Advertisement

Skeletal Radiology

, Volume 48, Issue 5, pp 791–802 | Cite as

A prototype assembled 3D-printed phantom of the glenohumeral joint for fluoroscopic-guided shoulder arthrography

  • Ramin JavanEmail author
  • Amy L. Ellenbogen
  • Nicholas Greek
  • Shawn Haji-Momenian
Technical Report
  • 167 Downloads

Abstract

Purpose

To describe the methodology of constructing a three-dimensional (3D) printed model of the glenohumeral joint, to serve as an interventional phantom for fluoroscopy-guided shoulder arthrography training.

Materials and methods

The osseous structures, intra-articular space and skin surface of the shoulder were digitally extracted as separate 3D meshes from a normal CT arthrogram of the shoulder, using commercially available software. The osseous structures were 3D-printed in gypsum, a fluoroscopically radiopaque mineral, using binder jet technology. The joint capsule was 3D printed with rubber-like TangoPlus material, using PolyJet technology. The capsule was secured to the humeral head and glenoid to create a sealed intra-articular space. A polyamide mold of the skin was printed using selective laser sintering. The joint was stabilized inside the mold, and the surrounding soft tissues were cast in silicone of varying densities. Fluoroscopically-guided shoulder arthrography was performed using anterior, posterior, and rotator interval approaches. CT arthrographic imaging of the phantom was also performed.

Results

A life-size phantom of the glenohumeral joint was constructed. The radiopaque osseous structures replicated in-vivo osseous corticomedullary differentiation, with dense cortical bone and less dense medullary cancellous bone. The glenoid labrum was successfully integrated into the printed capsule, and visualized on CT arthrography. The phantom was repeatedly used to perform shoulder arthrography using all three conventional approaches, and simulated the in vivo challenges of needle guidance.

Conclusions

3D printing of a complex capsule, such as the glenohumeral joint, is possible with this technique. Such a model can serve as a valuable training tool.

Notes

Acknowledgements

The authors would like to thank Maureen Schickel from Materialise for offering her technical expertise.

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflicts of interest.

References

  1. 1.
    Lomasney LM, Choi H, Jayanthi N. Magnetic resonance arthrography of the upper extremity. Radiol Clin N Am. 2013;51(2):227–37.CrossRefGoogle Scholar
  2. 2.
    Malfair D. Therapeutic and diagnostic joint injections. Radiol Clin N Am. 2008;46(3):439–53.CrossRefGoogle Scholar
  3. 3.
    Magee T. 3-T MRI of the shoulder: is MR arthrography necessary? AJR Am J Roentgenol. 2009;192(1):86–92.CrossRefGoogle Scholar
  4. 4.
    Probyn LJ, White LM, Salonen DC, Tomlinson G, Boynton EL. Recurrent symptoms after shoulder instability repair: direct MR arthrographic assessment--correlation with second-look surgical evaluation. Radiology. 2007;245(3):814–23.CrossRefGoogle Scholar
  5. 5.
    Jacobson JA, Lin J, Jamadar DA, Hayes CW. Aids to successful shoulder arthrography performed with a fluoroscopically guided anterior approach. Radiographics. 2003;379;23(2):373–8; discussion 379.Google Scholar
  6. 6.
    Farmer KD, Hughes PM. MR arthrography of the shoulder: fluoroscopically guided technique using a posterior approach. AJR Am J Roentgenol. 2002;178(2):433–4.CrossRefGoogle Scholar
  7. 7.
    Depelteau H, Bureau NJ, Cardinal E, Aubin B, Brassard P. Arthrography of the shoulder: a simple fluoroscopically guided approach for targeting the rotator cuff interval. AJR Am J Roentgenol. 2004;182(2):329–32.CrossRefGoogle Scholar
  8. 8.
    Friedman T, Michalski M, Goodman TR, Brown JE. 3D printing from diagnostic images: a radiologist's primer with an emphasis on musculoskeletal imaging-putting the 3D printing of pathology into the hands of every physician. Skeletal Radiol. 2016;45(3):307–21.CrossRefGoogle Scholar
  9. 9.
    Auricchio F, Marconi S. 3D printing: clinical applications in orthopaedics and traumatology. EFORT Open Rev. 2016;1(5):121–7.CrossRefGoogle Scholar
  10. 10.
    Numminen K, Sipila O, Makisalo H. Preoperative hepatic 3D models: virtual liver resection using three-dimensional imaging technique. Eur J Radiol. 2005;56(2):179–84.CrossRefGoogle Scholar
  11. 11.
    Esses SJ, Berman P, Bloom AI, Sosna J. Clinical applications of physical 3D models derived from MDCT data and created by rapid prototyping. AJR Am J Roentgenol. 2011;196(6):W683–8.CrossRefGoogle Scholar
  12. 12.
    Vukicevic M, Mosadegh B, Min JK, Little SH. Cardiac 3D printing and its future directions. J Am Coll Cardiol Imaging. 2017;10(2):171–84.CrossRefGoogle Scholar
  13. 13.
    Javan R, Herrin D, Tangestanipoor A. Understanding spatially complex segmental and branch anatomy using 3D printing: liver, lung, prostate, coronary arteries, and circle of Willis. Acad Radiol. 2016;23(9):1183–9.CrossRefGoogle Scholar
  14. 14.
    Tai BL, Rooney D, Stephenson F, Liao P, Sagher O, Shih AJ, et al. Development of a 3D-printed external ventricular drain placement simulator: technical note. J Neurosurg. 2015;123(4):1070–6.CrossRefGoogle Scholar
  15. 15.
    O'Reilly MK, Reese S, Herlihy T, Geoghegan T, Cantwell CP, Feeney RNM, et al. Fabrication and assessment of 3D printed anatomical models of the lower limb for anatomical teaching and femoral vessel access training in medicine. Anat Sci Educ. 2016;9(1):71–9.CrossRefGoogle Scholar
  16. 16.
    Dias TR, Alves Junior JDC, Abdala N. Learning curve of radiology residents during training in fluoroscopy-guided facet joint injections. Radiol Bras. 2017;50(3):162–9.CrossRefGoogle Scholar
  17. 17.
    Ali S, Qandeel M, Ramakrishna R, Yang CW. Virtual simulation in enhancing procedural training for fluoroscopy-guided lumbar puncture: a pilot study. Acad Radiol. 2018;25(2):235–9.CrossRefGoogle Scholar
  18. 18.
    Javan R, Bansal M, Tangestanipoor A. A prototype hybrid gypsum-based 3-dimensional printed training model for computed tomography-guided spinal pain management. J Comput Assist Tomogr. 2016;40(4):626–31.CrossRefGoogle Scholar
  19. 19.
    Pham DL, Xu C, Prince JL. Current methods in medical image segmentation. Annu Rev Biomed Eng. 2000;2:315–37.CrossRefGoogle Scholar
  20. 20.
    Mitsouras D, Liacouras P, Imanzadeh A, Giannopoulos AA, Cai T, Kumamaru KK, et al. Medical 3D printing for the radiologist. Radiographics. 2015;35(7):1965–88.CrossRefGoogle Scholar
  21. 21.
    Shirazi SFS, Gharehkhani S, Mehrali M, Yarmand H, Metselaar HSC, Kadri NA, et al. A review on powder-based additive manufacturing for tissue engineering: selective laser sintering and inkjet 3D printing. Sci Technol Adv Mater. 2015;16(3):033502.  https://doi.org/10.1088/1468-6996/16/3/033502.CrossRefGoogle Scholar
  22. 22.
    Faulkner AR, Bourgeois AC, Bradley YC, Pasciak AS. A robust and inexpensive phantom for fluoroscopically guided lumbar puncture training. Simul Healthc. 2015;10(1):54–8.CrossRefGoogle Scholar
  23. 23.
    Dimmick S, Jones M, Challen J, Iedema J, Wattuhewa U, Coucher J. CT-guided procedures: evaluation of a phantom system to teach accurate needle placement. Clin Radiol. 2007;62(2):166–71.CrossRefGoogle Scholar
  24. 24.
    Boddu SR, Corey A, Peterson R, Saindane AM, Hudgins PA, Chen Z, et al. Fluoroscopic-guided lumbar puncture: fluoroscopic time and implications of body mass index—a baseline study. AJNR Am J Neuroradiol. 2014;35(8):1475–80.CrossRefGoogle Scholar
  25. 25.
    Liu Y, Gao Q, Du S, Chen Z, Fu J, Chen B, et al. Fabrication of cerebral aneurysm simulator with a desktop 3D printer. Sci Rep. 2017;7:44301.CrossRefGoogle Scholar
  26. 26.
    Chen RK, Shih AJ. Multi-modality gellan gum-based tissue-mimicking phantom with targeted mechanical, electrical, and thermal properties. Phys Med Biol. 2013;58(16):5511–25.CrossRefGoogle Scholar
  27. 27.
    Ryan JR, Chen T, Nakaji P, Frakes DH, Gonzalez LF. Ventriculostomy simulation using patient-specific ventricular anatomy, 3D printing, and hydrogel casting. World Neurosurg. 2015;84(5):1333–9.CrossRefGoogle Scholar
  28. 28.
    Morais P, Tavares JMRS, Queiros S, Veloso F, D'hooge J, Vilaca JL. Development of a patient-specific atrial phantom model for planning and training of inter-atrial interventions. Med Phys. 2017;44(11):5638–49.CrossRefGoogle Scholar
  29. 29.
    Javan R, Cho AL. An assembled prototype multimaterial three-dimensional-printed model of the neck for computed tomography- and ultrasound-guided interventional procedures. J Comput Assist Tomogr. 2017;41(6):941–8.CrossRefGoogle Scholar

Copyright information

© ISS 2018

Authors and Affiliations

  1. 1.Department of RadiologyGeorge Washington University HospitalWashingtonUSA
  2. 2.Clinical Learning and Simulation Skills (CLASS) CenterGeorge Washington University School of MedicineWashingtonUSA

Personalised recommendations