Abdominal Radiology

, Volume 43, Issue 10, pp 2809–2822 | Cite as

Principles of three-dimensional printing and clinical applications within the abdomen and pelvis

  • Sarah Bastawrous
  • Nicole Wake
  • Dmitry Levin
  • Beth Ripley


Improvements in technology and reduction in costs have led to widespread interest in three-dimensional (3D) printing. 3D-printed anatomical models contribute to personalized medicine, surgical planning, and education across medical specialties, and these models are rapidly changing the landscape of clinical practice. A physical object that can be held in one’s hands allows for significant advantages over standard two-dimensional (2D) or even 3D computer-based virtual models. Radiologists have the potential to play a significant role as consultants and educators across all specialties by providing 3D-printed models that enhance clinical care. This article reviews the basics of 3D printing, including how models are created from imaging data, clinical applications of 3D printing within the abdomen and pelvis, implications for education and training, limitations, and future directions.


3D printing 3-D printing Additive manufacturing Abdominal imaging Pre-surgical planning 


Compliance with ethical standards


This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.


  1. 1.
  2. 2.
    Matsumoto JS, Morris JM, Foley TA, et al. (2015) Three-dimensional physical modeling : applications and experience at Mayo Clinic. Radiographics 35:1989–2006CrossRefPubMedGoogle Scholar
  3. 3.
    Mitsouras D, Liacouras P, Imanzadeh A, et al. (2015) Medical 3D printing for the radiologist. Radiographics 35(7):1965–1988CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Wake N, Rude T, Kang SK, et al. (2017) 3D printed renal cancer models derived from MRI data: application in pre-surgical planning. Abdom Radiol 42(5):1501–1509CrossRefGoogle Scholar
  5. 5.
    Choy WJ, Mobbs RJ, Wilcox B, et al. (2017) Reconstruction of thoracic spine using a personalized 3D-printed vertebral body in adolescent with T9 primary bone tumor. World Neurosurg 105:1032.e13–1032.e17CrossRefGoogle Scholar
  6. 6.
    Wong KC, Kumta SM, Geel NV, et al. (2015) One-step reconstruction with a 3D-printed, biomechanically evaluated custom implant after complex pelvic tumor resection. Comput Aided Surg 20(1):14–23CrossRefPubMedGoogle Scholar
  7. 7.
    Javan R, Herrin D, Tangestanipoor A (2016) Understanding spatially complex segmental and branch anatomy using 3D printing. Acad Radiol 23(9):1183–1189CrossRefPubMedGoogle Scholar
  8. 8.
    Aranda JL, Jiménez MF, Rodríguez M, Varela G (2015) Tridimensional titanium-printed custom-made prosthesis for sternocostal reconstruction. Eur J Cardiothoracic Surg 48(4):e92–e94CrossRefGoogle Scholar
  9. 9.
    Park E-K, Lim J-Y, Yun I-S, et al. (2016) Cranioplasty enhanced by three-dimensional printing. J Craniofac Surg 27(4):1Google Scholar
  10. 10.
    Bernhard J-C, Isotani S, Matsugasumi T, et al. (2016) Personalized 3D printed model of kidney and tumor anatomy: a useful tool for patient education. World J Urol 34(3):337–345CrossRefPubMedGoogle Scholar
  11. 11.
    Suzuki M, Ogawa Y, Kawano A, et al. (2004) Rapid prototyping of temporal bone for surgical training and medical education. Acta Otolaryngol 124(4):400–402CrossRefPubMedGoogle Scholar
  12. 12.
    Adams F, Qiu T, Mark A, et al. (2017) Soft 3D-printed phantom of the human kidney with collecting system. Ann Biomed Eng 45(4):963–972CrossRefPubMedGoogle Scholar
