Summary Proton CT (pCT) is an evolving technology that promises to improve proton treatment planning by addressing the range uncertainty problem. Proton.

Slides:



Advertisements
Similar presentations
1 ACES Workshop, March 2011 Mark Raymond, Imperial College. Two-in-one module PT logic already have a prototype readout chip for short strips in hand CBC.
Advertisements

Using the EUDET pixel telescope for resolution studies on silicon strip sensors with fine pitch Thomas Bergauer for the SiLC R&D collaboration 21. May.
28 August 2002Paul Dauncey1 Readout electronics for the CALICE ECAL and tile HCAL Paul Dauncey Imperial College, University of London, UK For the CALICE-UK.
Vertex2002 pCT: Hartmut F.-W. Sadrozinski, SCIPP Initial Studies in Proton Computed Tomography L. R. Johnson, B. Keeney, G. Ross, H. F.-W. Sadrozinski,
DSP online algorithms for the ATLAS TileCal Read Out Drivers Cristobal Cuenca Almenar IFIC (University of Valencia-CSIC)
Hartmut F.-W. Sadrozinski RESMDD06 Radiography Studies for Proton CT M. Petterson, N. Blumenkrantz, J. Feldt, J. Heimann, D. Lucia, H. F.-W. Sadrozinski,
The performance of LHCf calorimeter was tested at CERN SPS in For electron of GeV, the energy resolution is < 5% and the position resolution.
RESMDD'02 pCT: Hartmut F.-W. Sadrozinski, SCIPP INITIAL STUDIES on PROTON COMPUTED TOMOGRAPHY USING SILICON STRIP DETECTORS L. Johnson, B. Keeney, G. Ross,
GLAST LAT Readout Electronics Marcus ZieglerIEEE SCIPP The Silicon Tracker Readout Electronics of the Gamma-ray Large Area Space Telescope Marcus.
GLAST LAT Readout Electronics Marcus ZieglerIEEE SCIPP The Silicon Tracker Readout Electronics of the Gamma-ray Large Area Space Telescope Marcus.
The Design of MINER  A Howard Budd University of Rochester August, 2004.
Activities for Proton Computed Tomography PCT Loma Linda University Medical Center Hartmut F.-W. Sadrozinski Santa Cruz Inst. for Particle Physics SCIPP.
Vertex2002 pCT: Hartmut F.-W. Sadrozinski, SCIPP Initial Studies in Proton Computed Tomography L. R. Johnson, B. Keeney, G. Ross, H. F.-W. Sadrozinski,
Design and test of a high-speed beam monitor for hardon therapy H. Pernegger on behalf of Erich Griesmayer Fachhochschule Wr. Neustadt/Fotec Austria (H.
Beam Test for Proton Computed Tomography PCT
The Transverse detector is made of an array of 256 scintillating fibers coupled to Avalanche PhotoDiodes (APD). The small size of the fibers (5X5mm) results.
Performance test of STS demonstrators Anton Lymanets 15 th CBM collaboration meeting, April 12 th, 2010.
Data is sent to PC. Development of Front-End Electronics for time projection chamber (TPC) Introduction Our purpose is development of front-end electronics.
U N C L A S S I F I E D FVTX Detector Readout Concept S. Butsyk For LANL P-25 group.
VC Feb 2010Slide 1 EMR Construction Status o General Design o Electronics o Cosmics test Jean-Sebastien Graulich, Geneva.
M. Scaringella 1, M. Bruzzi 2,3, M. Bucciolini 3,4,10, M. Carpinelli 8,9, G. A. P. Cirrone 5, C. Civinini 3, G. Cuttone 5, D. Lo Presti 6,7, S. Pallotta.
Leo Greiner IPHC meeting HFT PIXEL DAQ Prototype Testing.
1 Digital Active Pixel Array (DAPA) for Vertex and Tracking Silicon Systems PROJECT G.Bashindzhagyan 1, N.Korotkova 1, R.Roeder 2, Chr.Schmidt 3, N.Sinev.
Leo Greiner TC_Int1 Sensor and Readout Status of the PIXEL Detector.
A Front End and Readout System for PET Overview: –Requirements –Block Diagram –Details William W. Moses Lawrence Berkeley National Laboratory Department.
