Evidence map›Paper›PMID 35614275›Full record

ArticleJournal of digital imaging2022

HEARTBEAT4D: An Open-source Toolbox for Turning 4D Cardiac CT into VR/AR.

M Bindschadler, S Buddhe, M R Ferguson, T Jones, S D Friedman, R K Otto

Open access · greenAbstract read
In one paragraph

Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

6 authors at 4 institutions in 2 countries.

M BindschadlerDepartment of Neurology, Seattle, WA, USA.
S BuddheDepartment of Pediatrics, Seattle Children's Heart Center and the University of Washington, Seattle, WA, USA.
M R FergusonDepartment of Radiology, University of Washington, Seattle, WA, USA.
T JonesDepartment of Pediatrics, Seattle Children's Heart Center and the University of Washington, Seattle, WA, USA.
S D FriedmanDepartment of Neurology, Seattle, WA, USA.
R K OttoDepartment of Radiology, University of Washington, Seattle, WA, USA. randolph.otto@seattlechildrens.org.ORCID 0000-0003-1273-7176
Seattle Children's Hospital · USUniversity of Washington · USImprovement Service · GBSeattle Children's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Four-dimensional data sets are increasingly common in MRI and CT. While clinical visualization often focuses on individual temporal phases capturing the tissue(s) of interest, it may be possible to gain additional insight through exploring animated 3D reconstructions of physiological motion made possible by augmented or virtual reality representations of 4D patient imaging. Cardiac CT acquisitions can provide sufficient spatial resolution and temporal data to support advanced visualization, however, there are no open-source tools readily available to facilitate the transformation from raw medical images to dynamic and interactive augmented or virtual reality representations. To address this gap, we developed a workflow using free and open-source tools to process 4D cardiac CT imaging starting from raw DICOM data and ending with dynamic AR representations viewable on a phone, tablet, or computer. In addition to assembling the workflow using existing platforms (3D Slicer and Unity), we also contribute two new features: 1. custom software which can propagate a segmentation created for one cardiac phase to all others and export to surface files in a fully automated fashion, and 2. a user interface and linked code for the animation and interactive review of the surfaces in augmented reality. Validation of the surface-based areas demonstrated excellent correlation with radiologists' image-based areas (R > 0.99). While our tools were developed specifically for 4D cardiac CT, the open framework will allow it to serve as a blueprint for similar applications applied to 4D imaging of other tissues and using other modalities. We anticipate this and related workflows will be useful both clinically and for educational purposes.

Indexed as

Augmented RealityVirtual RealityFour-Dimensional Computed TomographyHumansImaging, Three-DimensionalMagnetic Resonance ImagingSoftware

Identifiers

PMID35614275
PMCPMC9712868
OpenAlexW4281555750

What OpenQuestion holds

Textmetadata
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.