Activity quantification of 137Cs point sources using the ProSPECTus Compton camera Thomas Woodroof t.f.woodroof@liverpool.ac.uk Dr Jonathan Bridge, School of Engineering Dr Andrew Boston, Department of Physics Dr James Cooper, School of Environmental Sciences Industrial Partner: National Nuclear Laboratory

Motivation: dynamics of environmental radioactivity Fukushima disaster (March 2011) contaminated large areas of eastern Japan: 137Cs (Eγ = 662 keV, t1/2 = 30 years). Processes driving redistribution of environmental 137Cs are poorly quantified: plant uptake, soil transport, leaf litterfall... Difficult to assess long-term risks and plan remediation in this complex system. Experiments to measure these processes are needed!

Compton imaging Compton scattering and photoelectric absorption of gamma rays. Measure energy of associated interactions to calculate Compton scattering angle: Detector segmentation gives approximate interaction locations.

Reconstruction algorithm: source position, number of events. Applications in medical imaging, astrophysics, nuclear security & industry. Qualitative time-lapse imaging of movement of 137Cs through a soil column already demonstrated. Aim for quantitative.

Complex geometry & interaction kinematics mean imaging event rate varies with source position – so how to measure source activity and hence transport rates etc.?

Calibrating ProSPECTus for activity quantification Choose a subset of ProSPECTus field of view with approximate dimensions of planned experiments. Place 137Cs point sources at positions spanning this phase space & measure absolute imaging efficiency. Simulate the system using GAMOS (Geant4-based Architecture for Medicine- Oriented Simulations) & compare to experimental results  validation of simulated response across phase space. Features still to be modelled: dead time, strip-by-strip energy resolutions and thresholds, detector dead layers.

Si(Li) scatterer strip resolutions at 122 keV.

HPGe absorber strip resolutions at 122 keV.

Simulate the response of ProSPECTus to an assembly of 137Cs point sources: full phase space characterisation. Record fraction of imaging events as function of source position. Interpolate to find an analytical function that describes variation in response: convert event rate into activity estimate.

Results & discussion Validation of GAMOS simulations x (mm) y (mm) z (mm) Experimental/simulated efficiencies -45 40 1.418 45 1.419 -35 50 0.647 35 1.267 -25 60 1.872 25 1.068 -15 70 0.877 15 0.938 -5 80 0.942 5 0.799 90 0.866 0.895 100 0.939 0.941 110 1.146 1.280 120 1.268 1.383 130 1.345 1.633 Weighted mean ratio is 1.328. Spread of values from 0.65 to 1.87. Expect inclusion of previously neglected aspects to improve this.

Phase space characterisation To use this, need to know position of source. Algorithm does excellent job of reconstructing in x and y. Standoff (z) is more of a challenge…

Pulse shape analysis, iterative reconstruction algorithms.

Extended/dispersed source quantifications will be crucial next step.

Conclusions Validation of GAMOS simulations of ProSPECTus is ongoing. Phase space can be characterised with analytical function. Method is generally applicable: different energies, phase spaces, Compton camera systems... Should also be useful for medical imaging etc. Currently work is on point sources only, but need to move beyond this for meaningful experiments on dynamics of 137Cs in environmental media.

Questions Special thanks to Dr Dan Judson. References [1] Cover image from J. Dormand, ‘The Proof of Concept of a Fused Radiometric and Optical Stereoscopic Imaging System.’ [2] Fukushima contamination diagram from G. Steinhauser et al., ‘Comparison of the Chernobyl and Fukushima nuclear accidents: A review of the environmental impacts,’ Science of the Total Environment 2013; Vol. 470: 800-817. [3] Redistribution processes figure from J. Bridge et al., ‘Radionuclides as Diffuse Pollution: Linking Dynamic Soil Processes with Bioavailability and Management by End-Users (RADIO:BIOMES).’ [4] Column image from J. Dormand, private communication. [5] Compton camera diagram from J. Dormand, ‘The Proof of Concept of a Fused Radiometric and Optical Stereoscopic Imaging System.’ [6] Analytical image reconstruction algorithm http://ns.ph.liv.ac.uk/~dsj/web/ [7] Scatterer schematic from L. Harkness, et al., ‘Characterisation of a Si(Li) orthogonal-strip detector,’ Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 726 (2013) 52. [8] Absorber schematic from H. Boston, et al., ‘Characterisation of the SmartPET planar Germanium detectors,’ Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 579 (2007) 104. [9] P. Arce, et al., ‘GAMOS: A framework to do GEANT4 simulations in different physics fields with an user-friendly interface’ Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 735 (2014) 304. [10] Column image from J. Dormand, private communication.