  13. 13.
    Gross BC, Erkal JL, Lockwood SY, Chen C, Spence DM (2014) Evaluation of 3D printing and its potential impact on biotechnology and the chemical sciences. Anal Chem 86(7):3240–3253CrossRefPubMedGoogle Scholar
  14. 14.
    Konno T, Mashiko T, Oguma H, et al. (2016) Rapid 3-dimensional models of cerebral aneurysm for emergency surgical clipping. No Shinkei Geka 44(8):651–660PubMedGoogle Scholar
  15. 15.
    Janusziewicz R, Tumbleston JR, Quintanilla AL, Mecham SJ, Desimone JM (2016) Layerless fabrication with continuous liquid interface production. Proc Natl Acad Sci USA 113(42):11703–11708CrossRefPubMedGoogle Scholar
  16. 16.
    Ripley B, Levin D, Kelil T, et al. (2017) 3D printing from MRI Data: harnessing strengths and minimizing weaknesses. J Magn Reson Imaging 45(3):635–645CrossRefPubMedGoogle Scholar
  17. 17.
    Hsu C, Ghaffari M, Alaraj A, et al. (2017) Gap-free segmentation of vascular networks with automatic image processing pipeline. Comput Biol Med 82(January):29–39CrossRefPubMedGoogle Scholar
  18. 18.
    Schulz-Wendtland R, Harz M, Meier-Meitinger M, et al. (2017) Semi-automated delineation of breast cancer tumors and subsequent materialization using three-dimensional printing (rapid prototyping). J Surg Oncol 115(3):238–242CrossRefPubMedGoogle Scholar
  19. 19.
    George E, Liacouras P, Rybicki FJ, Mitsouras D (2017) Measuring and establishing the accuracy and reproducibility of 3D printed medical models. Radiographics 5:160165Google Scholar
  20. 20.
    Leng S, McGee K, Morris J, et al. (2017) Anatomic modeling using 3D printing: quality assurance and optimization. 3D Print Med 3(1):6CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Di Prima M, Coburn J, Hwang D, et al. (2015) Additively manufactured medical products—the FDA perspective. 3D Print Med 2(1):1CrossRefGoogle Scholar
  22. 22.
    Zein NN, Hanouneh IA, Bishop PD, et al. (2013) Three-dimensional print of a liver for preoperative planning in living donor liver transplantation. Liver Transplant 19:1304–1310CrossRefGoogle Scholar
  23. 23.
    Ikegami T, Maehara Y (2013) Transplantation: 3D printing of the liver in living donor liver transplantation. Nat Rev Gastroenterol Hepatol 10(12):697–698CrossRefPubMedGoogle Scholar
  24. 24.
    Kong X, Nie L, Zhang H, et al. (2016) Do Three-dimensional visualization and three-dimensional printing improve hepatic segment anatomy teaching? A Randomized Controlled Study. J Surg Educ 73(2):264–269CrossRefPubMedGoogle Scholar
  25. 25.
    Marro A, Bandukwala T, Mak W (2016) Three-dimensional printing and medical imaging: a review of the methods and applications. Curr Probl Diagn Radiol 45(1):2–9CrossRefPubMedGoogle Scholar
  26. 26.
    Marconi S, Pugliese L, Del Chiaro M, et al. (2016) An innovative strategy for the identification and 3D reconstruction of pancreatic cancer from CT images. Updates Surg 68(3):273–278CrossRefPubMedGoogle Scholar
  27. 27.
    Andolfi C, Plana A, Kania P, Banerjee PP, Small S (2017) Usefulness of three-dimensional modeling in surgical planning, resident training, and patient education. J Laparoendosc Adv Surg Tech 27(5):512–515CrossRefGoogle Scholar
  28. 28.
    Sayed Aluwee SAZ, Bin Zhou X, Kato H, et al. (2017) Evaluation of pre-surgical models for uterine surgery by use of three-dimensional printing and mold casting. Radiol Phys Technol 10(3):279–285CrossRefPubMedGoogle Scholar
