Impact of bowtie filter and detector collimation on multislice CT scatter profiles: A simulation study.

Geant4 Monte Carlo hybrid simulation method multislice CT scatter radiation scatter to primary ratio

Journal

Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 21 11 2019
revised: 30 09 2020
accepted: 13 11 2020
pubmed: 10 12 2020
medline: 15 5 2021
entrez: 9 12 2020
Statut: ppublish

Résumé

To investigate via Monte Carlo simulations, the impact of scan subject size, antiscatter grid (ASG), collimator size, and bowtie filter on the distribution of scatter radiation in a typical realistically modeled third generation 16 slice diagnostic computed tomography (CT) scanner. Full radiation transport was simulated with Geant4 in a realistic CT scanner geometric model, including the imaging phantom, bowtie filter (BTF), collimators and detector assembly, except for the ASGs. An analytical method was employed to quantify the probable transmission through the ASG of each photon intersecting the detector array. Normalized scatter profiles (NSP) and scatter-to-primary-ratio (SPR) profiles were simulated for 90 and 140 kVp beams for different size phantoms and slice thicknesses. The impact of CT scatter on the reconstructed attenuation coefficient factor was also studied as were the modulating effects of phantom- and patient-tissue heterogeneities on scatter profiles. A method to characterize the relative spatial frequency content of sinogram signals was developed to assess the latter. For the 21.4-cm diameter phantom, NSP and SPR increase linearly with collimator opening for both tube potentials, with the 90 kVp scan exhibiting slightly larger NSP and SPR. The BTF modestly modulates scatter under the phantom center, reducing the prominent off-axis lobes by factors of 1.1-1.3. The ASG reduces scatter on the central axis NSP threefold, and reduces scatter at the detectors outside the phantom shadow by factors of 25 to 500. For the phantoms with diameters of 27 and 32 cm, the scatter increases roughly three- and fourfold, respectively, demonstrating that scatter monotonically increases with phantom size, despite deployment of the ASG and BTF. In the absence of a scan subject, the ASG reduces the signal profile arising photons scattered by the BTF. Without ASG, the in-air scatter profile is relatively flat compared to the scatter profile when the ASG is present. For both 90 and 140 kVp photon spectra, the calculated attenuation coefficient decreases linearly with increasing collimation size. For both homogeneous and heterogeneous objects, NSPs are dominated by low spatial frequency content compared to the primary signal. However, the SPR, which quantifies the local magnitude of nonlinear detector response and is dominated by the high frequency content of the primary profile, can contribute strongly to high-spatial frequency streaking artifacts near high-density structures in reconstructed image artifacts. Public-domain Monte Carlo codes, Geant-4 in particular, is a feasible method for characterizing CT detector response to scattered- and off-focal radiation. Our study demonstrates that the ASG substantially reduces the scatter radiation and reshapes scatter-radiation profiles and affects the accuracy with which the detector array can measure narrow-beam attenuation due its inability to distinguish between true uncollided primary and narrow-angle coherently scattered photons. Hence, incorporating the impact of detector array collimation into the forward-projection signal formation models used by iterative reconstruction algorithms is necessary to use CT for accurately characterizing material properties. While tissue heterogeneities exercise a modest influence on local NPS shape and magnitude, they do not add significant high spatial frequency content.

Identifiants

pubmed: 33296513
doi: 10.1002/mp.14652
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

852-870

Subventions

Organisme : NIH HHS
ID : RO1 CA 212638
Pays : United States

Informations de copyright

© 2020 American Association of Physicists in Medicine.

