First application of the GPU-based software framework TIGRE for proton CT image reconstruction

Published:April 10, 2021DOI:


      • First application of the GPU-based framework TIGRE to proton CT image reconstruction.
      • Geant4 simulations were used to generate reconstruction input data.
      • A straight-line approximation allowed reconstruction within seconds.
      • Tomographic images of two Catphan modules were analyzed.
      • An image resolution of three line pairs per cm was achieved.


      In proton therapy, the knowledge of the proton stopping power, i.e. the energy deposition per unit length within human tissue, is essential for accurate treatment planning. One suitable method to directly measure the stopping power is proton computed tomography (pCT). Due to the proton interaction mechanisms in matter, pCT image reconstruction faces some challenges: the unique path of each proton has to be considered separately in the reconstruction process adding complexity to the reconstruction problem. This study shows that the GPU-based open-source software toolkit TIGRE, which was initially intended for X-ray CT reconstruction, can be applied to the pCT image reconstruction problem using a straight line approach for the proton path. This simplified approach allows for reconstructions within seconds.
      To validate the applicability of TIGRE to pCT, several Monte Carlo simulations modeling a pCT setup with two Catphan® modules as phantoms were performed. Ordered-Subset Simultaneous Algebraic Reconstruction Technique (OS-SART) and Adaptive-Steepest-Descent Projection Onto Convex Sets (ASD-POCS) were used for image reconstruction. Since the accuracy of the approach is limited by the straight line approximation of the proton path, requirements for further improvement of TIGRE for pCT are addressed.