  29. 29.
    Baek MH, Kim DY, Kim N, et al. (2016) Incorporating a 3-dimensional printer into the management of early-stage cervical cancer. J Surg Oncol 114(2):150–152CrossRefPubMedGoogle Scholar
  30. 30.
    Werner H, Lopes J, Tonni G, Araujo Júnior E (2015) Physical model from 3D ultrasound and magnetic resonance imaging scan data reconstruction of lumbosacral myelomeningocele in a fetus with Chiari II malformation. Child’s Nerv Syst 31(4):511–513CrossRefGoogle Scholar
  31. 31.
    Westerman ME, Matsumoto JM, Morris JM, Leibovich BC (2016) Three-dimensional printing for renal cancer and surgical planning. Eur Urol Focus 2(6):574–576CrossRefPubMedGoogle Scholar
  32. 32.
    Silberstein JL, Maddox MM, Dorsey P, et al. (2014) Physical models of renal malignancies using standard cross-sectional imaging and 3-dimensional printers: a pilot study. Urology 84(2):268–272CrossRefPubMedGoogle Scholar
  33. 33.
    Zhang Y, Ge H, Li N, et al. (2016) Evaluation of three-dimensional printing for laparoscopic partial nephrectomy of renal tumors: a preliminary report. World J Urol 34(4):533–537CrossRefPubMedGoogle Scholar
  34. 34.
    Wake N, Chandarana H, Huang WC, Taneja SS, Rosenkrantz AB (2016) Application of anatomically accurate, patient-specific 3D printed models from MRI data in urological oncology. Clin Radiol 71(6):610–614CrossRefPubMedGoogle Scholar
  35. 35.
    Chen DYT, Uzzo RG (2009) Optimal management of localized renal cell carcinoma: surgery, ablation, or active surveillance. J Natl Compr Canc Netw 7(6):635–642; quiz 643Google Scholar
  36. 36.
    Sivarajan G, Huang WC (2012) Current practice patterns in the surgical management of renal cancer in the United States. Urol Clin N Am 39(2):149–160, vGoogle Scholar
  37. 37.
    Ellison JS, Montgomery JS, Hafez KS, et al. (2013) Association of RENAL nephrometry score with outcomes of minimally invasive partial nephrectomy. Int J Urol 20(6):564–570CrossRefPubMedGoogle Scholar
  38. 38.
    Simhan J, Smaldone MC, Tsai KJ, et al. (2011) Objective measures of renal mass anatomic complexity predict rates of major complications following partial nephrectomy. Eur Urol 60(4):724–730CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Zargar H, Allaf ME, Bhayani S, et al. (2015) Trifecta and optimal perioperative outcomes of robotic and laparoscopic partial nephrectomy in surgical treatment of small renal masses: a multi-institutional study. BJU Int 116(3):407–414CrossRefPubMedGoogle Scholar
  40. 40.
    Atug F, Castle EP, Woods M, Davis R, Thomas R (2006) Robotics in urologic surgery: an evolving new technology. Int J Urol 13(7):857–863CrossRefPubMedGoogle Scholar
  41. 41.
    Knoedler M, Feibus AH, Lange A, et al. (2015) Individualized physical 3-dimensional kidney tumor models constructed from 3-dimensional printers result in improved trainee anatomic understanding. Urology 85(6):1257–1261CrossRefPubMedGoogle Scholar
  42. 42.
    Maddox MM, Feibus A, Liu J, et al. (2017) 3D-printed soft-tissue physical models of renal malignancies for individualized surgical simulation: a feasibility study. J Robot Surg 12(1):27–33CrossRefPubMedGoogle Scholar
  43. 43.
    Tran-Gia J, Schlogl S, Lassmann M (2016) Design and fabrication of kidney phantoms for internal radiation dosimetry using 3D printing technology. J Nucl Med 57(12):1998–2005CrossRefPubMedGoogle Scholar
  44. 44.
