Evidence map›Paper›PMID 36358899›Full record

ArticleBiomolecules2022

Clinical Applications of Mixed Reality and 3D Printing in Congenital Heart Disease.

Ivan Lau, Ashu Gupta, Abdul Ihdayhid, Zhonghua Sun

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
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  9. Usefulness of Mixed Reality in Surgical Treatment: Delphi Study.Journal of medical Internet research · 2025
    Article
  10. Review
  11. Article
  12. 3D printing in medicine: bridging imaging, education, and practice.Archives of medical sciences. Atherosclerotic diseases · 2025
    Article
  13. Review
  14. Article
  15. Article
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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

4 authors at 2 institutions in 1 country.

Ivan LauDiscipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia.
Ashu GuptaDepartment of Medical Imaging, Fiona Stanley Hospital, Perth, WA 6150, Australia.
Abdul IhdayhidCurtin Medical School, Faculty of Health Sciences, Curtin University, Perth, WA 6845, Australia.
Zhonghua SunDiscipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia.ORCID 0000-0002-7538-4761
Curtin University · AUFiona Stanley Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the anatomical features and generation of realistic three-dimensional (3D) visualization of congenital heart disease (CHD) is always challenging due to the complexity and wide spectrum of CHD. Emerging technologies, including 3D printing and mixed reality (MR), have the potential to overcome these limitations based on 2D and 3D reconstructions of the standard DICOM (Digital Imaging and Communications in Medicine) images. However, very little research has been conducted with regard to the clinical value of these two novel technologies in CHD. This study aims to investigate the usefulness and clinical value of MR and 3D printing in assisting diagnosis, medical education, pre-operative planning, and intraoperative guidance of CHD surgeries through evaluations from a group of cardiac specialists and physicians. Two cardiac computed tomography angiography scans that demonstrate CHD of different complexities (atrial septal defect and double outlet right ventricle) were selected and converted into 3D-printed heart models (3DPHM) and MR models. Thirty-four cardiac specialists and physicians were recruited. The results showed that the MR models were ranked as the best modality amongst the three, and were significantly better than DICOM images in demonstrating complex CHD lesions (mean difference (MD) = 0.76,

Indexed as

Augmented RealityHeart Defects, CongenitalHeartHumansPrinting, Three-DimensionalTomography, X-Ray Computed3D printingcongenital heart diseasediagnosisextended realitymixed realityvisualization

Identifiers

PMID36358899
PMCPMC9687840
OpenAlexW4307266174

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.