Références

Hsieh J. Computed Tomography, Second Edition. In: Computed Tomography, Second Edition, SPIE; 2009:207-299.
Nuyts J, De Man B, Fessler JA, Zbijewski W, Beekman FJ. Modelling the physics in the iterative reconstruction for transmission computed tomography. Phys Med Biol. 2013;58:R63-R96.
Evans JD, Whiting BR, O'Sullivan JA, et al. Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual-energy CT imaging on a commercial scanner: comparison of analytic and polyenergetic statistical reconstruction algorithms. Med Phys. 2013;40:121914.
Zhang S, Han D, Politte DG, Williamson JF, O’Sullivan JA. Impact of joint statistical dual-energy CT reconstruction of proton stopping power images: comparison to image- and sinogram-domain material decomposition approaches. Med Phys. 2018;45:2129-2142.
Williamson JF, Whiting BR, Benac J, et al. Prospects for quantitative computed tomography imaging in the presence of foreign metal bodies using statistical image reconstruction. Med Phys. 2002;29:2404-2418.
Joseph PM, Spital RD. The effects of scatter in x-ray computed tomography. Med Phys. 1982;9:464-472.
Liu X, Hsieh J. Hybrid deterministic-stochastic modeling of x-ray beam bowtie filter scatter on a CT system. J Xray Sci Technol. 2015;23:593-600.
Lazos D, Williamson JF. Monte Carlo evaluation of scatter mitigation strategies in cone-beam CT. Med Phys. 2010;37:5456-5470.
Boone JM. Method for evaluating bow tie filter angle-dependent attenuation in CT: theory and simulation results. Med Phys. 2009;37:40-48.
Bernstein H, Muntz EP, Schreckendgust J, Klein DJ, Lee K. A detailed experimental and theoretical comparison of the angular and energy dependencies of grid transmission. Med Phys. 1983;10:218-223.
Sisniega A, Zbijewski W, Badal A, et al. Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions. Med. Phys. 2013;40:1-19.
Cherry EM, Fahrig R. Comparison of CT scatter rejection effectiveness using antiscatter grids and energy-discriminating detectors. SPIE Med Imaging. 2015;9412:94123Y.
Chan HP, Doi K. Investigation of the performance of antiscatter grids: Monte Carlo simulation studies. Phys Med Biol. 1982;27:785-803.
Dance DR, Day GJ. The computation of scatter in mammography by Monte Carlo methods. Phys Med Biol. 1984;29:237-247.
Vogtmeier G, Dorscheid R, Juergen Engel K, et al. Two-dimensional anti-scatter grids for computed tomography detectors. In: Proceedings Volume 6913, Medical Imaging 2008: Physics of Medical Imaging; 691359 (2008); 2008. https://doi.org/10.1117/12.770063
Day GJ, Dance DR. X-ray transmission formula for antiscatter grids. Phys Med Biol. 1983;28:1429-1433.
Zhou A, White GL, Davidson R. Validation of a Monte Carlo code system for grid evaluation with interference effect on Rayleigh scattering. Phys Med Biol. 2018;63:03NT02.
Zhao W, Brunner S, Niu K, Schafer S, Royalty K, Chen G-H. A patient-specific scatter artifacts correction method; 2015. https://doi.org/10.1117/12.2043923
Liu X, Shaw CC, Wang T, Chen L, Altunbas MC, Kappadath SC. An accurate scatter measurement and correction technique for cone beam breast CT imaging using scanning sampled measurement (SSM) technique. Proc Soc Photo Opt Instrum Eng. 2006;6142:6142341-6142347.
Rinkel J, Gerfault L, Estève F, Dinten JM. A new method for x-ray scatter correction: first assessment on a cone-beam CT experimental setup. PhysMed Biol. 2007;52:4633-4652.
Siewerdsen JH, Jaffray DA. Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. Med Phys. 2001;28:220-231.
