Literature DB >> 34733071

Role of 3D Printing and Modeling to Aid in Neuroradiology Education for Medical Trainees.

Michael A Markovitz1, Sen Lu1, Narayan A Viswanadhan1.   

Abstract

BACKGROUND: Applications of 3-dimensional (3D) printing in medical imaging and health care are expanding. Currently, primary uses involve presurgical planning and patient and medical trainee education. Neuroradiology is a complex subdiscipline of radiology that requires further training beyond radiology residency. This review seeks to explore the clinical value of 3D printing and modeling specifically in enhancing neuroradiology education for radiology physician residents and medical trainees.
METHODS: A brief review summarizing the key steps from radiologic image to 3D printed model is provided, including storage of computed tomography and magnetic resonance imaging data as digital imaging and communications in medicine files; conversion to standard tessellation language (STL) format; manipulation of STL files in interactive medical image control system software (Materialise) to create 3D models; and 3D printing using various resins via a Formlabs 2 printer.
RESULTS: For the purposes of demonstration and proof of concept, neuroanatomy models deemed crucial in early radiology education were created via open-source hardware designs under free or open licenses. 3D-printed objects included a sphenoid bone, cerebellum, skull base, middle ear labyrinth and ossicles, mandible, circle of Willis, carotid aneurysm, and lumbar spine using a combination of clear, white, and elastic resins.
CONCLUSIONS: Based on this single-institution experience, 3D-printed complex neuroanatomical structures seem feasible and may enhance resident education and patient safety. These same steps and principles may be applied to other subspecialties of radiology. Artificial intelligence also has the potential to advance the 3D process.
Copyright © 2021 Frontline Medical Communications Inc., Parsippany, NJ, USA.

Entities:  

Year:  2021        PMID: 34733071      PMCID: PMC8560046          DOI: 10.12788/fp.0134

Source DB:  PubMed          Journal:  Fed Pract        ISSN: 1078-4497


  7 in total

1.  3D printing based on imaging data: review of medical applications.

Authors:  F Rengier; A Mehndiratta; H von Tengg-Kobligk; C M Zechmann; R Unterhinninghofen; H-U Kauczor; F L Giesel
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-05-15       Impact factor: 2.924

2.  ACR Appropriateness Criteria® Suspected Spine Trauma.

Authors:  Nicholas M Beckmann; O Clark West; Diego Nunez; Claudia F E Kirsch; Joseph M Aulino; Joshua S Broder; R Carter Cassidy; Gregory J Czuczman; Jennifer L Demertzis; Michele M Johnson; Kambiz Motamedi; Charles Reitman; Lubdha M Shah; Khoi Than; Elizabeth Ying-Kou Yung; Francesca D Beaman; Mark J Kransdorf; Julie Bykowski
Journal:  J Am Coll Radiol       Date:  2019-05       Impact factor: 5.532

3.  The effect of computed tomographic scanner parameters and 3-dimensional volume rendering techniques on the accuracy of linear, angular, and volumetric measurements of the mandible.

Authors:  Brian J Whyms; Houri K Vorperian; Lindell R Gentry; Eugene M Schimek; Edward T Bersu; Moo K Chung
Journal:  Oral Surg Oral Med Oral Pathol Oral Radiol       Date:  2013-05

4.  Patient-specific three-dimensional printing for pre-surgical planning in hepatocellular carcinoma treatment.

Authors:  Elizabeth Perica; Zhonghua Sun
Journal:  Quant Imaging Med Surg       Date:  2017-12

5.  Fully Automated and Standardized Segmentation of Adipose Tissue Compartments via Deep Learning in 3D Whole-Body MRI of Epidemiologic Cohort Studies.

Authors:  Thomas Küstner; Tobias Hepp; Marc Fischer; Martin Schwartz; Andreas Fritsche; Hans-Ulrich Häring; Konstantin Nikolaou; Fabian Bamberg; Bin Yang; Fritz Schick; Sergios Gatidis; Jürgen Machann
Journal:  Radiol Artif Intell       Date:  2020-10-28

Review 6.  Artificial intelligence and hybrid imaging: the best match for personalized medicine in oncology.

Authors:  Martina Sollini; Francesco Bartoli; Andrea Marciano; Roberta Zanca; Riemer H J A Slart; Paola A Erba
Journal:  Eur J Hybrid Imaging       Date:  2020-12-09

7.  The need for DICOM encapsulation of 3D scanning STL data.

Authors:  Jae Joon Hwang; Yun-Hoa Jung; Bong-Hae Cho
Journal:  Imaging Sci Dent       Date:  2018-12-20
  7 in total
  2 in total

1.  [Biomechanical analysis and effectiveness evaluation of zone ++ reconstruction of hemipelvis with rod-screw prosthesis].

Authors:  Jingyi Dang; Zhao Zhang; Zhenzhou Mi; Debin Cheng; Jun Fu; Dong Liu; Hongbin Fan
Journal:  Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi       Date:  2022-04-15

2.  Virtual Scoliosis Surgery Using a 3D-Printed Model Based on Biplanar Radiographs.

Authors:  Aurélien Courvoisier; Antonio Cebrian; Julien Simon; Pascal Désauté; Benjamin Aubert; Célia Amabile; Lucie Thiébaut
Journal:  Bioengineering (Basel)       Date:  2022-09-14
  2 in total

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