 Energy (kev) 20 40 60 80 100 120 140 160 180 Energy (kev) 100 mm water, 3.5 mm Al, 0.9 mm Ti; 120 kvp; pulse height analyzer; unipolar pulse 60.0 40.0 20.0 0.0 0.0 20.0 40.0 60.0 80.0 deadtime loss ratio: 1-n recorded/n t (%) 100-DE (%) DE = Detection efficiency (%) COVw = Weighted coefficient of variation (%) J. Cammin, presented at IEEE NSS/MIC 2014 21 7
Evaluation of PIECE-1 CNR 6.0 CNR 6.0 CNR 4.1 CNR 4.9 22 Strategy for low-dose CT Combine the following 3 technologies: 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 Note 2. Annual background radiation: 3.1 msv 23 Joint estimation with tissue types Sinogram y Characteristic coefficients w Tissue type z E Projection noise K. Nakada, et al., IEEE MIC (2013); Med Phys (2015) 24 8
Joint estimation with tissue types Sinogram y Characteristic coefficients w Tissue type z E Projection noise Geometry Statistical relationship 0.20 w pe 0.10 Iodine-mixed blood z i = z j = blood 2 α w i w j rib Smooth lung fat z i z spine j β blood 0.00 muscle Discontinuous liver muscle location 0.00 0.10 0.20 0.30 0.40 w K. Nakada, et al., IEEE MIC (2013); Med Phys (2015) cs 25 Joint estimation with tissue types Sinogram y Characteristic coefficients w Tissue type z E Projection noise Geometry Statistical relationship w z i = z j = blood α w i w j 2 Smooth z i z j z β blood muscle Discontinuous location K. Nakada, et al., IEEE MIC (2013); Med Phys (2015) 26 Truth FBP PML K. Nakada, CERN wrokshop (2015) JE-MAP @70keV, WW 400HU, WL -50HU 27 9
Truth FBP PML K. Nakada, CERN wrokshop (2015) JE-MAP @70keV, WW 400HU, WL -50HU 28 Joint estimation with tissue types PML FBP Noise reduction at FWHM=3 pixels by 30%: FBP PML by 33%: PML JE-MAP by 53%: FBP JE-MAP JE-MAP K. Nakada, et al., IEEE MIC (2013) 29 Photon counting low-dose CT Current CT detectors lead 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) 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 30 10
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 31 Whole-body prototype PCD-CT system 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) 128x10 6 counts/s/mm 2 with 13.5% loss, 256x10 6 with 25.2% loss Shading artifacts due to energetic cross-talks (not shown) Cadavers In-vivo swines Courtesy of Cynthia H. McCollough, Ph.D. (Mayo Clinic) 32 Clinical benefits of spectral CT Improvement of current CT images 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 New class of CT imaging K Taguchi, Med Phys 40(10), 100901 (19 pages) (2013) 33 11
Molecular CT with nanoparticle contrast agents or probes Bi D. Pan, Angew Chem Int Ed 49: 9635-9639 (2010) 34 Imaging macrophages in atherosclerotic plaques Nano agent Nano agent Conventional Injection F. Hyafil, Nat Med 13(5): 636-641 (2007) Nano agent Conventional agent 35 The use of PCDs and coded-aperture for simultaneous absorption, phase, and differential phase contrast imaging Low-dose single scan followed by a novel retrieval algorithm 5cm average breast tissue 1.5 mgy dose 6 energy bins, CdTe detector M. Das, AAPM 2015, TH-AB-204-07 (8:30 am) Absorption Phase Diff. phase 36 12
Summary Current CT detectors cause the major limitations of CT images PCDs address them and enable new applications Low-dose CT by integrating 3 technologies Photon counting detectors (PCDs) Iterative reconstruction for PCDs (PIECE) Joint estimation with tissue types (JE-MAP) A few whole-body prototype PCD-CT systems being evaluated at hospitals 37 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 38 13
Thresholds to pulse height comparators DAC Comparators Counter 1 Digital output Input analog pulses Preamp Shaper DAC Counter 2 Digital output DAC Counter N Digital output 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 41 Joint estimation with tissue types Sinogram y Characteristic coefficients w Tissue type z E Projection noise w z blood muscle location K. Nakada, et al., IEEE MIC (2013); Med Phys (2015) 42 14