Evidence map›Paper›PMID 31889235›Full record

Article3D printing in medicine2019

Creating patient-specific anatomical models for 3D printing and AR/VR: a supplement for the 2018 Radiological Society of North America (RSNA) hands-on course.

Nicole Wake, Amy E Alexander, Andy M Christensen, Peter C Liacouras, Maureen Schickel, Todd Pietila, Jane Matsumoto

Abstract read
In one paragraph

Article in 3D printing in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. A training tool for clinicians in segmenting medical images to make 3D models.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2023
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nicole WakeDepartment of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY, 10467, USA. nwake@montefiore.org.ORCID http://orcid.org/0000-0002-8441-6059
Amy E AlexanderDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Andy M ChristensenDepartment of Radiology, The Ottawa Hospital, Ottawa, Canada.
Peter C Liacouras3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, MD, USA.
Maureen SchickelMaterialise USA, Plymouth, MI, USA.
Todd PietilaMaterialise USA, Plymouth, MI, USA.
Jane MatsumotoDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Christopher M Collins · 2014 to 2026
$19.3M
NIBIB NIH HHS NIH P41 EB017183NIBIB NIH HHS P41 EB017183Stratasys In-kind Research Support
6 · The paper itself

Abstract

Advanced visualization of medical image data in the form of three-dimensional (3D) printing continues to expand in clinical settings and many hospitals have started to adapt 3D technologies to aid in patient care. It is imperative that radiologists and other medical professionals understand the multi-step process of converting medical imaging data to digital files. To educate health care professionals about the steps required to prepare DICOM data for 3D printing anatomical models, hands-on courses have been delivered at the Radiological Society of North America (RSNA) annual meeting since 2014. In this paper, a supplement to the RSNA 2018 hands-on 3D printing course, we review methods to create cranio-maxillofacial (CMF), orthopedic, and renal cancer models which can be 3D printed or visualized in augmented reality (AR) or virtual reality (VR).

Indexed as

3D printingAugmented realityVirtual reality

Identifiers

PMID31889235
PMCPMC6937827

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.