GLAST LAT ProjectMarch 24, F Tracker Peer Review, WBS GLAST Large Area Telescope: Tracker Subsystem WBS F: On-Orbit Calibration and.
Parallel Data Acquisition Systems for a Compton Camera
Beam Tests of 3D Vertically Interconnected Prototypes Matthew Jones (Purdue University) Grzegorz Deptuch, Scott Holm, Ryan Rivera, Lorenzo Uplegger (FNAL)
Swadhin Taneja Stony Brook University On behalf of Vertex detector team at PHENIX Collaboration 112/2/2015S. Taneja -- DNP Conference, Santa Fe Nov 1-6.
Vertex 2005, Nikko Manfred Pernicka, HEPHY Vienna 1.
Some thoughts on the New Small Wheel Trigger Issues V. Polychronakos, BNL 10 May,
Studies of the possibility to use of a Gas Pixel Detector (GPD) as a fast track trigger device George Bashindzhagyan (Speaker,
Update on final LAV front-end M. Raggi, T. Spadaro, P. Valente & G. Corradi, C. Paglia, D. Tagnani.
Apollo Go, NCU Taiwan BES III Luminosity Monitor Apollo Go National Central University, Taiwan September 16, 2002.
BTeV Hybrid Pixels David Christian Fermilab July 10, 2006.
Sensor testing and validation plans for Phase-1 and Ultimate IPHC_HFT 06/15/ LG1.
Hartmut F.-W. Sadrozinski: pCT HSTD8 Dec Development of a Head Scanner for Proton CT Hartmut F.-W. Sadrozinski R. P. Johnson, S. Macafee, A. Plumb,
Leo Greiner IPHC beam test Beam tests at the ALS and RHIC with a Mimostar-2 telescope.
Abstract Beam Test of a Large-area GEM Detector Prototype for the Upgrade of the CMS Muon Endcap System V. Bhopatkar, M. Hohlmann, M. Phipps, J. Twigger,
Time and amplitude calibration of the Baikal-GVD neutrino telescope Vladimir Aynutdinov, Bair Shaybonov for Baikal collaboration S Vladimir Aynutdinov,
Beam Test of a Large-Area GEM Detector Prototype for the Upgrade of the CMS Muon Endcap System Vallary Bhopatkar M. Hohlmann, M. Phipps, J. Twigger, A.
 0 life time analysis updates, preliminary results from Primex experiment 08/13/2007 I.Larin, Hall-B meeting.
RD51 GEM Telescope: results from June 2010 test beam and work in progress Matteo Alfonsi on behalf of CERN GDD group and Siena/PISA INFN group.
Tracking at the Fermilab Test Beam Facility Matthew Jones, Lorenzo Uplegger April 29 th Infieri Workshop.
Custom IC Design and Data Acquisition Robert P. Johnson Santa Cruz Institute for Particle Physics University of California Santa Cruz Proton Computed Tomography.
Siena, May A.Tonazzo –Performance of ATLAS MDT chambers /1 Performance of BIL tracking chambers for the ATLAS muon spectrometer A.Baroncelli,
Upgrade with Silicon Vertex Tracker Rachid Nouicer Brookhaven National Laboratory (BNL) For the PHENIX Collaboration Stripixel VTX Review October 1, 2008.
Update on works with SiPMs at Pisa Matteo Morrocchi.
FPGA based signal processing for the LHCb Vertex detector and Silicon Tracker Guido Haefeli EPFL, Lausanne Vertex 2005 November 7-11, 2005 Chuzenji Lake,
The BTeV Pixel Detector and Trigger System Simon Kwan Fermilab P.O. Box 500, Batavia, IL 60510, USA BEACH2002, June 29, 2002 Vancouver, Canada.
A Low-dose, Accurate Medical Imaging Method for Proton Therapy: Proton Computed Tomography Bela Erdelyi Department of Physics, Northern Illinois University,
29/05/09A. Salamon – TDAQ WG - CERN1 LKr calorimeter L0 trigger V. Bonaiuto, L. Cesaroni, A. Fucci, A. Salamon, G. Salina, F. Sargeni.
