1. Orthopaedic applications of MARS spectral CT Kishore Rajendran Department of Radiology, Centre for Bioengineering University of Otago, Christchurch New Zealand

2. 2 MARS small-animal scanners Medipix All Resolution System (MARS)

3. 3 Topics CT imaging Introduction to MARS technology –Medipix photon-counting detectors –Small-animal gantry system –Imaging routine (data acquisition, processing, and reconstruction) Orthopaedic applications of MARS imaging –Metal implant imaging –Non-destructive characterization of 3D-printed biomaterial scaffolds –Quantitative cartilage imaging for osteoarthritis Summary and outlook

4. 4 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.

5. 5 Computed Tomography Cone-beam geometry enables multi-slice fast scans Parallel-beam and fan-beam geometries are outdated, but are easy to implement computationally. Parallel-beam geometryFan-beam geometryCone-beam geometry

6. 6 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

7. 7 Computed Tomography Lambert-Beer Law, I = I 0 e -µL I (attenuated beam), I o (incident beam) and L (path length) are known, µ to be estimated µ is the linear attenuation coefficient (material-specific and x-ray energy-specific) IoIo I

8. 8 Computed Tomography 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 IoIo I

9. Conventional CT Spectral signatures of materials

10. Bin1 Spectral signatures of materials Bin2 Bin3Bin4Bin5 Spectral CT

11. Colour CT image 11 Calcium component Barium component Analogy: Black and white TV (grayscale) vs. Colour TV

12. 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. 12

13. 13 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)

14. Overview: MARS imaging routine 14

15. Medipix Energy-discriminating, pixelated detectors 15 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.

16. 16 MARS detector module ASIC MedipixMXR Medipix3.0 Medipix3.1 Medipix3RX Sensor layer Silicon Gallium arsenide Cadmium telluride Cadmium zinc telluride (CZT) Readout MARS camera V5 (ILR Christchurch) 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, Am 241 radioactive source, XRF of Mo, Pb foils

17. Medipix Unsubtracted Bins 17 Kishore Rajendran, “MARS Spectral CT technology for orthopaedic applications,” Ph.D. thesis, University of Otago, Christchurch, New Zealand, 2015. Bin 1: [T1 to kVp] Range Bin 2: [T2 to kVp] Bin 3: [T3 to kVp] Bin 4: [T4 to kVp]

18. Medipix Subtracted Bins 18 Kishore Rajendran, “MARS Spectral CT technology for orthopaedic applications,” Ph.D thesis, University of Otago, Christchurch, New Zealand, 2015. Bin 1: [T1 to T2] Range Bin 2: [T2 to T3] Bin 3: [T3 to T4] Bin 4: [T4 to kVp]

19. MARS Project 19 Hardware & Robotics Visualization & Image Processing Preclinical research Detector characterization Scanner control system Detector readout electronics Preprocessing techniques Reconstruction algorithms Material decomposition methods 3D rendering and virtual reality Vascular imaging Oncology Bone and cartilage imaging

20. MARS Project 20 Hardware & Robotics Visualization & Image Processing Preclinical research Detector characterization Scanner control system Detector readout electronics Preprocessing techniques Reconstruction algorithms Material decomposition methods 3D rendering and virtual reality Vascular imaging Oncology Bone and cartilage imaging

21. Orthopaedic applications of MARS Reducing metal artefacts in implant imaging Quantitative cartilage imaging for osteoarthritis Characterizing additive manufactured scaffolds for tissue engineering 21

22. Orthopaedic applications of MARS Reducing beam hardening effects and metal artefacts in spectral CT using Medipix3RX 22

23. X-ray beam hardening 23

24. 24 CT metal artefacts Image courtesy: Dr Nigel Anderson, Radiology, Christchurch Hospital, New Zealand

25. 25 Cupping effect Cupping effect due to beam hardening

26. Spectral CT approach 26 T1T2 T3T4T1T2T3T1T2T4T3T1T2

27. Test samples Titanium and cobalt-chromium alloys Aluminium and stainless-steel 27 Christchurch Regenerative Medicine and Tissue Engineering (CReaTE)

28. 28 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. Metal artefact reduction in Ti scaffold

29. 29 CoCr + PMMA – Spectral reconstruction EnergyCNR 50 to 120 keV16.9 60 to 120 keV17.6 70 to 120 keV18.7 80 to 120 keV19.4 5.5 mm K. Rajendran et.al, Assessing metal artefacts in multi-energy CT, In Preparation

30. 30 Steel phantom 60 to 120 keV 15 to 120 keV35 to 120 keV 80 to 120 keV 30 12.5 mm

31. 3D visualization – Ti, CoCr and ceramic implants Ti screw in PMMAPMMA and CoCrCeramic and PMMA

32. Bony ingrowth in Ti scaffolds imaged using MARS

33. Orthopaedic applications of MARS Quantitative cartilage imaging for osteoarthritis 33

34. 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 34 Priniciple

35. Excised tibial plateau 35 K. Rajendran et.al, Quantitative cartilage imaging using spectral CT, in submission to European Radiology

36. 36 Multi-energy reconstructions 6mm

37. Multi-energy material decomposition 4mm

38. 38

39. 39 MARS MD vs. Histology MARS material imagesGAG histology

40. 40 3D visualization

41. 41 MARS MD vs. Histology MARS [20-120 keV] MARS-MD (Ca + I) Histology

42. Orthopaedic applications of MARS Characterizing 3D printed biomaterial scaffolds 42

43. 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 43 Additive Manufacturing

44. Material identification in Bioglass scaffold Spectral image (15 to 50 keV) Image segmentation using PCA 2mm

45. Outlook 45 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)

46. 46 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.

47. Hybrid spectral reconstruction 47

48. 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 48 Summary 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

49. Acknowledgements 49

50. 50 MARS group CReaTE group