High Resolution and High Sensitivity PET Scanner with Novel Readout Concept Erlend Bolle1,Michael Rissi1, Michelle Böck1, Jo Inge Buskenes1, Kim-Eigard Hines1, Ole Dorholt1, Ole Røhne1, Steinar Stapnes1,2, Jan G. Bjaalie3, Arne Skretting4 1 Universitet i Oslo, Norway 2 CERN, Geneva, Switzerland 3Department of Anatomy & CMBN, Oslo, Norway 4Rikshospitalet-Radiumhospitalet Medical Center, Oslo, Norway

Why small-animal PET? Biomedical Applications: detectibility of small tumors in transgenetic mice/rats -> concepts for human cancer longtime-study at each animal -> more control, disease progression, therapeutic response -> statistical power improved functional information available -> PET: functional and kinetic data, non-invasive, in-vivo

Challenges for improving small-animal PET Systems PET systems’ performance improved by enhancing important parameters of detector systems: photon sensitivity: fraction of coincident annihilation photon pairs emitted from a source spatial resolution: determined by: positron range, annihilation photon acollinearity, intrinsic detector resolution contrast resolution: ability to differentiate/quantify one region from background or two adjacent regions Current Trends in Preclinical PET Systems Design – C.S. Levin, H. Zaidi

Challenges for Classical PET measure depth of interaction (DOI) no information on DOI -> parallax error δP = L sinα increases with distance from center of field of view (FOV) solution: spatial resolution improved by measuring interaction point in 3D

Challenges for Classical PET True Scatter Random Body scatter events occur in body and scanner Scatter Scatter Scanner

COMPET - Detector Arrangement

COMPET - Detector Arrangement LYSO crystal: information on x-, y-coordinates, energy of event wave length shifter (WLS): z-coordinate high resolution (sub-millimeter) readout on the end of WLS and LYSO → reflector on opposite end light below angle of total reflection escapes LYSO → absorbed at one side by WLS light transport relies on internal reflection → polished and crack-free surface resolution along the 3 dimensions tuned by varying LYSO/WLS dimensions based on method proposed by AX-PET collaboration https://twiki.cern.ch/twiki/bin/view/AXIALPET/WebHome

COMPET Flexible Geometry

COMPET - Facts 4-8cm bore opening (adjustable) with 8cm axial view very high sensitivity (16%) high resolution (sub-millimeter) 3D event reconstruction no inter module and inter crystal gap High data throughput FPGA/ethernet readout (10Mevents/sec) Backend computer farm for data taking and image reconstruction MRI compability y x z

Detector Module 2×3mm2 MPPC 2×3×80mm3 1×3×80mm3 1×3mm2 MPPC 600 LYSO crystals 400 WLS 2×3×80mm3 LYSO 1×3×80mm3 WLS 2×3mm2 MPPC (LYSO) 1×3mm2 MPPC (WLS) 2×3mm2 MPPC 2×3×80mm3 1×3×80mm3 1×3mm2 MPPC

Detector Module-Main Components LYSO 3x3mm2 MPPC WLS –wave length shifter

AX-PET Workshop, Valencia MRI Insert AX-PET Workshop, Valencia

MR Insert - Challenges no ferromagnetic components do not disturb MR fit inside existing MR shielding cooling

Ultimate Goal (a) Dynamically acquired PET images from a C57BL/6 mouse injected with [11C]-d-threo-methylphenidate show a specific dopamine transporter binding in the striatum (S) and nonspecific uptake in the Harderian glands (H). (b) Brain morphology is revealed from the magnetic resonance images simultaneously acquired using a 3D TSE sequence. (c) The fused images show enhanced tracer uptake, matching the morphology of the striatum in the magnetic resonance data. (d) Time-activity curves (TACs), derived from the PET data simultaneously acquired during MRI, allow further analysis such as kinetic modeling to determine the dopamine transporter binding potential. The clear separation of the striatum and cerebellum (Cb) curve indicates more specific tracer binding in the striatum than in the cerebellum. Both TACs include unbound tracer. Scale bars, 1 cm.

Simulation Setup software: Gate v5.0.0p01 (based on GEANT4) list output via ROOT 3 different scenarios: total deposited energy in 2 modules > 2∙ 450 keV (no inter-module scatter accepted) total deposited energy in less than 3 crystals > 2 ∙ 450 keV (accepting inter-crystal scatters) total deposited energy in exactly 2 crystals > 2 ∙450 keV (accepting only photoelectric events) Simulation of back-to-back gamma rays (511 keV) x y

Sensitivity Simulation source: back-to-back gammas (511 keV) 5 layers, 4 modules diameter: 50 mm, length: 72 mm 3D event reconstruction: 3 cases assumed LYSO Crystals Photoelectric event Multiple scatter Single scatter g

Detector Sensitivity All events (multiple scatters) Single scatters Photoelectric events

COMPET - High Resolution Sensitivity vs resolution Ref.: C. Levin et.al., “Current Trends in Preclinical PET System Design”

COMPET - High Sensitivity COMPET LYSO Box 8 450-650, 10 16 Ref.: C. Levin et.al., “Effects of system geometry and other physical factors on photon sensitivity of high-resolution positron emission tomography”

Central Point Source Resolution g MPPC LYSO WLS POI resolution s(POI) [mm] FWHMx [mm] FWHMy [mm] 0.3 0.8 0.4 0.5 0.9 0.6 0.7 1.0 1.2

Point Source Resolution activity: 4x106 Bq 1s run time assumed POI resolution: s = 0.5mm of back-to-back g-rays xSource [mm] ySource[mm] zSource[mm] FWHMx[mm] FWHMy[mm] 0.0 0.86 0.89 5.0 0.80 1.05 10.0 0.87 1.22 15.0 0.92 1.50 20.0 0.96 1.52 -20.0 1.59 1.67

AX-PET Workshop, Valencia Reconstruction 3D Fourier rebinning to transaxial slices 2D filtered back projection (using ramp filter) for each transaxial slice Derenzo - phantom AX-PET Workshop, Valencia

Resolution vs. Sensitivity Resolution FWHM [mm]

Simulation - Summary according to simulations: DOI resolution of 0.5 mm is achievable -> CPS resolution of approx. 0.9 x 0.9 mm2 point-source-resolution degrades for off-axis objects to approx. 1.6 x 1.6 mm2 close to the detector maximal sensitivity of to back to back gammas: if multiple scatter events reconstructed -> sensitivity: 16% if only single scatter events accepted -> sensitivity: 14%.

Conclusion and Future Work Detector concept -> demonstrated New readout scheme -> proven to work All parts bought -> implement full scanner Hoping for first results beginning of 2011! 2010 Simulation Image reconstruction Prototype testing System implementation 2011 System verification Preclinical tests 2012 Preclinical test Fused MRI/PET images Thanks a lot to: Norwegian Research Council Swiss National Fund