Off-Detector Processing for Phase II Track Trigger Ulrich Heintz (Brown University) for U.H., M. Narain (Brown U) M. Johnson, R. Lipton (Fermilab) E. Hazen,
Silicon Tracking Detectors for Hadron Beam Monitoring and Imaging Silicon Tracking Detectors for Hadron Beam Monitoring and Imaging Phil Allport (Particle.
DAQ ACQUISITION FOR THE dE/dX DETECTOR
Analysis of LumiCal data from the 2010 testbeam
The 3D Medical Imaging using Proton Computed Tomography
Resolution Studies of the CMS ECAL in the 2003 Test Beam
PSD Front-End-Electronics A.Ivashkin, V.Marin (INR, Moscow)
Silicon Pixel Detector for the PHENIX experiment at the BNL RHIC
AQUA-ADVANCED QUALITY ASSURANCE FOR CNAO
Integration and alignment of ATLAS SCT
Towards Proton Computed Tomography
CMS Preshower: Startup procedures: Reconstruction & calibration
Single Photon Emission Tomography
The Pixel Hybrid Photon Detectors of the LHCb RICH
Example of DAQ Trigger issues for the SoLID experiment
BESIII EMC electronics
High Rate Photon Irradiation Test with an 8-Plane TRT Sector Prototype
The CMS Tracking Readout and Front End Driver Testing
Presentation transcript:

Summary Proton CT (pCT) is an evolving technology that promises to improve proton treatment planning by addressing the range uncertainty problem. Proton CT will generate a set of integrated relative stop- ping power (RSP) measurements that are used to reconstruct a map of RSP values to be input into a treatment planning system. Our NIH funded pCT Collaboration has built and successfully operated a Phase-II scanner that was designed to measure individually at least one million protons per second, more than 50 times faster than our previous Phase-I device. At this rate a full scan can be completed in less than 10 minutes, a performance level that will allow us to complete a full pre-clinical performance evaluation of this new modality. Here we report on the hardware implementation, initial testing and first image reconstruction. Our Phase-II scanner is based on two silicon-strip tracking-detector modules, an energy/range detector based on 5 scintillator stages read out by photomultiplier tubes, a rotating stage, and a custom high-speed data acquisition system based on 16 FPGAs. H.F.-W. Sadrozinski, et al, Development of a Head Scanner for Proton CT, Nucl. Instr. Meth. A 699 (2013) 205. ( not to scale ) Silicon strip detectors are nearly ideal candidates for the tracking portion of a pCT system. The relatively high cost per cm 2 of the sensors (compared to plastic scintillators, for example) is more than offset by their high performance, reliability, stability, and ease of assembly. Furthermore, the sensor cost would be a minor portion of the overall cost of a clinical system. Silicon strip detectors offer the following attractive characteristics, demonstrated in very large systems such as the Fermi-LAT Gamma-ray Space Telescope and the CERN LHC tracking detectors: Near 100% efficiency for charged particle detection with practically zero noise occupancy. Inherently fine spatial resolution (about 70 microns rms in this case). Simple calibration that is stable over time periods of many years. Compact and easy assembly using standard mechanized industrial processes, with excellent mechanical stability. Photograph of one tracking detector assembly with 4 layers of silicon-strip detectors. A “V” layer, which measures the vertical coordinate, is visible in front. Signals from 64 strips are amplified, digitized, and read out by each custom IC (inset). A Xilinx Spartan-6 FPGA controls the setup and readout, assembles the data from the 12 front-end ICs, and transmits the data to the event builder over a DVI-D cable at a rate of 100 Mbit/s. The loose cables visible here are used to program the 6 FPGAs (1 on each “V” board and 2 on each “T” board). An I 2 C bus on each board monitors temperature as well as the voltages and currents for each voltage regulator, plus the current for the 100 V SSD bias. The use of “slim-edge” technology reduces the dead region around SSD joints to less than 0.6 mm in width. R. Johnson et al, Tracker Readout ASIC for Proton Computed Tomography Data Acquisition, IEEE Trans. Nucl. Sci. 60, , ASIC SSDs FPGA Results from a Pre-Clinical Head Scanner for Proton CT Hartmut F.-W. Sadrozinski, for the pCT Collaboration: R. P. Johnson, Tia Plautz, Hartmut F.