J Neurol Surg B Skull Base 2023; 84(05): 463-469
DOI: 10.1055/a-1885-1111
Original Article

Exploring the Impact of Using Patient-Specific 3D Prints during Consent for Skull Base Neurosurgery

Shan Y. Mian
1   Department of Surgery and Cancer, Imperial College London, Faculty of Medicine, London, United Kingdom
Shubash Jayasangaran
2   School of Medicine, The University of Edinburgh, Edinburgh, United Kingdom
Aishah Qureshi
2   School of Medicine, The University of Edinburgh, Edinburgh, United Kingdom
Mark A. Hughes
3   Edinburgh Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
› Author Affiliations


Objectives Informed consent is fundamental to good practice. We hypothesized that a personalized three-dimensional (3D)-printed model of skull base pathology would enhance informed consent and reduce patient anxiety.

Design Digital images and communication in medicine (DICOM) files were 3D printed. After a standard pre-surgery consent clinic, patients completed part one of a two-part structured questionnaire. They then interacted with their personalized 3D printed model and completed part two. This explored their perceived involvement in decision-making, anxiety, concerns and also their understanding of lesion location and surgical risks. Descriptive statistics were used to report responses and text classification tools were used to analyze free text responses.

Setting and Participants In total,14 patients undergoing elective skull base surgery (with pathologies including skull base meningioma, craniopharyngioma, pituitary adenoma, Rathke cleft cyst, and olfactory neuroblastoma) were prospectively identified at a single unit.

Results After 3D model exposure, there was a net trend toward reduced patient-reported anxiety and enhanced patient-perceived involvement in treatment. Thirteen of 14 patients (93%) felt better about their operation and 13/14 patients (93%) thought all patients should have access to personalized 3D models. After exposure, there was a net trend toward improved patient-reported understanding of surgical risks, lesion location, and extent of feeling informed. Thirteen of 14 patients (93%) felt the model helped them understand the surgical anatomy better. Analysis of free text responses to the model found mixed sentiment: 47% positive, 35% neutral, and 18% negative.

Conclusion In the context of skull base neurosurgery, personalized 3D-printed models of skull base pathology can inform the surgical consent process, impacting the levels of patient understanding and anxiety.

Previous Presentations

Early work was presented as a poster at the Congress of the European Association of Neurological Surgeons in Hamburg, in October, 2021.

Ethical Approval

The NHS Lothian Caldicott Guardian (ref 20173) issued approval of handling of patient data. Given no identifiable data was used, and that this was an observational study of outcomes with no treatments offered, no further ethical committees were consulted.

Authors' Contribution

S.M., S.J., A.Q., and M.H. all contributed to and partook in the execution of the study and collection of data, with S.M. and M.H. writing the report. M.H. acted as a supervisor and guarantor for the study.

Data Sharing

As this study was conducted by a postgraduate student, any published data will be held in its repository. As such, the data within has not been deposited or shared elsewhere, or prior to this submission, with the exception of the abstract referred to on the first page.

Publication History

Received: 02 March 2022

Accepted: 20 June 2022

Accepted Manuscript online:
27 June 2022

Article published online:
13 September 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

