Skip to main content
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
1.A. Cormack, “Representation of a function by its line integrals, with some radiological applications,” J. Appl. Phys. 34(9), 27222727 (1963).
2.R. Schulte et al., “Density resolution of proton computed tomography,” Med. Phys. 32(4), 10351046 (2005).
3.J. Seco and N. Depauw, “Proof of principle study of the use of a CMOS active pixel sensor for proton radiography,” Med. Phys. 38(2), 622623 (2011).
4.U. Schneider et al., “First proton radiography of an animal patient,” Med. Phys. 31(5), 10461051 (2004).
5.R. F. Hurley et al., “Water-equivalent path length calibration of a prototype proton CT scanner,” Med. Phys. 39(5), 24382446 (2012).
6.B. Schaffner and E. Pedroni, “The precision of proton range calculations in proton radiotherapy treatment planning: Experimental verification of the relation between CT-HU and proton stopping power,” Phys. Med. Biol. 43, 15791592 (1998).
7.H. Paganetti, “Range uncertainties in proton therapy and the role of Monte Carlo simulations,” Phys. Med. Biol. 57(11), R99R117 (2012).
8.U. Schneider, P. Pemler, J. Besserer, E. Pedroni, A. Lomax, and B. Kaser-Hotz, “Patient specific optimization of the relation between CT-Hounsfield units and proton stopping power with proton radiography,” Med. Phys. 32(1), 195199 (2005).
9.N. Depauw, M. F. Dias, A. Rosenfeld, and J. C. Seco, “Ion radiography as a tool for patient set-up & image guided particle therapy: A Monte Carlo study,” Technol. Cancer Res. Treat. 13, 6976 (2014).
10.M. Testa et al., “Proton radiography and proton computed tomography based on time-resolved dose measurements,” Phys. Med. Biol. 58(22), 82158233 (2013).
11.U. Schneider, J. Besserer, and M. Hartmann, “Technical note: Spatial resolution of proton tomography: Impact of air gap between patient and detector,” Med. Phys. 39(2), 798800 (2012).
12.P. Pemler et al., “A detector system for proton radiography on the gantry of the Paul-Scherrer-Institute,” Nucl. Instrum. Methods Phys. Res., Sect. A 432(2-3), 483495 (1999).
13.H. Shinoda, T. Kanai, and T. Kohno, “Application of heavy-ion CT,” Phys. Med. Biol. 51(16), 40734081 (2006).
14.R. Schulte et al., “Conceptual design of a proton computed tomography system for applications in proton radiation therapy,” IEEE Trans. Nucl. Sci. 51(3), 866872 (2004).
15.C. Talamonti et al., “Proton radiography for clinical applications,” Nucl. Instrum. Methods Phys. Res., Sect. A 612(3), 571575 (2010).
16.V. Sipala et al., “PRIMA: An apparatus for medical application,” Nucl. Instrum. Methods Phys. Res., Sect. A 658, 7377 (2011).
17.G. Poludniowski et al., “Proton-counting radiography for proton therapy: A proof of principle using CMOS APS technology,” Phys. Med. Biol. 59(11), 25692581 (2014).
18.P. S. Friedman et al., “Plasma panel sensors for particle and beam detection,” IEEE Nuclear Science Symposium Medical Imaging Conference Record, Anaheim, CA (IEEE, 2012), pp. 17751780.
19.R. Ball et al., “Development of a plasma panel radiation detector,” Nucl. Instrum. Methods Phys. Res., Sect. A 764, 122132 (2014).
20.S. Braccini et al., “First results on proton radiography with nuclear emulsion detectors,” J. Instrum. 5(09), 114 (2010).
21.D. Watts et al., “A proton range telescope for quality assurance in hadrontherapy,” in  IEEE Nuclear Science Symposium Conference Record, Orlando, FL (IEEE, 2009), pp. 41634166.
22.R. Hollebeek et al., “A new technology for fast two-dimensional detection of proton therapy beams,” Phys. Res. Int. 2012(i), 111 (2012).
23.M. Akisada, J. Ohashi, and K. Kondo, “Conceptual design of proton computed tomography with magnetic spectrometer,” Jpn. J. Appl. Phys. 22(4), 752758 (1983).
24.U. Schneider and E. Pedroni, “Proton radiography as a tool for quality control in proton therapy,” Med. Phys. 22(4), 353363 (1995).
25.J. Heimann, “Developing an FPGA-based readout for the pCT detector system” (University of California Berkeley, CA, 2005).
26.M. Petterson et al., “Proton radiography studies for proton CT,” IEEE Nuclear Science Symposium Conference Record, San Diego, CA (IEEE, 2006), pp. 2276–2280.
27.E. Vanzi et al., “The PRIMA collaboration: Preliminary results in FBP reconstruction of pCT data,” Nucl. Instrum. Methods Phys. Res., Sect. A 730, 184190 (2013).