Johns PC, Yaffe M. Scattered radiation in fan beam imaging systems. Med Phys. 1982;9:231-239.
Busi M, Olsen UL, Knudsen EB, et al. A Monte Carlo simulation of scattering reduction in spectral x-ray computed tomography. Adv. Comput. Methods X-Ray Opt. IV; 2017: 25. https://doi.org/10.1117/12.2273763
Akbarzadeh A, Ay MR, Ghadiri H, Sarkar S, Zaidi H. A novel approach for experimental measurement of scatter profile and scatter to primary ratio in 64-slice CT scanner. In: 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Berlin, Heidelberg: Springer, Berlin Heidelberg; 2008, pp. 473-477.
Leliveld CJ, Maas JG, Van Eijk CW, Bom VR. On the significance of scattered radiation in industrial x-ray computerized tomographic imaging. IEEE Trans. Nucl. Sci. 1994;41:290-294.
Kalender W. Monte Carlo calculations of X-ray scatter data for diagnostic radiology. Phys Med Biol. 1981;26:835-849.
Persliden J, Alm Carlsson G. Scatter rejection by air gaps in diagnostic radiology. Calculations using a Monte Carlo collision density method and consideration of molecular interference in coherent scattering. Phys Med Biol. 1997;42:155-175.
Kyriakou Y, Kalender W. Efficiency of antiscatter grids for flat-detector CT. Phys Med Biol. 2007;52:6275-6293.
Kyriakou Y, Meyer M, Kalender WA. Technical note: comparing coherent and incoherent scatter effects for cone-beam CT. Phys Med Biol. 2008;53:174-185.
Williamson JF. Monte Carlo simulation of photon transport phenomena. In: Morin RL, ed. Monte Carlo Simulation in the Radiological Sciences. Boca Raton: CRC Press; 1988:53-102.
Jarry G, Graham SA, Moseley DJ, Jaffray DJ, Siewerdsen JH, Verhaegen F. Characterization of scattered radiation in kV CBCT images using Monte Carlo simulations. Med Phys. 2006;33:4320-4329.
Najafi Darmian A, Ay MR, Pouldian M, et al. Characterization of scattered radiation profile in volumetric 64 slice CT scanner: Monte Carlo study using GATE. In: IEEE Nuclear Science Symposium Conference Record; 2012:2692-2696. https://doi.org/10.1109/NSSMIC.2011.6152951
Chen YCY, Liu B, O’Connor M, Didier CS, Glick SJ. Comparison of Scatter/Primary Measurements with GATE Simulations for X-Ray Spectra in Cone Beam CT Mammography. In: 2006 IEEE Nucl. Sci. Symp. Conf. Rec; 2006;6:3909-3914. https://doi.org/10.1109/NSSMIC.2006.353843
Wadeson N, Morton E, Lionheart W. Scatter in an uncollimated x-ray CT machine based on a Geant4 Monte Carlo simulation. In: Medical Imaging 2010: Physics of Medical Imaging; 2010;7622:76223E. https://doi.org/10.1117/12.843981
Ning R, Tang X, Conover D. X-ray scatter correction algorithm for cone beam CT imaging. Med Phys. 2004;31:1195-1202.
Endo M, Tsunoo T, Nakamori N, Yoshida K. Effect of scattered radiation on image noise in cone beam CT. Med Phys. 2001;28:469-474.
Barnes GT, Cleare HM, Brezovich IA. Reduction of scatter in diagnostic radiology by means of a scanning multiple slit assembly. Radiology. 1976;120:691-694.
Neitzel U. Grids or air gaps for scatter reduction in digital radiography: a model calculation. Med Phys. 1992;19:475-481.
Engel KJ, Bäumer C, Wiegert J, Zeitler G. Spectral analysis of scattered radiation in CT. In: Medical Imaging 2008: Physics of Medical Imaging; 2008;6913:69131R. https://doi.org/10.1117/12.771063
Zimmerman K, Cai L, Lai X, Kaul M, Thompson R, Zhan X. Simulation of scattered radiation with various anti-scatter grid designs in a photon counting CT. In: Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109484Q (1 March 2019); 2019. https://doi.org/10.1117/12.2512494