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        • Cormack A.M.
        Representation of a function by its line integrals, with some radiological applications.
        J Appl Phys. 1963; 34: 2722-2727
        • Schulte R.
        • Bashkirov V.
        • Li T.
        • Liang Z.
        • Mueller K.
        • Heimann J.
        • et al.
        Conceptual design of a proton computed tomography system for applications in proton radiation therapy.
        IEEE Trans Nucl Sci. 2004; 51: 866-872
        • Schneider U.
        • Besserer J.
        • Pemler P.
        • Dellert M.
        • Moosburger M.
        • Pedroni E.
        • et al.
        First proton radiography of an animal patient.
        Med Phys. 2004; 31: 1046-1051
        • Bortfeld T.R.
        • Loeffler J.S.
        Three ways to make proton therapy affordable.
        Nat News. 2017; 549: 451
        • Schneider U.
        • Pedroni E.
        • Lomax A.
        The calibration of CT Hounsfield units for radiotherapy treatment planning.
        Phys Med Biol. 1996; 41: 111-124
        • Yang M.
        • Zhu X.R.
        • Park P.C.
        • Titt U.
        • Mohan R.
        • Virshup G.
        • et al.
        Comprehensive analysis of proton range uncertainties related to patient stopping-power-ratio estimation using the stoichiometric calibration.
        Phys Med Biol. 2012; 57: 4095
        • Schulte R.W.
        • Bashkirov V.
        • Li T.
        • Liang Z.
        • Mueller K.
        • Heimann J.
        • et al.
        Conceptual design of a proton computed tomography system for applications in proton radiation therapy.
        IEEE Trans Nucl Sci. 2004; 51: 866-872
        • Esposito M.
        • Waltham C.
        • Taylor J.T.
        • Manger S.
        • Phoenix B.
        • Price T.
        • et al.
        Pravda: The first solid-state system for proton computed tomography.
        Phys Med. 2018; 55: 149-154
        • Scaringella M.
        • Bruzzi M.
        • Bucciolini M.
        • Carpinelli M.
        • Cirrone G.
        • Civinini C.
        • et al.
        A proton computed tomography based medical imaging system.
        J Instrumen. 2014; 9: C12009
        • Collins-Fekete C.A.
        • Brousmiche S.
        • Portillo S.K.
        • Beaulieu L.
        • Seco J.
        A maximum likelihood method for high resolution proton radiography/proton ct.
        Phys Med Biol. 2016; 61: 8232
        • Williams D.
        The most likely path of an energetic charged particle through a uniform medium.
        Phys Med Biol. 2004; 49: 2899
        • Schulte R.
        • Penfold S.
        • Tafas J.
        • Schubert K.
        A maximum likelihood proton path formalism for application in proton computed tomography.
        Med Phys. 2008; 35: 4849-4856
        • Wang D.
        • Mackie T.R.
        • Tomé W.A.
        Bragg peak prediction from quantitative proton computed tomography using different path estimates.
        Phys Med Biol. 2011; 56: 587
        • Rit S.
        • Dedes G.
        • Freud N.
        • Sarrut D.
        • Létang J.M.
        Filtered backprojection proton CT reconstruction along most likely paths.
        Med Phys. 2013; 40031103
        • Hansen D.C.
        • Sørensen T.S.
        • Rit S.
        Fast reconstruction of low dose proton ct by sinogram interpolation.
        Phys Med Biol. 2016; 61: 5868
        • Biguri A.
        • Dosanjh M.
        • Hancock S.
        • Soleimani M.
        TIGRE: a MATLAB-GPU toolbox for CBCT image reconstruction.
        Biomed Phys Eng Expr. 2016; 2055010
        • Kazemi S.
        • Diaz O.
        • Elangovan P.
        • Wells K.
        • Lohstroh A.
        Validation and application of a new image reconstruction software toolbox (TIGRE) for breast cone-beam computed tomography.
        in: Medical Imaging 2018: Physics of Medical Imaging. 10573. International Society for Optics and Photonics, 2018: 105735E
        • Despres P.
        • Jia X.
        A review of gpu-based medical image reconstruction.
        Phys Med. 2017; 42: 76-92
        • Hansen M.S.
        • Sørensen T.S.
        Gadgetron: an open source framework for medical image reconstruction.
        Magn Resonan Med. 2013; 69: 1768-1776
        • Karbasi P.
        • Cai R.
        • Schultze B.
        • Nguyen H.
        • Reed J.
        • Hall P.
        • et al.
        A highly accelerated parallel multi-gpu based reconstruction algorithm for generating accurate relative stopping powers.
        IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE. 2017; 2017: 1-4
        • Morgan L.
        • Finnegan P.
        Benefits and drawbacks of open source software: an exploratory study of secondary software firms.
        in: IFIP International Conference on Open Source Systems. Springer, 2007: 307-312
        • Schultze B.
        • Censor Y.
        • Karbasi P.
        • Schubert K.E.
        • Schulte R.W.
        An improved method of total variation superiorization applied to reconstruction in proton computed tomography.
        IEEE Trans Med Imaging. 2019; 39: 294-307
        • Lee J.
        • Kim C.
        • Min B.
        • Kwak J.
        • Park S.
        • Lee S.B.
        • et al.
        Sparse-view proton computed tomography using modulated proton beams.
        Med Phys. 2015; 42: 1129-1137
        • Censor Y.
        • et al.
        Block-Iterative Algorithms with Diagonally Scaled Oblique Projections for the Linear Feasibility Problem.
        SIAM J Matrix Anal Appl. 2002; 24: 40-58
        • Andersen A.H.
        • Kak A.C.
        Simultaneous algebraic reconstruction technique (sart): a superior implementation of the art algorithm.
        Ultrasonic Imaging. 1984; 6: 81-94
        • Sidky E.Y.
        • Pan X.
        Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization.
        Phys Med Biol. 2008; 53: 4777
        • Ulrich-Pur F.
        • Bergauer T.
        • Burker A.
        • Hatamikia S.
        • Hirtl A.
        • Irmler C.
        • et al.
        Imaging with protons at MedAustron.
        Nucl Instrum Methods Phys Res A. 2020; 978164407
        • Donahue W.
        • Newhauser W.D.
        • Ziegler J.F.
        Analytical model for ion stopping power and range in the therapeutic energy interval for beams of hydrogen and heavier ions.
        Phys Med Biol. 2016; 61: 6570
        • Bragg W.H.
        • Kleeman R.
        XXXIX. On the αParticles of Radium, and their Loss of Range in passing through various Atoms and Molecules.
        Lond Edinburgh Dublin Philos Mag J Sci. 1905; 10: 318-340
        • Khellaf F.
        • Krah N.
        • Létang J.M.
        • Collins-Fekete C.A.
        • Rit S.
        A comparison of direct reconstruction algorithms in proton computed tomography.
        Phys Med Biol. 2020; 65105010
        • Brooke M.D.
        • Penfold S.N.
        An inhomogeneous most likely path formalism for proton computed tomography.
        Phys Med. 2020; 70: 184-195
        • Paganetti H.
        Dose to water versus dose to medium in proton beam therapy.
        Phys Med Biol. 2009; 54: 4399
        • Biegun A.
        • van Goethem M.
        • van der Graaf E.
        • van Beuzekom M.
        • Koffeman E.
        • Nakaji T.
        • et al.
        The optimal balance between quality and efficiency in proton radiography imaging technique at various proton beam energies: A monte carlo study.
        Phys Med. 2017; 41: 141-146
        • Cirrone G.A.P.
        • Bucciolini M.
        • Bruzzi M.
        • Candiano G.
        • Civinini C.
        • Cuttone G.
        • et al.
        Monte carlo evaluation of the filtered back projection method for image reconstruction in proton computed tomography.
        Nucl Instrum Methods Phys Res A. 2011; 658: 78-83
        • Agostinelli S.
        • Allison J.
        • et al.
        Amako K.a., Apostolakis J., Araujo H., Arce P., Geant4-a simulation toolkit. Nuclear instruments and methods in physics research section A.
        Accel Spectrom Detect Assoc Equip. 2003; 506: 250-303
      1. The Phantom Laboratory. Catphan 600®Manual. 2015.; accessed: 2021-01-15.

        • Volz L.
        • Piersimoni P.
        • Bashkirov V.A.
        • Brons S.
        • Collins-Fekete C.A.
        • Johnson R.P.
        • et al.
        The impact of secondary fragments on the image quality of helium ion imaging.
        Phys Med Biol. 2018; 63195016
        • Michalak G.
        • Taasti V.
        • Krauss B.
        • Deisher A.
        • Halaweish A.
        • McCollough C.
        A comparison of relative proton stopping power measurements across patient size using dual-and single-energy ct.
        Acta Oncol. 2017; 56: 1465-1471
        • Soret M.
        • Bacharach S.L.
        • Buvat I.
        Partial-volume effect in pet tumor imaging.
        J Nucl Med. 2007; 48: 932-945
        • Seco J.
        • Oumano M.
        • Depauw N.
        • Dias M.F.
        • Teixeira R.P.
        • Spadea M.F.
        Characterizing the modulation transfer function (mtf) of proton/carbon radiography using monte carlo simulations.
        Med Phys. 2013; 40091717
        • Li T.
        • Liang Z.
        • Singanallur J.V.
        • Satogata T.J.
        • Williams D.C.
        • Schulte R.W.
        Reconstruction for proton computed tomography by tracing proton trajectories: A monte carlo study.
        Med Phys. 2006; 33: 699-706
        • Giacometti V.
        • Bashkirov V.A.
        • Piersimoni P.
        • Guatelli S.
        • Plautz T.E.
        • Sadrozinski H.F.W.
        • et al.
        Software platform for simulation of a prototype proton CT scanner.
        Med Phys. 2017; 44: 1002-1016
      2. Schultze B., Karbasi P., Giacomelli V., Plautz T., Schübert K.E., Schulte R.W.. Reconstructing highly accurate relative stopping powers in proton computed tomography. In: 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE; 2015, p. 1–3.

        • Hatamikia S.
        • Biguri A.
        • Kronreif G.
        • Kettenbach J.
        • Russ T.
        • Furtado H.
        • et al.
        Optimization for customized trajectories in cone beam computed tomography.
        Med Phys. 2020;