Transcript KishoreRajendran_ASET_08JAN16x

Orthopaedic applications of MARS spectral CT
Kishore Rajendran
Department of Radiology, Centre for Bioengineering
University of Otago, Christchurch
New Zealand
MARS small-animal scanners
Medipix All Resolution System (MARS)
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Topics
• CT imaging
• Introduction to MARS technology
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Medipix photon-counting detectors
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Small-animal gantry system
–
Imaging routine (data acquisition, processing, and reconstruction)
• Orthopaedic applications of MARS imaging
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Metal implant imaging
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Non-destructive characterization of 3D-printed biomaterial scaffolds
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Quantitative cartilage imaging for osteoarthritis
• Summary and outlook
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Computed Tomography
• Mathematical foundation - Radon Transform, and Fourier Transform
• First CT scanner - Godfrey Hounsfield (EMI Ltd) and Allan Cormack (Tufts Univ.)
1971 First successful scan of a cerebral cyst
1979 Nobel Prize for Physiology and Medicine
• Current technology: Multislice CT, Dual-energy CT, and Spectral CT (upcoming)
• CT enables high resolution volumetric imaging for clinical and industrial
applications. Recently, microCT has become popular for non-destructive
imaging of samples at < 1 µm spatial resolution.
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Computed Tomography
Parallel-beam geometry
Fan-beam geometry
Cone-beam geometry
• Cone-beam geometry enables multi-slice fast scans
• Parallel-beam and fan-beam geometries are outdated, but are easy to
implement computationally.
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Computed Tomography: Spiral/Helical scans
• Helical geometry enables fast whole body scans
• Uses cone-beam geometry
Image courtesy
Siemens Healthcare
JT Bushberg et.al, The Essential Physics of Medical Imaging, LW&W, 2002
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Computed Tomography
Io
I
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Lambert-Beer Law, I = I0e-µL
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I (attenuated beam), Io (incident beam) and L (path length) are known, µ to be estimated
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µ is the linear attenuation coefficient (material-specific and x-ray energy-specific)
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Computed Tomography
Io
I
Algebraic framework for reconstructing µ from transmitted x-ray data
Ax = b
A – ray geometry information
x – volume data to be estimated (µ)
b – Transmission data (measured line integral)
Several algorithms have been devised since the 1970s – ART, SART, SIRT, OSEM
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Spectral signatures of materials
Conventional CT
Spectral signatures of materials
Spectral CT
Bin1
Bin2
Bin3
Bin4
Bin5
Colour CT image
Barium component
Calcium component
Analogy: Black and white TV (grayscale) vs. Colour TV
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MARS Spectral CT
• Multidimensional data with spatial, spectral, temporal components.
Single energy CT – dual energy CT – multienergy CT (spectral)
• Resolving x-ray energies  attenuation spectra of materials  quantification of
native tissue types and contrast pharmaceuticals.
• Spectroscopic x-ray detection enabled using Medipix photon-counting detectors
developed at CERN.
• Better x-ray detection efficiency (PCD)  low radiation dose.
• Can provide molecular information at high spatial resolution.
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MARS small-animal scanners
• Rotating gantry setup with Medipix detectors
• Polychromatic x-ray source for diagnostic x-rays (10 to 120 keV)
• Fully automated imaging chain (acquire, store, process, transfer, visualize)
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Overview: MARS imaging routine
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Medipix
Energy-discriminating, pixelated detectors
R. Ballabriga Suñé, “The design and implementation in 0.13m cmos of an algorithm permitting
spectroscopic imaging with high spatial resolution for hybrid pixel detectors,” Ph.D.
dissertation, Ramon Llull University, Barcelona, Spain, 2009.
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MARS detector module
ASIC
Sensor layer
Readout
MedipixMXR
Silicon
MARS camera V5
(ILR Christchurch)
Medipix3.0
Gallium arsenide
Medipix3.1
Cadmium telluride
Medipix3RX
Cadmium zinc telluride (CZT)
Notable features:
55 µm pixel pitch and 110 µm pixel pitch (usually 14 mm x 14 mm chip, 128 x 128 pixel grid)
Operating modes: fine-pitch, spectroscopic, and charge-summing mode (3RX)
Energy calibration: kVp technique, Am241 radioactive source, XRF of Mo, Pb foils
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Medipix
Unsubtracted Bins
Range
Bin 1: [T1 to kVp]
Bin 2: [T2 to kVp]
Bin 3: [T3 to kVp]
Bin 4: [T4 to kVp]
Kishore Rajendran, “MARS Spectral CT technology for orthopaedic applications,”
Ph.D. thesis, University of Otago, Christchurch, New Zealand, 2015.
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Medipix
Subtracted Bins
Range
Bin 1: [T1 to T2]
Bin 2: [T2 to T3]
Bin 3: [T3 to T4]
Bin 4: [T4 to kVp]
Kishore Rajendran, “MARS Spectral CT technology for orthopaedic applications,”
Ph.D thesis, University of Otago, Christchurch, New Zealand, 2015.
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MARS Project
Hardware &
Robotics
•Detector characterization
•Scanner control system
•Detector readout electronics
Visualization &
Image Processing
•Preprocessing techniques
•Reconstruction algorithms
•Material decomposition methods
•3D rendering and virtual reality
Preclinical research
•Vascular imaging
•Oncology
•Bone and cartilage imaging
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MARS Project
Hardware &
Robotics
•Detector characterization
•Scanner control system
•Detector readout electronics
Visualization &
Image Processing
•Preprocessing techniques
•Reconstruction algorithms
•Material decomposition methods
•3D rendering and virtual reality
Preclinical research
•Vascular imaging
•Oncology
•Bone and cartilage imaging
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Orthopaedic applications of MARS
• Reducing metal artefacts in implant imaging
• Quantitative cartilage imaging for osteoarthritis
• Characterizing additive manufactured scaffolds for tissue
engineering
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Orthopaedic applications of MARS
Reducing beam hardening effects and metal artefacts in spectral CT
using Medipix3RX
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X-ray beam hardening
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CT metal artefacts
Image courtesy: Dr Nigel Anderson, Radiology, Christchurch Hospital, New Zealand
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Cupping effect due to beam hardening
Cupping effect
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Spectral CT approach
T1
T2
T3
T4
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Test samples
• Titanium and cobalt-chromium alloys
• Aluminium and stainless-steel
Christchurch Regenerative Medicine and Tissue Engineering (CReaTE)
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Metal artefact reduction in Ti scaffold
CNR = 4.8, 5.4, 7.9 and 8.1 respectively
K. Rajendran et.al, Reducing Beam hardening and metal artefacts in spectral CT using
Medipix3RX, Journal of Instrumentation, Vol. 9 P03015, March 2014.
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CoCr + PMMA – Spectral reconstruction
5.5 mm
Energy
CNR
50 to 120 keV
16.9
60 to 120 keV
17.6
70 to 120 keV
18.7
80 to 120 keV
19.4
K. Rajendran et.al, Assessing metal artefacts in multi-energy CT , In Preparation
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Steel phantom
15 to 120 keV
35 to 120 keV
12.5 mm
60 to 120 keV
80 to 120 keV
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3D visualization – Ti, CoCr and ceramic implants
Ti screw in PMMA
PMMA and CoCr
Ceramic and PMMA
Bony ingrowth in Ti scaffolds imaged using MARS
Orthopaedic applications of MARS
Quantitative cartilage imaging for osteoarthritis
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Priniciple
• EPIC
– Equilibrium-Partitioned Imaging of Cartilage
• Target: Glycosaminoglycans (GAG)
– GAG depletion occurs during osteoarthritis (OA)
– GAG can be marked using ionic contrast pharmaceuticals
– GAG (negatively-charged) can attract/repel ionic contrast
• Current methods for imaging GAG in cartilage
– microCT - pseudo-quantitative
– dGEMRIC (delayed gadolinium enhanced MRI of cartilage) – low
resolution
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Excised tibial plateau
K. Rajendran et.al, Quantitative cartilage imaging using spectral CT, in submission to European Radiology
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Multi-energy reconstructions
6mm
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Multi-energy material decomposition
4mm
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MARS MD vs. Histology
MARS material images
GAG histology
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3D visualization
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MARS MD vs. Histology
MARS [20-120 keV]
MARS-MD (Ca + I)
Histology
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Orthopaedic applications of MARS
Characterizing 3D printed biomaterial scaffolds
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Additive Manufacturing
• Tissue-engineered constructs are used in musculoskelatal regenerative
medicine
• New composite biomaterials including metal alloys, bioceramics,
biodegradable polymers are developed for orthopaedic and dental implants
• Scaffolds also incorporate drugs/agents to promote healing at implant sites
• Characterizing 3D-printing processes and evaluating the quality of printed
structures are currently limited to surface assessment or pseudo-quantitative
microCT
Spectral CT can enable non-destructive evaluation of 3D printed
scaffolds used in tissue-engineering and regenerative medicine
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Material identification in Bioglass scaffold
Spectral image (15 to 50 keV)
2mm
Image segmentation using PCA
Outlook
• Spectral CT can provide multi-energy data at a single exposure, and has the
potential to reduce radiation dose
• Challenges
– Sensor fabrication
– Detector electronics (charge-sharing and pulse pile-up effects)
– Better reconstruction techniques
• Near-term implementation
– Small-animal scanners and spectral microCT
– Hybrid CT system
– Soft-tissue imaging using low-Z sensors (Si, GaAs)
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Hybrid spectral CT
Alex M. T. Opie, James R. Bennett, Michael Walsh, Kishore Rajendran, Hengyong Yu, Qiong Xu, Anthony
Butler, Philip Butler, Guohua Cao, Aaron M. Mohs and Ge Wang, Study of scan protocol for exposure
reduction in hybrid spectral micro-CT, Scanning, 2014, 36(4): 444 – 455.
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Hybrid spectral reconstruction
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Summary
• Spectral CT is enabled using novel photon-counting detectors
• Multi-energy data can be simultaneously acquired at a single x-ray
exposure, and tissue types and markers can be quantified
• Orthopaedic applications of spectral CT
– Metal artefact reduction
– Quantitative cartilage imaging
– Imaging 3D printed scaffolds
• A human scale MARS scanner prototype to be available by 2020 at Otago
School of Medicine, Christchurch, New Zealand
Further reading: Mike F. Walsh, Raja Aamir, Raj K. Panta, Kishore Rajendran, Nigel G. Anderson,
Anthony P. H. Butler, and Phil H. Butler, Spectral molecular CT with photon-counting detectors, In
Solid-state radiation detectors: Technology and applications, Editors: Salah Awadalla and Krzysztof
Iniewski, CRC Press, 2015. Chapter 9, pp: 195 - 219
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Acknowledgements
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CReaTE group
MARS group
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