Engel KJ, Herrmann C, Zeitler G. X-ray scattering in single- and dual-source CT. Med Phys. 2008;35:318-332.
Prakash P, Boudry JM. Comparative study of bowtie and patient scatter in diagnostic CT. In: Medical Imaging 2017: Physics of Medical Imaging, Mar. 2017, vol. 10132, p. 101322G. https://doi.org/10.1117/12.2253012
Zhang S, Han D, Williamson JF, et al. Experimental implementation of a joint statistical image reconstruction method for proton stopping power mapping from dual-energy CT data. Med Phys. 2019;46:273-285.
Platten D, Keat N, Lewis M, Edyvean S. Wide bore CT scanner comparison report version 14. Report 06014, Mar-06”, London; 2006. http://www.impactscan.org/reports/Report06014.htm.
Shefer E, Altman A, Behling R, et al. State of the art of CT detectors and sources: a literature review. Curr Radiol Rep. 2013;1:76-91.
Birch R, Marshall M. Computation of bremsstrahlung X-ray spectra and comparison with spectra measured with a Ge(Li) detector. Phys Med Biol. 1979;24:505-517.
Agostinelli S, Allison J, Amako K, et al. GEANT4 - a simulation toolkit. Nucl Instrum Methods Phys Res Sect A. 2003;506:250-303.
Maigne L, Perrot Y, Schaart DR, Donnarieix D, Breton V. Comparison of GATE/GEANT4 with EGSnrc and MCNP for electron dose calculations at energies between 15 keV and 20 MeV. Phys Med Biol. 2011;56:811-827.
Collaboration G. Physics Reference Manual. Release 10.5; 2019. http://geant4-userdoc.web.cern.ch/geant4-userdoc/UsersGuides/PhysicsReferenceManual/fo/PhysicsReferenceManual.pdf (accessed Jun. 24, 2019).
Berger M, Hubbell JH, Seltzer SM, et al. XCOM: Photon Cross Section Database (NIST Standard Reference Database 8 (XGAM)), Gaithersburg, MD; 2010. https://doi.org/10.18434/T48G6X
Cullen D, Hubbell JH, Kissel L. EPDL97: the Evaluated Photon Data Library, UCRL-50400 and, Vol. 6 and Rev.5, vol. 6, pp. 1-35; 1997.
Allison J, Amako K, Apostolakis J, et al. Recent developments in GEANT4. Nucl Instrum Methods Phys Res Sect A Accel Spectrom Detect Assoc Equip. 2016;835:186-225.
Hubbell JH, Veigele WJ, Briggs EA, Brown RT, Cromer DT, Howerton RJ. Atomic form factors, incoherent scattering functions, and photon scattering cross sections. J Phys Chem Ref Data. 1975;4:471-538.
Hubbell JH, Overbo I. Relativistic atomic form factors and photon coherent scattering cross sections. J Phys Chem Ref Data. 1979;8:69-106.
Poludniowski G, Evans PM, Webb S. Rayleigh scatter in kilovoltage x-ray imaging: is the independent atom approximation good enough? Phys Med Biol. 2009;54:6931-6942.
Shuyan X. Application of Monte Carlo Method in Experimental Nuclear Physics. Beijing: Atomic Energy Press; 2006.
Colijn AP, Beekman FJ. Accelerated simulation of cone beam X-Ray scatter projections. IEEE Trans Med Imaging. 2004;23:584-590.
Richardson WH. Bayesian-based iterative method of image restoration*. J Opt Soc Am. 1972;62:55.
Lucy LB. An iterative technique for the rectification of observed distributions. Astron J. 1974;79:745.
Geant4 Collaboration. Geant4 User’s Guide for Application Developers; 2016.
Afsharpour H, Landry G, D’Amours M, et al. ALGEBRA: algorithm for the heterogeneous dosimetry based on GEANT4 for BRAchytherapy. Phys Med Biol. 2012;57:3273-3280.
Zhu L, Benett NR, Fahrig R. Scatter correction method for x-ray CT using primary modulation: theory and preliminary. IEEE Trans Med Imaging. 2006;37:934-946.
Zhu L. Local filtration based scatter correction for cone-beam CT using primary modulation. Med. Phys. 2016;43:6199-6209.
Bootsma GK, Verhaegen F, Jaffray DA. Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections. Med Phys. 2013;40:111901.
Schörne K; and P. (Prof. D. Böni, “Development of Methods for Scatter Artifact Correction in Industrial X-ray Cone-beam Computed Tomography”, Fak. für Phys., p. 145; 2012.
Gao H, Fahrig R, Bennett NR, Sun M, Star-Lack J, Zhu L. Scatter correction method for x-ray CT using primary modulation: phantom studies. Med Phys. 2010;37:934-946.
Gray JE, Capp MP, Whitehead FR. An improved technique for X-ray image evaluation: the two dimensional modulation transfer function. Invest Radiol. 1974;9:252-261.
Zhu L, Xie Y, Wang J, Xing L. Scatter correction for cone-beam CT in radiation therapy. Med Phys. 2009;36:2258-2268.
Williamson JF. Monte Carlo evaluation of kerma at a point for photon transport problems. Med Phys. 1987;14:567-576.
Chen Y, Liu B, O’Connor JM, Didier CS, Glick SJ. Characterization of scatter in cone-beam CT breast imaging: comparison of experimental measurements and Monte Carlo simulation. Med Phys. 2009;36:857-869.
Gutierrez D, Zaidi H. Assessment of x-ray scatter for the micro-CT subsystem of the FLEX Triumph preclinical PET-CT scanner. IEEE Nucl Sci Symp Conf Rec. 2010;38:2216-2223. https://doi.org/10.1109/NSSMIC.2010.5874177.
Malušek A, Sandborg MP, Carlsson GA. Simulation of scatter in cone beam CT: effects on projection image quality. In: Proc. SPIE Med. Imaging 2003 Phys. Med. Imaging, vol. 5030, no. June 2003, pp. 740-751. https://doi.org/10.1117/12.479940
Midgley S. Angular width of a narrow beam for X-ray linear attenuation coefficient measurements. Radiat Phys Chem. 2006;75:945-953.
Paternò G, Cardarelli P, Contillo A, Gambaccini M, Taibi A. Geant4 implementation of inter-atomic interference effect in small-angle coherent X-ray scattering for materials of medical interest. Phys Medica. 2018;51:64-70.
Chantler CT. Detailed tabulation of atomic form factors, photoelectric absorption and scattering cross section, and mass attenuation coefficients for Z = 1-92 from E = 1-10 eV to E = 0.4-1.0 MeV. J Phys Chem Ref Data. 2000;29:597-1048.
Omer M, Hajima R. JAEA-Data/Code 2018-007 Geant4 Physics Process for Elastic Scattering of γ-Rays Integrated Support Center for Nuclear Nonproliferation and Nuclear Security; 2018. https://doi.org/10.11484/jaea-data-code-2018-007
Whiting B, Williamson J, Liu R, Webb T, Porras-Chaverri M, O’Sullivan J. Dependence of scatter-to-primary ratio on x-ray energy. In: AAPM Annual Meeting; 2019:E504.
Niu T, Zhu L. Scatter correction for full-fan volumetric CT using a stationary beam blocker in a single full scan. Med Phys. 2011;38:6027-6038.

Auteurs

Ruirui Liu (R)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63110, USA.

Shuangyue Zhang (S)

Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA.

Tianyu Zhao (T)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63110, USA.

Joseph A O'Sullivan (JA)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63110, USA.

Jeffrey F Williamson (JF)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63110, USA.

Tyler Webb (T)

Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA.

Mariela Porras-Chaverri (M)

Atomic, Nuclear and Molecular Sciences Research Center (CICANUM), University of Costa Rica, San José, Coast Rica.

Bruce Whiting (B)

Radiology Department, University of Pittsburgh, Pittsburgh, PA, USA.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH