Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Quantitative analysis of fetal magnetic resonance phantoms and recommendations for an anthropomorphic motion phantom



To provide a review and quantitative analysis of the available fetal MR imaging phantoms.

Materials and methods

A literature search was conducted across Pubmed, Google Scholar, and Ryerson University Library databases to identify fetal MR imaging phantoms. Phantoms were graded on a semi-quantitative scale in regards to four evaluation categories: (1) anatomical accuracy in size and shape, (2) dielectric conductivity similar to the simulated tissue, (3) relaxation times similar to simulated tissue, and (4) physiological motion similar to fetal gross body, cardiovascular, and breathing motion. This was followed by statistical analysis to identify significant findings.


Seventeen fetal phantoms were identified and had an average overall percentage accuracy of 26%, with anatomical accuracy being satisfied the most (56%) and physiological motion the least (7%). Phantoms constructed using 3D printing were significantly more accurate than conventionally constructed phantoms.


Currently available fetal phantoms lack accuracy and motion simulation. 3D printing may lead to higher accuracy compared with traditional manufacturing. Future research needs to focus on properly simulating both fetal anatomy and physiological motion to produce a phantom that is appropriate for fetal MRI sequence development and optimization.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11


  1. 1.

    Bulas D, Egloff A (2013) Benefits and risks of MRI in pregnancy. Semin Perinatol 37:301–304

  2. 2.

    Pugash D, Brugger PC, Bettelheim D, Prayer D (2008) Prenatal ultrasound and fetal MRI: the comparative value of each modality in prenatal diagnosis. Eur J Radiol 68:214–226

  3. 3.

    Biegon A (2014) Quantitative magnetic resonance imaging of the fetal brain in utero: methods and applications. World J Radiol 6:523–529

  4. 4.

    Gholipour A, Estroff JA, Warfield SK (2010) Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans Med Imaging 29:1739–1758

  5. 5.

    Gholipour A, Estroff JA, Barnewolt CE, Robertson RL, Grant PE, Gagoski B, Warfield SK, Afacan O, Connolly SA, Neil JJ, Wolfberg A, Mulkern RV (2014) Fetal MRI: a technical update with educational aspirations. Concepts Magn Reson Part A 43A:237–266

  6. 6.

    Jansz MS, Seed M, van Amerom JFP, Wong D, Grosse-Wortmann L, Yoo S-J, Macgowan CK (2010) Metric optimized gating for fetal cardiac MRI. Magn Reson Med 64:1304–1314

  7. 7.

    Kording F, Schoennagel BP, de Sousa MT, Fehrs K, Adam G, Yamamura J, Ruprecht C (2018) Evaluation of a portable doppler ultrasound gating device for fetal cardiac MR imaging: initial results at 1.5T and 3T. Magn Reson Med Sci 17:308–317

  8. 8.

    García-Polo P, Gagoski B, Guerin B, Gale E, Adalsteinsson E, Grant PE, Wald LL (2015) An anthropomorphic MR phantom of the gravid abdomen including the uterus, placenta, fetus and fetal brain. In: ISMRM Annual Meeting, Abstract #1545

  9. 9.

    Serag A, Macnaught G, Denison FC, Reynolds RM, Semple SI, Boardman JP (2017) Histograms of oriented 3D gradients for fully automated fetal brain localization and robust motion correction in 3 T magnetic resonance images. Biomed Res Int 2017:1–8

  10. 10.

    van Amerom JFP, Lloyd DFA, Price AN, Kuklisova Murgasova M, Aljabar P, Malik SJ, Lohezic M, Rutherford MA, Pushparajah K, Razavi R, Hajnal JV (2018) Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection: fetal cardiac cine imaging using dynamic MRI. Magn Reson Med 79:327–338

  11. 11.

    Keraudren K, Kuklisova-Murgasova M, Kyriakopoulou V, Malamateniou C, Rutherford MA, Kainz B, Hajnal JV, Rueckert D (2014) Automated fetal brain segmentation from 2D MRI slices for motion correction. NeuroImage 101:633–643

  12. 12.

    Swailes NE, MacDonald ME, Frayne R (2011) Dynamic phantom with heart, lung, and blood motion for initial validation of MRI techniques. J Magn Reson Imaging 34:941–946

  13. 13.