  • References

  • 1 Horvath J. A Brief History of 3D Printing. In: Mastering 3D Printing. Apress; 2014: 3-10
  • 2 Liaw CY, Guvendiren M. Current and emerging applications of 3D printing in medicine. Biofabrication 2017; 9 (02) 024102
  • 3 Mishra S. Application of 3D printing in medicine. Indian Heart J 2016; 68 (01) 108-109
  • 4 Schubert C, van Langeveld MC, Donoso LA. Innovations in 3D printing: a 3D overview from optics to organs. Br J Ophthalmol 2014; 98 (02) 159-161
  • 5 Ploch CC, Mansi CSSA, Jayamohan J, Kuhl E. Using 3D printing to create personalized brain models for neurosurgical training and preoperative planning. World Neurosurg 2016; 90: 668-674
  • 6 Weinstock P, Rehder R, Prabhu SP, Forbes PW, Roussin CJ, Cohen AR. Creation of a novel simulator for minimally invasive neurosurgery: fusion of 3D printing and special effects. J Neurosurg Pediatr 2017; 20 (01) 1-9
  • 7 Thiong'o GM, Bernstein M, Drake JM. 3D printing in neurosurgery education: a review. 3D Print Med 2021; 7 (01) 9
  • 8 Liew Y, Beveridge E, Demetriades AK, Hughes MA. 3D printing of patient-specific anatomy: a tool to improve patient consent and enhance imaging interpretation by trainees. Br J Neurosurg 2015; 29 (05) 712-714
  • 9 Randazzo M, Pisapia JM, Singh N, Thawani JP. 3D printing in neurosurgery: a systematic review. Surg Neurol Int 2016; 7 (34, Suppl 33) S801-S809
  • 10 Pucci JU, Christophe BR, Sisti JA, Connolly Jr ES. Three-dimensional printing: technologies, applications, and limitations in neurosurgery. Biotechnol Adv 2017; 35 (05) 521-529
  • 11 Baskaran V, Štrkalj G, Štrkalj M, Di Ieva A. Current applications and future perspectives of the use of 3D printing in anatomical training and neurosurgery. Front Neuroanat 2016; 10 (June): 69
  • 12 Waran V, Narayanan V, Karrupiah R, Cham CY. 3D Printing in Neurosurgery. In: 3D Printing in Medicine. Springer International Publishing; 2017: 51-58
  • 13 Appelbaum P, Lidz C, Meisel A. Informed Consent: Legal Theory and Clinical Practice. Fair Lawn, NJ: Oxford University Press; 1987
  • 14 Prevedello DM, Doglietto F, Jane Jr JA, Jagannathan J, Han J, Laws Jr ER. History of endoscopic skull base surgery: its evolution and current reality. J Neurosurg 2007; 107 (01) 206-213
  • 15 Fink AS, Prochazka AV, Henderson WG. et al. Predictors of comprehension during surgical informed consent. J Am Coll Surg 2010; 210 (06) 919-926
  • 16 Fink AS, Prochazka AV, Henderson WG. et al. Enhancement of surgical informed consent by addition of repeat back: a multicenter, randomized controlled clinical trial. Ann Surg 2010; 252 (01) 27-36
  • 17 Taylor AM, Diggle P, Wessels Q. What do the public know about anatomy? Anatomy education to the public and the implications. Anat Sci Educ 2018; 11 (02) 117-123
  • 18 Moxham BJ, Hennon H, Lignier B, Plaisant O. An assessment of the anatomical knowledge of laypersons and their attitudes towards the clinical importance of gross anatomy in medicine. Ann Anat 2016; 208: 194-203
  • 19 Lidz CW, Appelbaum PS, Meisel A. Two models of implementing informed consent. Arch Intern Med 1988; 148 (06) 1385-1389
  • 20 Prochazka AV, Fink AS, Bartenfeld D. et al. Patient perceptions of surgical informed consent: is repeat back helpful or harmful?. J Patient Saf 2014; 10 (03) 140-145
  • 21 Schenker Y, Fernandez A, Sudore R, Schillinger D. Interventions to improve patient comprehension in informed consent for medical and surgical procedures: a systematic review. Med Decis Making 2011; 31 (01) 151-173
  • 22 Mildenberger P, Eichelberg M, Martin E. Introduction to the DICOM standard. Eur Radiol 2002; 12 (04) 920-927
  • 23 Giannopoulos AA, Pietila T. Post-processing of DICOM Images. In: 3D Printing in Medicine. Springer International Publishing; 2017: 23-34
  • 24 Meshmixer.. Accessed December 16, 2021 at: https://www.autodesk.com/research/projects/meshmixer
  • 25 MonkeyLearn - Text Analysis. . Accessed December 17, 2021 at: https://monkeylearn.com/
  • 26 Chan SW, Tulloch E, Cooper ES, Smith A, Wojcik W, Norman JE. Montgomery and informed consent: where are we now?. BMJ 2017; 357: j2224
  • 27 Braddock III CH, Edwards KA, Hasenberg NM, Laidley TL, Levinson W. Informed decision making in outpatient practice: time to get back to basics. JAMA 1999; 282 (24) 2313-2320
  • 28 Barry MJ. Involving patients in medical decisions: how can physicians do better?. JAMA 1999; 282 (24) 2356-2357
  • 29 Bernhard JC, Isotani S, Matsugasumi T. et al. Personalized 3D printed model of kidney and tumor anatomy: a useful tool for patient education. World J Urol 2016; 34 (03) 337-345
  • 30 Web-accessible interactive software of 3D anatomy representing pathophysiological conditions to enhance the patient-consent process for procedures | Request PDF. Accessed September 27, 2021 at: https://www.researchgate.net/publication/49849999_Web-accessible_interactive_software_of_3D_anatomy_representing_pathophysiological_conditions_to_enhance_the_patient-consent_process_for_procedures
  • 31 Rodriguez-Paz JM, Kennedy M, Salas E. et al. Beyond “see one, do one, teach one”: toward a different training paradigm. Qual Saf Health Care 2009; 18 (01) 63-68
  • 32 J750 Digital Anatomy 3D Printer for Lifelike Medical Models | Stratasys. Accessed December 17, 2021 at: https://www.stratasys.com/3d-printers/j750-digital-anatomy
  • 33 Kosterhon M, Neufurth M, Neulen A. et al. Multicolor 3d printing of complex intracranial tumors in neurosurgery. J Vis Exp 2020; 2020 (155) e60471
  • 34 Schuck PH. Rethinking informed consent. Yale Law J 1994; 103 (04) 899-959