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Functional computed tomography using energy resolved photon counting detectors Anthony Butler Overview Why functional imaging Recent trends in clinical imaging Spectral CT and the MARS project Medical applications Radiopharmaceutical imaging Soft tissue imaging Conclusions Change in radiology utilisation 1998-2005 => 4.5% /year 2006-2008 => 1.4% /year Bending the Curve: The Recent Marked Slowdown in Growth of Noninvasive Diagnostic Imaging American Journal of Roentgenology, Jan. 2011 Drivers of change 2000-2008 “CT Slice War” fan beam geometry to cone beam geometry 2000: acquire a single transverse slice per rotation 2012: acquire up to 64-500 slices per rotation Current State Anatomical imaging is now really good Very little benefit in more speed or resolution Anatomical imaging is now really good Functional imaging is the future What is the tissue? What is its behaviour? Is the treatment working? (not just size, shape, location) What the diagnostician wants to know Constituents (fat, water, calcium, iron) Cancer and pathogen labels Physiological markers etc MARS spectral CT project Goals To obtain novel information about tissues Compositional information Functional information To have a route to human imaging The Team Technical team University of Canterbury Clinical team University of Otago International Partners Incl. CERN, Mayo Clinic, etc The company MARS Bioimaging Ltd Single energy CT Single- , dual-, and spectral CT Xray source B/W Patient Grey scale detector Hounsfield Units Single energy CT Single- , dual-, and spectral CT Xray source B/W Dual energy CT Patient Grey scale detector Xray source B/W Xray source B/W Two grey scale detectors Hounsfield Units Single energy CT Single- , dual-, and spectral CT Xray source B/W MARS spectral CT Dual energy CT Patient Grey scale detector Xray source B/W Xray source B/W Two grey scale detectors Xray source Medipix Color detectors Hounsfield Units Spectral CT is now possible Medipix All Resolution System Energy resolution Spatial resolution Temporal resolution Current single-energy CT provides Spatial resolution Temporal resolution Brightness only (grey scale) X-ray camera Medipix3 photon processing detector Quantum / counting detector (Film, CR, DR, CT are all integrating detectors) Pixel detector Each pixel has its own electronics Spectral detector Measure energy of photons Reconstruction tailored to photon counting Photon counting detectors poor in high flux 0.15 Water x-ray source Ca Fe Sunflowe r oil Iodine 0.1 0.05 0 Medipix Air Reconstruction tailored to photon counting Photon counting detectors poor in high flux High x-ray flux beam 0.15 Water x-ray source Ca Fe Sunflowe r oil Iodine 0.1 Medipix Air 0.05 High x-ray flux beam 0 Reconstruction tailored to photon counting Reconstruct only from central detector elements 0.15 Water x-ray source Ca Fe Sunflowe r oil Iodine 0.1 0.05 0 Medipix Air ROI Measure individual materials Iodine: Pulmonary circulation Barium: Lung Calcium: normal bone Pharmaceuticals identified by spectral information Iodine: Pulmonary circulation Barium: Lung Calcium: normal bone Functional cartilage imaging Histology and spectral CT to demonstrate GAG content • Low GAG • High hexabrix Cartilage Bone - Volume rendering - Energy gradient by PCA • High GAG • Low hexabrix Funded by NZ Arthritis Foundation Quantification of fat and water Spectral CT of a mouse 10-35keV “Fat-like” “Calcium-like” Initial work funded by Health Research Council “Water-like” Atheroma characterization Aim to indentify plaque components Unstable plaques need therapy Next Steps: Ca versus Fe Inflammatory markers Funded by National Heart Foundation The future: Functional labels •Complex physiological markers can be made •These often have unique spectral response (contain heavy atoms) We can measure the spectral response of nano-particle that target aggregated platelets. Next step: Measure them in mice… Conclusion Recently radiology improvements have been speed and spatial resolution Functional imaging is the future of radiology Spectral CT is able provide this information Anthony Butler, M Walsh, P Ronaldson, N Scott, R Zainon, S Geiseg, T Janmale, N Cook, A Opie, R Amir, R Doesburg, N de Ruiter,H Yu, J Bennett, G Wang, T Woodfield, N Cook, P Bones, J Mohr, N Anderson, P Butler