    Filippou V, Tsoumpas C (2018) Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT, and ultrasound. Med Phys 45:e740–e760

  14. 14.

    Cheung CL, Looi T, Drake J, Kim PCW (2012) Magnetic resonance imaging properties of multimodality anthropomorphic silicone rubber phantoms for validating surgical robots and image guided therapy systems. In: Holmes DR III, Wong KH (eds) Medical Imaging 2012: image-guided procedures, robotic interventions, and modeling. San Diego, USA

  15. 15.

    Patel M (2013) Design and development of a MRI and US compatible heart phantom. Master’s Thesis, Hamburg University of Applied Sciences and University Medical Center Hamburg-Eppendorf

  16. 16.

    Antoni S-T, Lehmann S, Neidhardt M, Fehrs K, Ruprecht C, Kording F, Adam G, Schupp S, Schlaefer A (2018) Model checking for trigger loss detection during Doppler ultrasound-guided fetal cardiovascular MRI. Int J Comput Assist Radiol Surg 13:1755–1766

  17. 17.

    Hutter J, Christiaens DJ, Schneider T, Cordero-Grande L, Slator PJ, Deprez M, Price AN, Tournier J-D, Rutherford M, Hajnal JV (2018) Slice-level diffusion encoding for motion and distortion correction. Med Image Anal 48:214–229

  18. 18.

    Goolaub DS, Roy CW, Schrauben E, Sussman D, Marini D, Seed M, Macgowan CK (2018) Multidimensional fetal flow imaging with cardiovascular magnetic resonance: a feasibility study. J Cardiovasc Magn Reson 20:77

  19. 19.

    Malamateniou C, Malik SJ, Counsell SJ, Allsop JM, McGuinness AK, Hayat T, Broadhouse K, Nunes RG, Ederies AM, Hajnal JV, Rutherford MA (2013) Motion-compensation techniques in neonatal and fetal MR imaging. Am J Neuroradiol 34:1124–1136

  20. 20.

    Valenti O, Di Prima FAF, Renda E, Faraci M, Hyseni E, De Domenico R, Monte S, Giorgio E (2011) Fetal cardiac function during the first trimester of pregnancy. J Prenat Med 5:59–62

  21. 21.

    Snijders RJM, McLaren R, Nicolaides KH (1990) Computer-assisted analysis of fetal heart rate patterns at 20–41 weeks’ gestation. Fetal Diagn Ther 5:79–83

  22. 22.

    Roberts AB, Little D, Cooper D, Campbell S (1979) Normal patterns of fetal activity in the third trimester. BJOG Int J Obstet Gynaecol 86:4–9

  23. 23.

    Cosmi EV, Anceschi MM, Cosmi E, Piazze JJ, La Torre R (2003) Ultrasonographic patterns of fetal breathing movements in normal pregnancy. Int J Gynecol Obstet 80:285–290

  24. 24.

    Natale R, Nasello-Paterson C, Connors G (1988) Patterns of fetal breathing activity in the human fetus at 24 to 28 weeks of gestation. Am J Obstet Gynecol 158:317–321

  25. 25.

    Ruano R, Joubin L, Aubry M-C, Thalabard J-C, Dommergues M, Dumez Y, Benachi A (2006) A nomogram of fetal lung volumes estimated by 3-dimensional ultrasonography using the rotational technique (virtual organ computer-aided analysis). J Ultrasound Med 25:701–709

  26. 26.

    Govindan RB, Vairavan S, Ulusar UD, Wilson JD, Mckelvey SS, Preissl H, Eswaran H (2011) A novel approach to track fetal movement using multi-sensor magnetocardiographic recordings. Ann Biomed Eng 39:964–972

  27. 27.

    Kuwata T, Matsubara S, Ohkusa T, Ohkuchi A, Izumi A, Watanabe T, Suzuki M (2008) Establishing a reference value for the frequency of fetal movements using modified ‘count to 10’ method: reference value for fetal movement. J Obstet Gynaecol Res 34:318–323

  28. 28.

