Activities for Proton Computed Tomography PCT Loma Linda University Medical Center Hartmut F.-W. Sadrozinski Santa Cruz Inst. for Particle Physics SCIPP State University of New York at Stony Brook UCSC Santa Cruz Institute of Particle Physics INFN Florence & Catania

The Proton CT Collaboration Proton Treatment: LLUMC Particle Tracking Systems: SCIPP, INFN Firenze Energy Detectors: BNL, LLUMC, INFN Catania Monte Carlo Simulation (GEANT 4): BNL, SCIPP, INFN, SLAC Image Reconstruction: SUNY Stony Brook Goal –Develop proton CT for applications in proton therapy Specific Aims –Design, construct and test components of a modular proton CT system –Develop, test, and optimize a dose-efficient image reconstruction algorithm –Evaluate performance of proton CT prototype

Why Proton CT? Major advantages of proton beam therapy: –Finite range in tissue (protection of critical normal tissues) since cross section fairly flat and low away from peak –Maximum dose and effectiveness at end of range (Bragg peak effect) Major uncertainties of proton beam therapy: –range uncertainty due to use of X-ray CT for treatment planning (up to several mm) –patient setup variability Goal of pCT Collaboration Develop proton CT for applications in proton therapy

Computed Tomography (CT) X-ray tube Detector array XCT: Based on X-ray absorption Faithful reconstruction of patient’s anatomy Stacked 2D maps of linear X-ray attenuation Coupled linear equations Invert matrices and reconstruct z- dependent features Proton CT: replaces X-ray absorption with proton energy loss reconstruct mass density (  distribution instead of electron distribution

Proton CT System (Final & prototype)

Comparison pCT - X-ray CT

Challenge One: Calorimeter Resolution Can achieve proton energy resolution much better than energy straggling (~1%) Dose to the patient during imaging depends on the square of the effective energy resolution (including beam straggling) “First Experimental Calorimeter Studies for Proton CT at LLUMC”, M. C. L. Klock, R. W. Schulte, V.Bashkirov, et al., submitted to Nucl. Inst. Meth.

Challenge Two: High-speed DAQ SSD PFME FPGA Hardware: Modular Commercial Hartmut Sadrozinski et al., IEEE TRANS ON NUCL. SCIE., VOL. 51, NO. 5, 1 (NI 6534).

Fig. 7. Reference system for the simulation study. The phantom is centered at u =15 cm, t = 3.5 cm. The protons arrive along the u direction at plane u = 0 cm. The entry and exit detector planes are at u = 0 cm and u = 30 cm respectively. Images of the phantom shown in Fig. 7 reconstructed from a simulated data set of (a) 35,000 proton histories and (b) 8,750 proton histories per projection. In the left images all holes had an object contrast of 100%, in the center images the contrast of the top, center, and bottom row of holes was 30%, 20%, and 10%, respectively, and in the left images Challenge Four: Low-Dose Image reconstruction

Challenge Four: Image of Al Annulus Subdivide SSD area into pixels 1.Strip x strip 194um x 194um 2. 4 x 4 strips (0.8mm x 0.8mm) Image corresponds to average energy in pixel “Initial studies on proton computed tomography using a silicon strip detector telescope”, L. Johnson et al., NIM. A 514 (2003) 215

Beam Test Improvements Improvements: –Increased precision of input parameters (entrance angle) needed to correct for beam divergence –Calorimeter DAQ –Geant4 description of data and understanding of “Banana” in non- uniform medium Next Steps: NON-uniform phantom (non-uniform density and/or shape, small aninal?) pCT Reconstruction: FBP, Layer-by-layer deconvolution

Banana Improvements Add non-uniformities of phantom to “banana” Needs to be validated with GEANT4 How to add into reconstruction?

Beam Test Improvements: Resolution Theoretical Resolution in pCT set-up as a function of distance z1 in first telescope. In Tel L= 20 cm z 4 =3cm Measure x1, x2, x4, x5 and, reconstruct displacement d and entrance angle  and exit angle 

Beam Test Improvements: Resolution Theoretical Resolution in pCT set-up as a function of distance z1 in first telescope. Measure x1, x2, x4, x5 and, reconstruct displacement d and entrance angle  and exit angle 

Acknowledgments LLUMC Reinhartd Schulte, MD Vladimir Bashkirov, PhD George Coutrakon, PhD Peter Koss, MS SUNY Stony Brook Jerome Z. Liang, PhD Klaus Mueller, PhD Tianfang Li (grad student) INFN Catania Pablo Cirrone, PhD Giacomo Cuttone, PhD Nunzio Randazzo, PhD Domenico Lo Presti, Engineer Valeria Sipali (grad student) Brookhaven National Laboratory Steve Peggs, PhD Todd Satogata, PhD Craig Woody, PhD Florence U. Mara Bruzzi, PhD David Menichelli, PhD Monica Scaringella (grad student) Santa Cruz Institute of Particle Physics Hartmut Sadrozinski, PhD Abe Seiden, PhD David C Williams, PhD Zhan Lang, PhD Brian Keeney (grad. Student) Jason Feldt (grad. Student) Jason Heimann (undergrad student) Dominic Lucia (undergrad student) Nate Blumenkrantz (undergrad student) Eric Scott (undergrad student)