Evidence map›Paper›PMID 38282094›Full record

Review3D printing in medicine2024

Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: pediatric congenital heart disease conditions.

Justin R Ryan, Reena Ghosh, Greg Sturgeon, Arafat Ali, Elsa Arribas, Eric Braden, Seetharam Chadalavada, Leonid Chepelev, Summer Decker, Yu-Hui Huang and 10 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in 3D printing in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
–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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Applications of 3D Printing Technology in Diagnosis and Management of Heart Failure.Current treatment options in cardiovascular medicine · 2024
    Article
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

20 authors.

Justin R RyanWebster Foundation 3D Innovations Lab, Rady Children's Hospital-San Diego, San Diego, CA, USA. jryan2@rchsd.org.
Reena GhoshDepartment of Cardiac Surgery, Boston Children's Hospital, Boston, MA, USA.
Greg SturgeonDuke Children's Pediatric & Congenital Heart Center, Durham, NC, USA.
Arafat AliDepartment of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Elsa ArribasDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Eric BradenArkansas Children's Hospital, Little Rock, AR, USA.
Seetharam ChadalavadaDepartment of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Leonid ChepelevJoint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
Summer DeckerDepartment of Radiology, University of South Florida Morsani College of Medicine, Tampa, USA.
Yu-Hui HuangDepartment of Radiology, University of Minnesota, Minneapolis, MN, USA.
Ciprian IonitaDepartment of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA.
Joonhyuk LeeDepartment of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Peter LiacourasDepartment of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA.
Jayanthi ParthasarathyDepartment of Radiology, Nationwide Children's Hospital, Columbus, OH, USA.
Prashanth RaviDepartment of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Michael SandelierDepartment of Radiology - Advanced Reality Lab, James A. Haley VA Hospital, Tampa, FL, USA.
Kelsey SommerCanon Medical Informatics, Minnetonka, MN, USA.
Nicole WakeResearch and Scientific Affairs, GE HealthCare, New York, NY, USA.
Frank RybickiDepartment of Radiology, University of Arizona, Phoenix, AZ, USA.
David BallardMallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of medical 3D printing (focusing on anatomical modeling) has continued to grow since the Radiological Society of North America's (RSNA) 3D Printing Special Interest Group (3DPSIG) released its initial guideline and appropriateness rating document in 2018. The 3DPSIG formed a focused writing group to provide updated appropriateness ratings for 3D printing anatomical models across a variety of congenital heart disease. Evidence-based- (where available) and expert-consensus-driven appropriateness ratings are provided for twenty-eight congenital heart lesion categories.

methodsA structured literature search was conducted to identify all relevant articles using 3D printing technology associated with pediatric congenital heart disease 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 pediatric congenital heart lesions. Recommendations are provided in accordance with strength of evidence of publications corresponding to each cardiac clinical scenario combined with expert opinion from members of the 3DPSIG.

conclusionsThis consensus appropriateness ratings document, created by the members of the RSNA 3DPSIG, provides a reference for clinical standards of 3D printing for pediatric congenital heart disease clinical scenarios.

Indexed as

3D printingAdditive manufacturingAnatomic modelAnd congenital heart diseaseAppropriatenessCardiacQualityRadiology

Identifiers

PMID38282094
PMCPMC10823658

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.