    Kuwata T, Matsubara S, Ohkusa T, Yada Y, Suzuki M (2011) Decreased fetal movement prompts investigation of prenatal/neonatal nemaline myopathy: the possible merit of fetal movement count: fetal movement in fetal myopathy. J Obstet Gynaecol Res 37:921–925

  29. 29.

    Hayat TTA, Nihat A, Martinez-Biarge M, McGuinness A, Allsop JM, Hajnal JV, Rutherford MA (2011) Optimization and initial experience of a multisection balanced steady-state free precession cine sequence for the assessment of fetal behavior in utero. Am J Neuroradiol 32:331–338

  30. 30.

    Huang SY, Seethamraju RT, Patel P, Hahn PF, Kirsch JE, Guimaraes AR (2015) Body MR imaging: artifacts, k-Space, and solutions. Radiographics 35:1439–1460

  31. 31.

    Xin SX, Gu S, Carluccio G, Collins CM (2015) Consideration of the effects of intense tissue heating on the RF electromagnetic fields during MRI: simulations for MRgFUS in the hip. Phys Med Biol 60:301–307

  32. 32.

    Bernstein MA, Huston J, Ward HA (2006) Imaging artifacts at 3.0T. J Magn Reson Imaging 24:735–746

  33. 33.

    American College of Obstetricians and Gynecologists (2017) Methods for estimating the due date. committee Opinion No. 700. Obstet Gynecol 129:e150–e154

  34. 34.

    Carpenter J, Bithell J (2000) Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians. Stat Med 19:1141–1164

  35. 35.

    Victoria T, Jaramillo D, Roberts TPL, Zarnow D, Johnson AM, Delgado J, Rubesova E, Vossough A (2014) Fetal magnetic resonance imaging: jumping from 1.5 to 3 tesla (preliminary experience). Pediatr Radiol 44:376–386

  36. 36.

    Spatz MH (2017) A 64 channel 3T array coil for highly accelerated fetal imaging at 22 weeks of pregnancy. Master’s Thesis, Massachusetts Institute of Technology

  37. 37.

    Chen Q, Xie G, Luo C, Yang X, Zhu J, Lee J, Su S, Liang D, Zhang X, Liu X, Li Y, Zheng H (2018) A dedicated 36-channel receive array for fetal MRI at 3 T. IEEE Trans Med Imaging 37:2290–2297

  38. 38.

    Stark DD, McCarthy SM, Filly RA, Parer JT, Hricak H, Callen PW (1985) Pelvimetry by magnetic resonance imaging. Am J Roentgenol 144:947–950

  39. 39.

    Ferrazzi G (2016) An exploration of methods for performing resting state fMRI in the human fetus. PhD Thesis, King’s College London

  40. 40.

    Büsing KA, Kilian AK, Schaible T, Debus A, Weiss C, Neff KW (2008) Reliability and validity of MR image lung volume measurement in fetuses with congenital diaphragmatic hernia and in vitro lung models. Radiol 246:553–561

  41. 41.

    Kehl S, Zirulnik A, Debus A, Sütterlin M, Siemer J, Neff W (2011) In vitro models of the fetal lung: comparison of lung volume measurements with 3-dimensional sonography and magnetic resonance imaging. J Ultrasound Med 30:1085–1091

  42. 42.

    Victoria T, Johnson AM, Adzick NS, Hedrick HL, Shellock FG (2018) Evaluation of magnetic resonance imaging safety and imaging issues associated with the occlusion balloon used during fetoscopic endoluminal tracheal occlusion. Fetal Diagn Ther 44:179–183

  43. 43.

    Portnoy S (2018) Fetal Magnetic Resonance Oximetry. PhD Thesis, University of Toronto

  44. 44.

    Bidhult S, Töger J, Heiberg E, Carlsson M, Arheden H, Aletras AH, Hedström E (2019) Independent validation of metric optimized gating for fetal cardiovascular phase-contrast flow imaging. Magn Reson Med 81:495–503

  45. 45.

    Armstrong T, Liu D, Martin T, Masamed R, Janzen C, Wong C, Chanlaw T, Devaskar SU, Sung K, Wu HH (2019) 3D R2* mapping of the placenta during early gestation using free-breathing multiecho stack-of-radial MRI at 3T: free-Breathing Radial Placental R2* Mapping. J Magn Reson Imaging 49:291–303

  46. 46.

