Evidence map›Paper›PMID 34460787›Full record

ArticleJournal of imaging2021

A Virtual Reality System for Improved Image-Based Planning of Complex Cardiac Procedures.

Shujie Deng, Gavin Wheeler, Nicolas Toussaint, Lindsay Munroe, Suryava Bhattacharya, Gina Sajith, Ei Lin, Eeshar Singh, Ka Yee Kelly Chu, Saleha Kabir and 4 more

Abstract read
In one paragraph

Article in Journal of imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Surgical planning in virtual reality: a systematic review.Journal of medical imaging (Bellingham, Wash.) · 2024
    Review
  6. Virtual Reality-based Methods for Training Novice Electrophysiology Trainees-A Pilot Study.The Journal of innovations in cardiac rhythm management · 2023
    Article
  7. Article
  8. Article
  9. 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

14 authors.

Shujie DengSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.ORCID 0000-0001-9985-2374
Gavin WheelerSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Nicolas ToussaintSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Lindsay MunroeSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Suryava BhattacharyaSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Gina SajithSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Ei LinSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Eeshar SinghSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Ka Yee Kelly ChuSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Saleha KabirDepartment of Congenital Heart Disease, Evelina London Children's Hospital, Guy's and St Thomas' National Health Service Foundation Trust, London SE1 7EH, UK.
Kuberan PushparajahSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
John M SimpsonSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Julia A SchnabelSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.
Alberto GomezSchool of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, UK.ORCID 0000-0002-7897-7589

Funding

British Heart Foundation TA/F/20/210021
6 · The paper itself

Abstract

The intricate nature of congenital heart disease requires understanding of the complex, patient-specific three-dimensional dynamic anatomy of the heart, from imaging data such as three-dimensional echocardiography for successful outcomes from surgical and interventional procedures. Conventional clinical systems use flat screens, and therefore, display remains two-dimensional, which undermines the full understanding of the three-dimensional dynamic data. Additionally, the control of three-dimensional visualisation with two-dimensional tools is often difficult, so used only by imaging specialists. In this paper, we describe a virtual reality system for immersive surgery planning using dynamic three-dimensional echocardiography, which enables fast prototyping for visualisation such as volume rendering, multiplanar reformatting, flow visualisation and advanced interaction such as three-dimensional cropping, windowing, measurement, haptic feedback, automatic image orientation and multiuser interactions. The available features were evaluated by imaging and nonimaging clinicians, showing that the virtual reality system can help improve the understanding and communication of three-dimensional echocardiography imaging and potentially benefit congenital heart disease treatment.

Indexed as

echocardiographypre-operative imagingvirtual reality

Identifiers

PMID34460787
PMCPMC8404926

What OpenQuestion holds

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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.