    Department of Health and Human Services: Center for Disease Control and Prevention and NCI (2014) U.S. Cancer Statistics Working Group. United States Cancer Statistics: 1999–2011 Incidence and Mortality Web-based ReportGoogle Scholar
  45. 45.
    Siegel RL, Miller KD, Jemal A (2017) Cancer Statistics, 2017. CA Cancer J Clin 67(1):7–30CrossRefPubMedGoogle Scholar
  46. 46.
    Shin T, Ukimura O, Gill IS (2016) Three-dimensional printed model of prostate anatomy and targeted biopsy-proven index tumor to facilitate nerve-sparing prostatectomy. Eur Urol 69(2):377–379CrossRefPubMedGoogle Scholar
  47. 47.
    Reis SP, Majdalany BS, AbuRahma AF, et al. (2017) ACR appropriateness criteria® pulsatile abdominal mass suspected abdominal aortic aneurysm. J Am Coll Radiol 14(5):S258–S265CrossRefPubMedGoogle Scholar
  48. 48.
    Powell JT, Sweeting MJ, Ulug P, et al. (2017) Meta-analysis of individual-patient data from EVAR-1, DREAM, OVER and ACE trials comparing outcomes of endovascular or open repair for abdominal aortic aneurysm over 5 years. Br J Surg 104(3):166–178CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Reise JA, Sheldon H, Earnshaw J, et al. (2010) Patient preference for surgical method of abdominal aortic aneurysm repair: postal survey. Eur J Vasc Endovasc Surg 39(1):55–61CrossRefPubMedGoogle Scholar
  50. 50.
    Neequaye SK, Aggarwal R, Van Herzeele I, Darzi A, Cheshire NJ (2007) Endovascular skills training and assessment. J Vasc Surg 46(5):1055–1064CrossRefPubMedGoogle Scholar
  51. 51.
    Torres IO, De Luccia N (2016) A simulator for training in endovascular aneurysm repair: the use of three dimensional printers. Eur J Vasc Endovasc Surg 54(2):247–253CrossRefGoogle Scholar
  52. 52.
    Tam MD, Latham TR, Lewis M, et al. (2016) A pilot study assessing the impact of 3-D printed models of aortic aneurysms on management decisions in EVAR planning. Vasc Endovasc Surg 50(1):4–9CrossRefGoogle Scholar
  53. 53.
    Taylor SM, Mills JL, Fujitani RM (1994) The juxtarenal abdominal aortic aneurysm. A more common problem than previously realized? Arch Surg 129(7):734–737CrossRefPubMedGoogle Scholar
  54. 54.
    Hu Z, Li Y, Peng R, et al. (2016) Experience with fenestrated endovascular repair of juxtarenal abdominal aortic aneurysms at a single center. Medicine (Baltimore) 95(10):e2683CrossRefGoogle Scholar
  55. 55.
    Starnes BW, Tatum B (2012) Early report from an investigator-initiated investigational device exemption clinical trial on physician-modified endovascular grafts. J Vasc Surg 58(2):311–317CrossRefGoogle Scholar
  56. 56.
    Taher F, Falkensammer J, McCarte J, et al. (2017) The influence of prototype testing in three-dimensional aortic models on fenestrated endograft design. J Vasc Surg 65(6):1591–1597CrossRefPubMedGoogle Scholar
  57. 57.
    Leotta DF, Starnes BW (2015) Custom fenestration templates for endovascular repair of juxtarenal aortic aneurysms. J Vasc Surg 61(6):1637–1641CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Meess KM, Izzo RL, Dryjski ML, Curl RE, et al. (2017) 3D printed abdominal aortic aneurysm phantom for image guided surgical planning with a patient specific fenestrated endovascular graft system. In: Cook TS, Zhang J (eds) Proceedings of SPIE—the International Society for Optical Engineering. SPIE, Bellingham, p 101380PGoogle Scholar
  59. 59.
    Koleilat I, Jaeggli M, Ewing JA, et al. (2016) Interobserver variability in physician-modified endograft planning by comparison with a three-dimensional printed aortic model. J Vasc Surg 64(6):1789–1796CrossRefPubMedGoogle Scholar
  60. 60.
    Huang J, Li G, Wang W, Wu K, Le T (2016) 3D printing guiding stent graft fenestration: a novel technique for fenestration in endovascular aneurysm repair. Vascular 25(4):442–446CrossRefPubMedGoogle Scholar
  61. 61.
    Itagaki MW (2015) Using 3D printed models for planning and guidance during endovascular intervention: a technical advance. Diagn Interv Radiol 21(4):338–341CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Yuan D, Luo H, Yang H, et al. (2017) Precise treatment of aortic aneurysm by three-dimensional printing and simulation before endovascular intervention. Sci Rep. 7(1):795CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Ruiz S, Galarreta D, Antón R, Cazón A, Finol EA (2017) A methodology for developing anisotropic AAA phantoms via additive manufacturing. J Biomech 57:161–166CrossRefGoogle Scholar
  64. 64.
    Marconi S, Pugliese L, Botti M, et al. (2017) Value of 3D printing for the comprehension of surgical anatomy. Surg Endosc 31(10):4102–4110CrossRefPubMedGoogle Scholar
  65. 65.
    Waran V, Devaraj P, Hari Chandran T, et al. (2012) Three-dimensional anatomical accuracy of cranial models created by rapid prototyping techniques validated using a neuronavigation station. J Clin Neurosci 19(4):574–577CrossRefPubMedGoogle Scholar
  66. 66.
    Mafeld S, Nesbitt C, Mccaslin J, et al. (2017) Three-dimensional (3D) printed endovascular simulation models: a feasibility study. Ann Transl Med 5(3):1–8CrossRefGoogle Scholar
  67. 67.
    Kolesky DB, Truby RL, Gladman AS, et al. (2014) 3D bioprinting of vascularized, heterogeneous cell-laden tissue constructs. Adv Mater 26(19):3124–3130CrossRefPubMedGoogle Scholar
  68. 68.
    Kang K, Kim Y, Lee SB, et al. (2017) Three-dimensional bio-printing of hepatic structures with direct-converted hepatocyte-like cells. Tissue Eng Part A . CrossRefPubMedGoogle Scholar
  69. 69.
    Laronda MM, Rutz AL, Xiao S, et al. (2017) A bioprosthetic ovary created using 3D printed microporous scaffolds restores ovarian function in sterilized mice. Nat Commun 8:15261CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Huotilainen E, Jaanimets R, Valášek J, et al. (2014) Inaccuracies in additive manufactured medical skull models caused by the DICOM to STL conversion process. J Craniomaxillofac Surg 42(5):259–265CrossRefGoogle Scholar
  71. 71.
    Hoang D, Perrault D, Stevanovic M, Ghiassi A (2016) Surgical applications of three-dimensional printing: a review of the current literature and how to get started. Ann Transl Med 4(23):456CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply  2018

Authors and Affiliations

  • Sarah Bastawrous
    • 1
    • 2
  • Nicole Wake
    • 3
    • 4
  • Dmitry Levin
    • 5
  • Beth Ripley
    • 1
    • 2
  1. 1.Department of RadiologyUniversity of Washington School of MedicineSeattleUSA
  2. 2.Department of RadiologyVA Puget Sound Health Care SystemSeattleUSA
  3. 3.Department of Radiology, Center for Advanced Imaging Innovation and Research and Bernard and Irene Schwartz Center for Biomedical ImagingNew York University School of MedicineNew YorkUSA
  4. 4.Sackler Institute of Graduate Biomedical SciencesNew York University School of MedicineNew YorkUSA
  5. 5.Division of Cardiology, Department of MedicineUniversity of Washington School of MedicineSeattleUSA

Personalised recommendations