    Wargo CJ, Moore J, Gore JC (2013) A comparison and evaluation of reduced-FOV methods for multi-slice 7T human imaging. Magn Reson Imaging 31:1349–1359

  47. 47.

    He X, Frey EC, Links JM, Gilland KL, Segars WP, Tsui BMW (2004) A mathematical observer study for the evaluation and optimization of compensation methods for myocardial SPECT using a phantom population that realistically models patient variability. IEEE Trans Nucl Sci 51:218–224

  48. 48.

    Gagoski B, Ye H, Cauley S, Bhat H, Setsompop K, Chatnuntawech I, Martin A, Jiang Y, Griswold M, Adalsteinsson E, Grant PE, Wald L (2015) Magnetic resonance fingerprinting for fetal imaging at 3T—initial results. In: ISMRM Annual Meeting, Abstract #3429

  49. 49.

    Tavallaei MA, Johnson PM, Liu J, Drangova M (2015) Design and evaluation of an MRI-compatible linear motion stage. Med Phys 43:62–71

  50. 50.

    Freed M, de Zwart JA, Loud JT, El Khouli RH, Myers KJ, Greene MH, Duyn JH, Badano A (2011) An anthropomorphic phantom for quantitative evaluation of breast MRI: a phantom for quantitative evaluation of breast MRI. Med Phys 38:743–753

  51. 51.

    Wang K, Ho C-C, Zhang C, Wang B (2017) A review on the 3D printing of functional structures for medical phantoms and regenerated tissue and organ applications. Eng 3:653–662

  52. 52.

    Mitsouras D, Lee TC, Liacouras P, Ionita CN, Pietilla T, Maier SE, Mulkern RV (2017) Three-dimensional printing of MRI-visible phantoms and MR image-guided therapy simulation: 3D Printing of MRI-Visible Phantoms. Magn Reson Med 77:613–622

  53. 53.

    Wang K, Wu C, Qian Z, Zhang C, Wang B, Vannan MA (2016) Dual-material 3D printed metamaterials with tunable mechanical properties for patient-specific tissue-mimicking phantoms. Addit Manuf 12:31–37

  54. 54.

    Wang K, Zhao Y, Chang Y-H, Qian Z, Zhang C, Wang B, Vannan MA, Wang M-J (2016) Controlling the mechanical behavior of dual-material 3D printed meta-materials for patient-specific tissue-mimicking phantoms. Mater Des 90:704–712

  55. 55.

    In E, Walker E, Naguib HE (2017) Novel development of 3D printable UV-curable silicone for multimodal imaging phantom. Bioprinting 7:19–26

  56. 56.

    Feldt-Rasmussen U, Mathiesen ER (2011) Endocrine disorders in pregnancy: physiological and hormonal aspects of pregnancy. Best Pract Res Clin Endocrinol Metab 25:875–884

  57. 57.

    Song K-H, Kim S-Y, Lee D-W, Jung J-Y, Lee J-H, Baek H-M, Choe B-Y (2015) Design of a fused phantom for quantitative evaluation of brain metabolites and enhanced quality assurance testing for magnetic resonance imaging and spectroscopy. J Neurosci Methods 255:75–84

Download references


The authors thank Brahmdeep Saini, Dr. Birgit Ertl-Wagner, and Dr. Michael Kolios for providing feedback on the manuscript. This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) [funding reference number RGPIN-2018-04155]. NSERC had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit this article for publication.

Author information

Study conception and design, analysis and interpretation of data and critical revision: DS, MS. Acquisition of data: MS, EC, JC, SN, and BA. Drafting of manuscript: DS, MS, EC, and NW.

Correspondence to Dafna Sussman.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Shulman, M., Cho, E., Aasi, B. et al. Quantitative analysis of fetal magnetic resonance phantoms and recommendations for an anthropomorphic motion phantom. Magn Reson Mater Phy (2019). https://doi.org/10.1007/s10334-019-00775-x

Download citation


  • Fetus
  • Magnetic Resonance Imaging
  • Phantoms
  • Imaging
  • Artifacts
  • Accuracy assessment
  • 3D printing
  • Synthesis methods