-W. Sadrozinski, A. Zatserklyaniy: SCIPP, U.C. Santa Cruz, Santa Cruz, CA, USA V. Bashkirov, V. Giacometti, F. Hurley, P. Piersimoni, R. Schulte: Division of Radiation Research, Loma Linda University, Loma Linda, CA, USA P. Karbasi, K. Schubert, B.Schultze: Baylor University, Waco, TX, USA This work is supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and the NSF, award Number R01EB The content of this contribution is solely the responsibility of the authors and does not necessarily represent the official views of NIBIB and NIH. protons Hit efficiency with gaps regions included = 99.4% 5-Stage Energy/Range Detector Dividing the energy detector into 5 stages greatly reduces the requirement on energy resolution, allowing effective use of fast plastic scintillators. Stages through which the proton passes directly measure contributions to total range, so the last segment, in which the proton stops, need measure only a small residual range, with only a relaxed precision requirement. Each custom board shown below digitizes the signals from three scintillator- PMT pairs (see the photograph at left). Each 14-bit ADC can operate at rates up to 65 MHz. The FPGA buffers the data and, upon receipt of a trigger, reduces the data by summing 6 samples around the peak of the pulse (1 before and 4 after). A separate amplifier-discriminator chain in each channel provides asynchronous signals for the trigger logic. Differential ADC driver Pipelined ADC Fast amp for trigger Trigger discriminator and threshold DAC FPGA Flash Signal In WEPL Calibration A polystyrene “phantom” with 3 stepped pyramids is used to calibrate the measurement of Water Equivalent Path Length (WEPL). In practice separate runs are executed with the stepped pyramids combined with 0, 1, 2, 3, or 4 polystyrene blocks. The tracking system is used to correlate each proton track with the correct step and with the reconstructed signals from the energy/range detector. The result is that the WEPL of each proton can be reconstructed to an rms precision of 3 mm, close to the theoretical limit due to stochastic range straggling of 2.75 mm for 200 MeV protons. 5-stage energy detector Stepped pyramids plus 4 blocks proton Front tracker Reconstructed WEPL of the phantom after calibration. Rear tracker Above is a display of the raw data from a single proton event, with no phantom present on the rotation stage. On the left are plotted the positions of all SSD strips above threshold in both VU and TU views. On the right are plotted bit ADC samples for each of the five scintillators. The 200 MeV proton stopped in Stage 4. Note that this event is from a diagnostic run in which the individual ADC samples were written out. Each bin represents  15 ns. Normally the pulses are reduced in the front-end FPGA to just a pulse-size sum for each of the five scintillators. The noise level seen in the tracker in this event (i.e. zero noise hits) is typical. Only a few strips out of 9216 have an electronics noise occupancy measuring above 1 hit per million triggers. Tracking Technology 5-Stage Energy Detector Trackers Rotation Stage pCT Data Acquisition (DAQ) Flow The readout is triggered, for ease of synchronization and event building, with ample buffering at the front end to minimize dead time. Eight layers of silicon strip detectors are read out by channel ICs, each with a 100 Mbit/s link to an FPGA on the same board. Similarly, each of the two energy detector boards includes an FPGA. The 14 front-end Spartan-6 FPGAs build the local event data and then send it over dual-link DVI-D cables to the Virtex-6 FPGA, which builds the complete event and then sends it by Ethernet to a computer that is running a custom Python-coded DAQ program. ASIC SSD (½ V or ¼ T) ASIC FPGA Virtex-6 Event Builder FPGA LVDS (Printed Circuits) LVDS (DVI Cables) DAQ Computer Ethernet 32 SSD total 144 ASIC total 4 V layers 4 T layers V layers have 12 ASICs T layers have 24 ASICs SSD (½ V or ¼ T)  9 MHz clock sync. from accelerator 1 Spartan-6 FPGA per V board; 2 per T board 100 Mbps per LVDS link FPGA ADCs FPGA ADCs Five-Stage Scintillator 800 Mbps maximum Example 200 MeV Proton Event v t u Side view Top view 5-stage energy detector signals Between spills. : l Proton CT Image Reconstruction Left (a): A slice of an example CT image reconstructed with data from the completed Phase- II scanner: the CATPHAN 404 module, a cylinder of plastic with several cylindrical inserts of differing materials. The data were collected for 90 stage orientations in 4 degree intervals, with about 3.2 million proton events collected at each angle. Only 51% passed through the reconstruction volume, and 32% of those were rejected by analysis cuts in the data processing. The 3-D image was reconstructed from 99.5 million proton histories, with a voxel size of 0.7 mm x 0.7 mm x 1 mm.) Right (b): An X-ray CT slice from the same phantom. The dashed line corresponds to the profiles shown below the CT images. PMPAir The CATPHAN 404 phantom is reconstructed from 200 MeV proton data taken in May 2015 at CDH. The reconstruction employed a filtered back-projection (FBP) followed by an iterated reconstruction (TVS with DROP) that makes use of the tracking information of individual protons to define a most-likely-path (MLP) through the phantom for each. D. C. Williams, “The most likely path of an energetic charged particle through a uniform medium”. Phys. Med. Biol. 49 (2004) 2899–2911. S. Penfold, “Image Reconstruction and Monte Carlo Simulations in the Development of Proton Computed Tomography for applications in Proton Radiation Therapy” PhD thesis Univ. of Wollongong, The system performs as designed, with a sustained rate of more than a million proton events acquired per second and trigger rates much higher than the maximum data acquisition rate., as illustrated here for both LLU and CDH beams. In the most recent beam test, 2.5 billion events with a total of 1.8  bytes were acquired with zero CRC errors in the data stream, zero parity errors in the command streams, and zero event building errors. Operations at Loma Linda U. (LLU) Synchrotron Spill 2.3 sec on. 2.3 sec off, Beam microstructure of ~100ns. Operations at Central DuPage Hospital (CDH) Cyclotron Continuous beam with small intensity modulations Rotational scan in steps of 2 o or 4 o during beam-off time Continuous rotational scan with 1 rev./min. 1. Real-time alignment 2. Optimization of binning for reconstruction. Beam onBeam off Beam on 3D rendering of the pCT-reconstructed RSP map of a pediatric anthropomorphic head phantom The pCT image of the CIRS head phantom obtained with the Phase II pCT scanner has been tested as input for a 3D-to-3D alignment procedure for treatment-room positioning. Three cardinal planes of 3D RSP images obtained with Phase II scans of the anthropomorphic head phantom. 3-D Reconstruction for in-room Position Verification and image-guided Proton Therapy in Progress Note that these images were taken in two separate scans displaced in the vertical direction. There are some artifacts in these images, which are currently being addressed in the reconstruction algorithm and in the WEPL calibration, usually the root-cause of artifacts in CT. V. Bashkirov et al., Development of proton computed tomography detectors for applications in hadron therapy, Nucl. Instr. Meth. A (in print). V. Bashkirov et al., Novel scintillation detector design and performance for proton radiography and computed tomography, Medical Physics (in print) The pCT scanner consists of two trackers, one preceding and one following the object being imaged, and an energy/range detector that measures the Water Equivalent Path Length (WEPL) of the material through which the proton passed in traversing the object. Together, the two trackers measure the incoming and outgoing proton trajectories, from which the geometric path through the object can be estimated. The stage rotates the object being imaged. pCT Scanner in the CDH Proton Beam Line Work is in progress to employ space-carving algorithms to define the reconstruction volume and eliminate the FBP. Progress has also been made on parallelized reconstruction algorithms that run on an array of GPUs. Full reconstructions have been completed in under 8 minutes, similar to the beam time required to acquire the data. The relative stopping power (RSP) of the variety of materials in the CATPHAN 404 phantom is accurately measured,. Spatial Resolution Studies: Edge Phantom A phantom was designed and fabricated for the purpose of measuring a modulation transfer function (MTF) T. Plautz, IUPESM World Congress 2015, Toronto, ON July 2015, CDH: 7 min continuous scan (1 rev/min), 150 Million histories, 1 mm x 1 mm x 1 mm voxel size, 1 deg angular bin size. Spatial Resolution is close to maximum (for 1mm pixels the Nyquist frequency is 5 lp/cm). MTF varies as a function of radius by ± 10-20%. MTF is the function of relative modulation with respect to spatial frequency (lp/cm) that characterizes the resolution of an imaging system. The authors acknowledge the support of Dr. Mark Pankuch during data taking at CDH. DAQ Performance Goal of sustained MHz+ operation has been reached (even at higher trigger rates)!