Simulation of computed tomography (CT) images using a Monte Carlo approach

• Autorzy: Wysocka-Rabin A. M. , Qamhiyeh S. , Jäkel O.
• Języki publikacji: EN

Abstrakty

EN

Heavy ion treatment planning uses an empirical scanner-dependent calibration relation between computed tomography (CT) numbers and ion range. Any deviation in the values of CT numbers will cause a drift in the calibration curve of the CT scanner, which can reduce the accuracy of treatment beam delivery. To reduce uncertainty in the empirical estimation of CT numbers, we developed a simulation that takes into consideration the geometry, composition, and physical process that underlie their measurement. This approach uses Monte Carlo (MC) simulations, followed by a simple filtered back-projection reconstruction. The MC code used is BEAMnrc/EGSnrc. With the manufacturer’s permission, we simulated the components (X-ray tube, associated filters and beam shapers) of a Siemens Emotion CT. We then generated an initial beam shape and spectra, and performed further simulations using the phantom with substitutes. We analyzed the resulting phase space file to calculate projections, taking into account the energy response of the CT detectors. Then, we applied a simple reconstruction algorithm to the calculated projections in order to receive the CT image.

Słowa kluczowe

EN

X-ray tomography; Monte Carlo (MC) method; treatment planning; hadrontherapy

• Wydawca: Institute of Nuclear Chemistry and Technology
• Czasopismo: Nukleonika
• Rocznik: 2011
• Tom: Vol. 56, No. 4
• Strony: 299--304
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Wysocka-Rabin A. M.

autor

Qamhiyeh S.

autor

Jäkel O.

• Department of Accelerator Physics, The Andrzej Sołtan Institute for Nuclear Studies, 05-400 Otwock/Świerk, Poland, Tel.: [phone], Fax: [phone]

Bibliografia

• 1. Das IJ, Chapman J, Verhaegen F, Zellmer D (1999) Interface dosimetry in kilovoltage photon beams. In: Ma C-M, Seuntjens J (eds) Kilovoltage X-ray beam dosimetry for radiotherapy and radiobiology. Medical Physics Publishing, Madison, WI, pp 239–259
• 2. Heismann BJ, Leppert J, Stierstorfer K (2003) Density and atomic number measurements with spectral X-ray attenuation method. J Appl Phys 94;3:2073–2079
• 3. Jäkel O, Jacob C, Schardt D, Karger CP, Hartmann GH (2001) Relation between carbon ion ranges and X-ray CT numbers. Med Phys 28;4:701–703
• 4. Kalender WA (2000) Computed tomography: fundamentals, system technology, image quality, applications. John Wiley & Sons, New York
• 5. Kawrakow I, Rogers DWO (2001) The EGSnrc code system: Monte Carlo simulation of electron and photon transport. Report no. PIRS-701. National Research Council of Canada, Ottawa
• 6. Marianno CM, Higley KA, Palmer TS (2000) A comparison between default EGS4 and EGS4 with bound Compton cross-sections when scattering occurs in bone and fat. Health Phys 78;6:716–720
• 7. Qamhiyeh S, Wysocka-Rabin A, Ellerbrock M, Jäkel O (2007) Effect of voltage of CT scanner, phantom size and phantom material on CT calibration and carbon range. Radiother Oncol 84;S1:S232
• 8. Romanchikova M (2006) Monte Carlo Simulation des Röntgenspektrumseiner computertomographischen Röntgenröhre. Master’s thesis, University of Heidelberg, Germany
• 9. Sennst A, Kachelriess M, Leidercker C, Schmidt B, Watzke O, Kalender WA (2004) An extensible software-based platform for reconstruction and evaluation of CT images. Radiographics 24;2:601–613
• 10. Verhaegen F (2002) Evaluation of the EGSnrc Monte Carlo code for interface dosimetry near high-Z media exposed to kilovolt and 60Co photons. Phys Med Biol 47:1691–1705