Evidence map›Paper›PMID 38032479›Full record

Review3D printing in medicine2023

Clinical situations for which 3D Printing is considered an appropriate representation or extension of data contained in a medical imaging examination: vascular conditions.

Joonhyuk Lee, Seetharam C Chadalavada, Anish Ghodadra, Arafat Ali, Elsa M Arribas, Leonid Chepelev, Ciprian N Ionita, Prashanth Ravi, Justin R Ryan, Lumarie Santiago and 4 more

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in 3D printing in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. A 3D-printed model of axillary cavernous hemangioma.Journal of vascular surgery cases and innovative techniques · 2025
    Article
  3. Article
  4. 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

14 authors at 11 institutions in 2 countries.

Joonhyuk LeeDepartment of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA.
Seetharam C ChadalavadaDepartment of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA.
Anish GhodadraDepartment of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Arafat AliDepartment of Radiology, Henry Ford Health, Detroit, MI, USA.
Elsa M ArribasDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Leonid ChepelevJoint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
Ciprian N IonitaDepartment of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA.
Prashanth RaviDepartment of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA.
Justin R RyanWebster Foundation 3D Innovations Lab, Rady Children's Hospital, San Diego, CA, USA.
Lumarie SantiagoDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Nicole WakeDepartment of Research and Scientific Affairs, GE HealthCare, New York, NY, USA.
Adnan M SheikhDepartment of Radiology, University of British Columbia, Vancouver, Canada.
Frank J RybickiDepartment of Radiology, University of Arizona - Phoenix, Phoenix, AZ, USA.
David H BallardMallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA. davidballard@wustl.edu.
University of Cincinnati Medical Center · USThe University of Texas MD Anderson Cancer Center · USAdvanced Imaging Research (United States) · USHenry Ford Health System · USMallinckrodt (United States) · USUC San Diego Health System · USUniversity at Buffalo, State University of New York · USUniversity of Arizona · USUniversity of British Columbia · CAUniversity of Pittsburgh Medical Center · USUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedical three-dimensional (3D) printing has demonstrated utility and value in anatomic models for vascular conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (3DPSIG) provides appropriateness recommendations for vascular 3D printing indications.

methodsA structured literature search was conducted to identify all relevant articles using 3D printing technology associated with vascular indications. Each study was vetted by the authors and strength of evidence was assessed according to published appropriateness ratings.

resultsEvidence-based recommendations for when 3D printing is appropriate are provided for the following areas: aneurysm, dissection, extremity vascular disease, other arterial diseases, acute venous thromboembolic disease, venous disorders, lymphedema, congenital vascular malformations, vascular trauma, vascular tumors, visceral vasculature for surgical planning, dialysis access, vascular research/development and modeling, and other vasculopathy. Recommendations are provided in accordance with strength of evidence of publications corresponding to each vascular condition combined with expert opinion from members of the 3DPSIG.

conclusionThis consensus appropriateness ratings document, created by the members of the 3DPSIG, provides an updated reference for clinical standards of 3D printing for the care of patients with vascular conditions.

Indexed as

3D printingAdditive manufacturingAnatomic modelAppropriatenessQualityRadiologyRapid prototypingVascular diseaseVascular surgery

Identifiers

PMID38032479
PMCPMC10688120
OpenAlexW4389179956

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.