28.V. A. Bashkirov, R. W. Schulte, S. N. Penfold, S. Member, and A. B. Rosenfeld, “Proton computed tomography: Update on current Status,” IEEE Nuclear Science Symposium Conference Record HT6–1, Honolulu, HI (IEEE, 2007), pp. 46854688.
29.I. Rinaldi et al., “Experimental characterization of a prototype detector system for carbon ion radiography and tomography,” Phys. Med. Biol. 58(3), 413427 (2013).
30.I. Rinaldi, S. Brons, O. Jäkel, B. Voss, and K. Parodi, “Experimental investigations on carbon ion scanning radiography using a range telescope,” Phys. Med. Biol. 59(12), 30413057 (2014).
31.H. Ryu, E. Song, J. Lee, and J. Kim, “Density and spatial resolutions of proton radiography using a range modulation technique,” Phys. Med. Biol. 53(19), 54615468 (2008).
32.H. Muraishi et al., “Evaluation of spatial resolution for heavy ion CT system based on the measurement of residual range distribution with HIMAC,” IEEE Trans. Nucl. Sci. 56(5), 27142721 (2009).
33.E. Bentefour, D. Samuel, M. Testa, and H.-M. Lu, “Methods and device for dose based proton radiography,” Med. Phys. 40(6), 308 (2013).
34.J. Telsemeyer, O. Jäkel, and M. Martišíková, “Quantitative carbon ion beam radiography and tomography with a flat-panel detector,” Phys. Med. Biol. 57(23), 79577971 (2012).
35.E. Gelover-Reyes, F. Jimenez-Sprang, I. Rosenberg, D. D’Souza, and G. Royle, “Proton radiography with silicon active sensors,” in ESTRO Proceedings (ESTRO, London, 2011), p. S531.
36.H.-M. Lu, “A point dose method for in vivo range verification in proton therapy,” Phys. Med. Biol. 53(23), N415N422 (2008).
37.H.-M. Lu, G. Mann, and E. Cascio, “Investigation of an implantable dosimeter for single-point water equivalent path length verification in proton therapy,” Med. Phys. 37(11), 5858 (2010).
38.H.-M. Lu, “A potential method for in vivo range verification in proton therapy treatment,” Phys. Med. Biol. 53(5), 14131424 (2008).
39.B. Gottschalk, S. Tang, E. H. Bentefour, E. Cascio, D. Prieels, and H.-M. Lu, “Water equivalent path length measurement in proton radiotherapy using time resolved diode dosimetry,” Med. Phys. 38(4), 22822288 (2011).
40.E. H. Bentefour, M. Testa, and H.-M. Lu, “In-vivo WEPL verification based on point dose measurements in proton treatment by beam scanning,” in PTCOG (PTCOG, 2012), Vol. 51, p. 3855.
41.T. Bortfeld, “An analytical approximation of the Bragg curve for therapeutic proton beams,” Med. Phys. 24(12), 20242033 (1997).
42.S. Bohndiek et al., “Characterization studies of two novel active pixel sensors,” Opt. Eng. 46(12), 124003 (2007).
43.S. A. Basun, R. S. Meltzer, and G. F. Imbusch, “Exchange-coupled chromium ion pairs in ruby revisited,” J. Lumin. 125(1-2), 3139 (2007).
44.S. Ganschow, D. Klimm, and R. Bertram, “On the effect of oxygen partial pressure on the chromium distribution coefficient in melt-grown ruby crystals,” J. Cryst. Growth 325(1), 8184 (2011).
45.J. Boone and A. Chavez, “Comparison of x-ray cross sections for diagnostic and therapeutic medical physics,” Med. Phys. 23(12), 19972005 (1996).
46.J. Berger and M. Zucker, ESTAR, PSTAR, and ASTAR: Computer Programs for Calculating Stopping-Power and Range Tables for Electrons, Protons, and Helium Ions (version 1.2.2),National Institute of Standards and Technology, 2004, available:
47.N. Hünemohr, B. Krauss, C. Tremmel, B. Ackermann, O. Jäkel, and S. Greilich, “Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates,” Phys. Med. Biol. 59(1), 8396 (2014).
48.M. Esposito, T. Anaxagoras, and O. Diaz, “Radiation hardness of a large area CMOS Active Pixel Sensor for bio-medical applications,” IEEE Nuclear Science Symposium Conference Record, Anaheim, CA (IEEE, 2012), Vol.N14, Iss. 183, pp. 13001304.
49.S. Meroli, D. Passeri, L. Servoli, and A. Angelucci, “Analysis of the performance of CMOS APS imagers after proton damage,” J. Instrum. 8(02), 15 (2013).
50.M. Esposito et al., “Ionizing and non ionizing radiation damage in a large area CMOS active pixel sensor for medical applications,” IEEE Trans. Nucl. Sci. 18 (2014), available at
51.G. D. Stewart, Silicon Pixel Detectors for Synchrotron Applications (University of Glasgow, Scotland, 2013).
52.A. C. Konstantinidis, A. Olivo, P. R. T. Munro, S. E. Bohndiek, and R. D. Speller, “Optical characterisation of a CMOS active pixel sensor using periodic noise reduction techniques,” Nucl. Instrum. Methods Phys. Res., Sect. A 620, 549556 (2010).

Data & Media loading...


Article metrics loading...



In recent years, there has been a movement toward single-detector proton radiography, due to its potential ease of implementation within the clinical environment. One such single-detector technique is the dose ratio method in which the dose maps from two pristine Bragg peaks are recorded beyond the patient. To date, this has only been investigated on the distal side of the lower energy Bragg peak, due to the sharp falloff. The authors investigate the limits and applicability of the dose ratio method on the proximal side of the lower energy Bragg peak, which has the potential to allow a much wider range of water-equivalent thicknesses (WET) to be imaged. Comparisons are made with the use of the distal side of the Bragg peak.

Using the analytical approximation for the Bragg peak, the authors generated theoretical dose ratio curves for a range of energy pairs, and then determined how an uncertainty in the dose ratio would translate to a spread in the WET estimate. By defining this spread as the accuracy one could achieve in the WET estimate, the authors were able to generate lookup graphs of the range on the proximal side of the Bragg peak that one could reliably use. These were dependent on the energy pair, noise level in the dose ratio image and the required accuracy in the WET. Using these lookup graphs, the authors investigated the applicability of the technique for a range of patient treatment sites. The authors validated the theoretical approach with experimental measurements using a complementary metal oxide semiconductor active pixel sensor (CMOS APS), by imaging a small sapphire sphere in a high energy proton beam.

Provided the noise level in the dose ratio image was 1% or less, a larger spread of WETs could be imaged using the proximal side of the Bragg peak (max 5.31 cm) compared to the distal side (max 2.42 cm). In simulation, it was found that, for a pediatric brain, it is possible to use the technique to image a region with a square field equivalent size of 7.6 cm2, for a required accuracy in the WET of 3 mm and a 1% noise level in the dose ratio image. The technique showed limited applicability for other patient sites. The CMOS APS demonstrated a good accuracy, with a root-mean-square-error of 1.6 mm WET. The noise in the measured images was found to be = 1.2% (standard deviation) and theoretical predictions with a 1.96 noise level showed good agreement with the measured errors.

After validating the theoretical approach with measurements, the authors have shown that the use of the proximal side of the Bragg peak when performing dose ratio imaging is feasible, and allows for a wider dynamic range than when using the distal side. The dynamic range available increases as the demand on the accuracy of the WET decreases. The technique can only be applied to clinical sites with small maximum WETs such as for pediatric brains.


Full text loading...


Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd