An Anthropomorphic Head Phantom Prototype for the Measurement of Geometric Distortion in Magnetic Resonance Imaging System

Document Type : Original Paper


1 Physics and medical engineering Department, Medical Faculty, Tehran University of Medical Sciences, Tehran, Iran

2 Department of Medical Physics, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran


Introduction: Our goal is to design and construct a new anthropomorphic head phantom for assessment of image distortion in treatment planning systems.
Material and Methods: In this study, CT scan images of heads were transferred to the Mimic software. Using this software, the skull texture was removed and a hollow layer was formed between the bone tissues, in which the bone tissue would be equivalent to the material. Then it was fabricated with a 3D printer using K2HPO4 (as bone). A new phantom containing 8,000 reference features (control points) with AutoCAD software designed, fabricated it with a 3D printer and filled it with gels that included nickel-doped agarose, urea, and sodium chloride (as soft tissue) and then placed this grid inside the head phantom. This phantom was tested on the Siemens 3 Tesla Prisma MRI model using a 64-channel head coil. In this regard, a three-dimensional reference model was used. Reproducibility on the phantom was investigated with three different imaging sessions per day for three different days.
Results: T2 gel value, 84.804 ± 3ms was obtained for gel that simulates brain tissue. In addition, their corresponding T1 measurements were 1090.92 (ms), respectively. By Adding nickel to agarose gels, the amount of CT number in all energies of 80 to 130 kVp increased. Increasing the concentration of nickel in gels results in a decrease in CT number. The geometric distortion in the 3D results was found to be due to field non-uniformity and nonlinearity of the gradients and its reproducibility.
Conclusion: The results show that, the amount of distortion in the middle of the field was less than that of its sides. This phantom can be used to check image distortion in treatment planning systems.


Main Subjects

  1. Alexander E, Loeffler JS, Lunsford LD. Stereotactic radiosurgery. 1993.
  2. Schell MC, Bova FJ, Larson DA, Leavitt DD, Lutz WR, Podgorsak EB, et al. Stereotactic Radiosurgery: AAPM Report No 54. Radiation Therapy Committee Report of Task Group. 1995;42.
  3. Zhang B, MacFadden D, Damyanovich AZ, Rieker M, Stainsby J, Bernstein M, et al. Development of a geometrically accurate imaging protocol at 3 Tesla MRI for stereotactic radiosurgery treatment planning. Physics in Medicine & Biology. 2010 Oct 20;55(22):6601.
  4. Nutting C, Brada M, Brazil L, Sibtain A, Saran F, Westbury C, et al. Radiotherapy in the treatment of benign meningioma of the skull base. Journal of neurosurgery. 1999 May 1;90(5):823-7.
  5. Walton L, Hampshire A, Forster DM, Kemeny AA. A phantom study to assess the accuracy of stereotactic localization, using T1-weighted magnetic resonance imaging with the Leksell stereotactic system. Neurosurgery. 1996 Jan 1;38(1):170-8.
  6. Sumanaweera TS, Adler Jr JR, Napel S, Glover GH. Characterization of spatial distortion in magnetic resonance imaging and its implications for stereotactic surgery. Neurosurgery. 1994 Oct 1;35(4):696-704.
  7. Price RR, Axel L, Morgan T, Newman R, Perman W, Schneiders N, Selikson M, Wood M, et al. Quality assurance methods and phantoms for magnetic resonance imaging: report of AAPM nuclear magnetic resonance Task Group No. 1. Medical physics. 1990 Mar 1;17(2):287-95.
  8. Mack A, Wolff R, Scheib S, Rieker M, Weltz D, Mack G, et al. Analyzing 3-tesla magnetic resonance imaging units for implementation in radiosurgery. Journal of Neurosurgery. 2005 Jan 1;102(Special_Supplement):158-64.
  9. DICOM Library - Anonymize, Share, View DICOM files ONLINE [Internet]. Available from:
  10. Filippou V, Tsoumpas C. Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT, and ultrasound. Medical physics. 2018 Sep;45(9):e740-60.
  11. Shurche S, Yousefi Sooteh M. Fabrication of New 3D Phantom for the measurement of Geometric Distortion in Magnetic Resonance Imaging System. Iranian Journal of Medical Physics. 2019 Sep 1;16(5):377-84.
  12. Bryant JA, Drage NA, Richmond S. CT number definition. Radiation Physics and Chemistry. 2012 Apr 1;81(4):358-61.
  13. Thomas SJ. Relative electron density calibration of CT scanners for radiotherapy treatment planning. The British journal of radiology. 1999 Aug;72(860):781-6.
  14. Claude KP, Schandorf C, Amuasi JH, Tagoe SN. Fabrication of a tissue characterization phantom from indigenous materials for computed tomography electron density calibration: peer reviewed original article. South African Radiographer. 2013 May 1;51(1):9-17.
  15. Runge VM, Wood ML, Kaufman DM, Nelson KL, Traill MR. FLASH: clinical three-dimensional magnetic resonance imaging. Radiographics. 1988 Sep;8(5):947-65.
  16. Tofts PS, Du Boulay EP. Towards quantitative measurements of relaxation times and other parameters in the brain. Neuroradiology. 1990 Sep;32:407-15.
  17. Gonzalez RC. Digital image processing. Pearson education india; 2009.
  18. Briechle K, Hanebeck UD. Template matching using fast normalized cross correlation. InOptical Pattern Recognition XII. 2001 Mar 20; 4387: 95-102.
  19. Crow FC. Summed-area tables for texture mapping. InProceedings of the 11th annual conference on Computer graphics and interactive techniques. 1984 Jan 1; 207-12.
  20. SJ D. A complete distortion correction for MR images: I. Gradient warp correction. Phys Med Biol. 2005;50:2651-61.
  21. Vincent L. Morphological grayscale reconstruction in image analysis: applications and efficient algorithms. IEEE transactions on image processing. 1993 Apr;2(2):176-201.
  22. Chung J, Hulbert G. A time integration algorithm for structural dynamics with improved numerical dissipation: the generalized-α
  23. Mizowaki T, Nagata Y, Okajima K, Kokubo M, Negoro Y, Araki N, et al. Reproducibility of geometric distortion in magnetic resonance imaging based on phantom studies. Radiotherapy and Oncology. 2000 Nov 1;57(2):237-42.
  24. Barbosa NA, da Rosa LA, Batista DV, Carvalho AR. Development of a phantom for dose distribution verification in Stereotactic Radiosurgery. Physica Medica. 2013 Sep 1;29(5):461-9.
  25. Weygand J, Fuller CD, Ibbott GS, Mohamed AS, Ding Y, Yang J, et al. Spatial precision in magnetic resonance imaging–guided radiation therapy: the role of geometric distortion. International Journal of Radiation Oncology* Biology* Physics. 2016 Jul 15;95(4):1304-16.
  26. Shurche S. Measurement of Radio Frequency Non-Homogeneity in MRI. Measurement. 2018;12(4).
  27. Gallas RR, Hünemohr N, Runz A, Niebuhr NI, Jäkel O, Greilich S. An anthropomorphic multimodality (CT/MRI) head phantom prototype for end-to-end tests in ion radiotherapy. Zeitschrift fuer Medizinische Physik. 2015 Dec 1;25(4):391-9.
  28. Orth RC, Sinha P, Madsen EL, Frank G, Korosec FR, Mackie TR, et al. Development of a unique phantom to assess the geometric accuracy of magnetic resonance imaging for stereotactic localization. Neurosurgery. 1999 Dec 1;45(6):1423.