1. Custom IC Design and Data Acquisition Robert P. Johnson Santa Cruz Institute for Particle Physics University of California Santa Cruz Proton Computed Tomography using Silicon-Strip Detectors 5/22/2014 1 Proton Computed Tomography

2. Collaborators in Building the pCT Scanner 5/22/2014 Proton Computed Tomography 2 U.C. Santa Cruz: Robert Johnson Hartmut Sadrozinski Joel DeWitt Andriy Zatserklyaniy Tia Plautz LLUMC: Reinhard Schulte, M.D. Vladimir Bashkirov Ford Hurley Nick Vence Valentina Giacometti Front-end and DAQ electronics

3. Outline 5/22/2014 Proton Computed Tomography 3 Introduction to pCT Pre-clinical scanner prototype Tracking System Energy Detector Data Acquisition Tracker Front-End ASIC Tracker Performance Noise occupancy Hit efficiency Bad channel rates DAQ System Performance

4. Proton Radiation Therapy 5/22/2014 Proton Computed Tomography 4 The proton beam is tuned such that the protons stop in the tumor, depositing most of their energy there. Compared with photon radiation (X-ray or  -ray), a higher does can be delivered to the tumor while minimizing exposure to surrounding tissue. Energy deposition vs. depth for several beam energies. Total proton dose vs. depth (sum of blue curves)  -ray dose vs. depth “Bragg Peak” placed in tumor region Zero dose behind the tumor!

5. Why the Interest in Proton CT? 5/22/2014 Proton Computed Tomography 5 Alderson Head Phantom Range Uncertainties (measured with PTR) > 5 mm > 10 mm > 15 mm Schneider U. & Pedroni E. (1995), “Proton radiography as a tool for quality control in proton therapy,” Med Phys. 22, 353. X-ray CT use in proton cancer therapy can lead to significant uncertainties in range determination, which limits its use in the case of some tumors located close to critical healthy tissue. Proton CT can measure directly the density distribution needed for range calculation, is less affected by intervening dense structures, and is unaffected by “beam hardening”.

6. Fermi-LAT Tracker/Converter Heritage 5/22/2014 Proton Computed Tomography 6 73 m 2 of Si (>10,000 SSDs) 880,000 channels 160 Watts In orbit since June 2008 W. Atwood et al., Design and Initial Tests of the Tracker-Converter of the Gamma-ray Large Area Space Telescope, Astroparticle Physics 28, 422-434, 2007. Our first prototype pCT scanner used the Fermi Tracker electronics and SSDs, but a much faster, specialized ASIC is needed for clinically realistic rates.

7. pCT Instrument Concept 5/22/2014 Proton Computed Tomography 7 Object being imaged (a calibration device is shown) Proton range detector Pair of silicon-strip based trackers. Incoming 200 MeV KE proton Tracking detectors based on silicon-strip sensors measure track vectors entering and exiting the object being imaged.  From this the protons path through the object is estimated. A range detector stops the proton and measures the residual range.  From this the Water Equivalent Path Length through the object is inferred. T U V H.F.-W. Sadrozinski et al, Development of a Head Scanner for Proton CT, Nucl. Instr. Meth A 699 (2013) 205.

8. The Actual Instrument 5/22/2014 Proton Computed Tomography 8 Tracker Modules Beam Rotating Stage Range Detector Range Detector Electronics Event Builder T V

9. Silicon-Strip Sensor Orientations 5/22/2014 Proton Computed Tomography 9 Measures V Coordinates Measures T Coordinates 384 strips ASICs Single-sided, AC coupled, 400  m n-on-p HPK sensors, left-over from the Fermi-LAT. We sawed off the sensor edges to minimize the gaps! After cut

10. Inside of one Tracker Module 5/22/2014 Proton Computed Tomography 10 V ASIC Spartan-6 FPGA Two V boards and two T boards

11. One Tracker “Cassette,” T side 5/22/2014 Proton Computed Tomography 11 Vertical strips Spartan-6 FPGAs ASICs DVI connector Power connector The T side has twice and many amplifier channels as the V side, and two FPGAs, each with a dedicated data line to the event builder. T

12. Range Detector Digitizer Board 5/22/2014 Proton Computed Tomography 12 FPGA 14-bit 65 MHz ADC (AD9244) Amplifier and differential ADC driver (AD8138) PMT signal Fast inverting amplifier Threshold DAC Trigger comparator with LVDS output Each of the 5 channels has a 14-bit 65 MHz pipeline ADC plus a separate amplifier and discriminator for triggering. Typical digitized PMT signal.

13. Data Acquisition Concept 5/22/2014 Proton Computed Tomography 13 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 During acquisition of image data, the system is triggered by the first scintillator stage. Triggered readout, not data driven. Designed to read out more than a million proton events per second.

14. 5/22/2014 Proton Computed Tomography 14 pCT Tracker ASIC Layout 100 MHz digital clock and 100 Mbps LVDS data output. Single-threshold digitization (binary output). 64 amplifiers are always active and supply a 64-wide-OR trigger as well as data. Output data are formatted as a list of clusters (first strip and number of strips). TSMC 0.25 micron CMOS

15. ASIC Features 5/22/2014 Proton Computed Tomography 15 Internal calibration system to pulse any set of channels with a programmable charge. RC/CR pulse shape with 200 ns peaking time. Two gain options. Also a 400 ns peaking time option. Extra optional inverter for p-on-n SSDs. Threshold programmed by an 8-bit DAC common to all channels. Digital 1-shot on each channel to define a hit window comparable to the accelerator beam RF period (~110 ns). 64-wide OR for self triggering. Two 64-bit masks to isolate noisy channels from the trigger and/or data stream. 32 deep FIFO to hold the hits during trigger latency. 4 independent event buffers, each with a processor to form the cluster lists for output. Digital commands to configure the system, load registers, and verify registers. e.g. set sample clock frequency. R. Johnson et al., Tracker Readout ASIC for Proton Computed Tomography Data Acquisition, IEEE Trans. Nucl. Sci. 60, 3262-3269, 2013

16. ASIC Noise Performance 5/22/2014 Proton Computed Tomography 16 Example threshold scans for eight adjacent channels. 18-cm long SSD strips (V-board strips). From the erfc fits, the noise sigma is about 1100 e. The relatively large total bias current on the edge-cut SSDs does not impact the strip noise performance. ENC = 280 + 35  C pF electrons The expected signal from a 200 MeV proton is about 60,000 electrons, so there is excessive noise margin!  It would be advantageous to go to 200  m SSDs to reduce multiple scattering. Gain variation: 2% rms within a chip 5% rms chip to chip Threshold DAC Setting Efficiency 60120 Analog power: 1.2 mW/channel Digital power: 2.3 mW/channel (100 MHz) Hold the charge- injection level constant and measure the detection efficiency versus discriminator threshold.

17. Noise Occupancy (Random Triggers) 5/22/2014 Proton Computed Tomography 17 Note: fC scale presently has an uncertainty of up to 30%. The signal from our highest momentum protons is over 9 fC Thus the amplifier noise is nearly negligible. The few noisy strips that are present in the system are due to defective SSD strips.

18. Tracker Hit Efficiency 5/22/2014 Proton Computed Tomography 18 To minimize confusion from overlapping protons, the time window to capture a hit must be less than about 100 ns. Hence the threshold must be set low enough relative to the expected signal that time jitter will be low. And the efficiency of getting all 8 SSD hits must be high.  We have no redundant detector planes, except that in the front telescope the beam spot can substitute for one measurement.  If a hit is missing and the track projects close to a known dead strip or a gap, that location can be assumed to be hit. This emphasizes the great importance of having high signal/noise.

19. 5/22/2014 Proton Computed Tomography 19 Bad strips Gaps between sensors Tracking resolution near the edge of the acceptance The measured hit efficiency generally lies between 98% and 99%, including gaps between detectors and bad strips. Note: the SSDs were run under-depleted at 75V bias (full depletion requires about 100V).

20. Bad Channels 5/22/2014 Proton Computed Tomography 20 The ASICs were not tested prior to assembly, and so far the yield has been 100% out of about 200 chips. Noisy and dead channels typically are due to bad detector strips, not the ICs. We found only 24 such channels in the system, out of 9216 channels, or about 0.3%.  These are leftover Hamamatsu-Photonics sensors from fabrication of the tracker of the Fermi orbiting gamma-ray telescope.

21. Residuals from Straight-Line Fits 5/22/2014 Proton Computed Tomography 21 (Before making alignment corrections.)

22. Data Acquisition Rate 5/22/2014 Proton Computed Tomography 22 Trigger Rate Acquired-Event Rate The accelerator spill intensity needs to be improved in uniformity, but the instrument succeeds in delivering our goal of a million events per second.

23. Conclusions 5/22/2014 Proton Computed Tomography 23 Our pCT scanner is now fully operational and able to take data at an event rate above 1 MHz. The Tracker ASIC met all of our requirements in the first submission and had a very high yield. The custom data acquisition system based on FPGAs meets our goal of >1 million protons per second. Future goals:  Increase the proton rate up to 5 to 10 MHz by designing and building a segmented range detector (to measure simultaneous protons).  This could get the scan time down to 1 or 2 minutes.  Transfer the technology to industry (e.g. Varian).

24. Extra Slides 5/22/2014 Proton Computed Tomography 24

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28. Residuals from Straight-Line Fits 5/22/2014 Proton Computed Tomography 28