Evidence map›Paper›PMID 36908292›Full record

ArticleFrontiers in medical technology2023

A workflow for viewing biomedical computational fluid dynamics results and corresponding data within virtual and augmented reality environments.

John Venn, Christopher E Larkee, Guilherme J M Garcia, Vitaliy L Rayz, John F LaDisa

Abstract read
In one paragraph

Article in Frontiers in medical technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

John VennDepartment of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States.
Christopher E LarkeeOpus College of Engineering, Marquette University, Milwaukee, WI, United States.
Guilherme J M GarciaDepartment of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States.
Vitaliy L RayzDepartment of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States.
John F LaDisaDepartment of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States.

Funding

Mechanisms of morbidity after correcting aortic coarctations of varying severityR01HL142955 · NHLBI · MEDICAL COLLEGE OF WISCONSIN · PI John Frank LaDisa · 2018 to 2026
$3.2M
Quantifying altered hemodynamics in response to stenting for aortic coarctationR15HL096096 · NHLBI · MARQUETTE UNIVERSITY · PI LADISA, JOHN FRANK · 2009 to 2009
$228k
NHLBI NIH HHS R01 HL142955NHLBI NIH HHS R15 HL096096
6 · The paper itself

Abstract

Researchers conducting computational fluid dynamics (CFD) modeling can spend weeks obtaining imaging data, determining boundary conditions, running simulations and post-processing files. However, results are typically viewed on a 2D display and often at one point in time thus reducing the dynamic and inherently three-dimensional data to a static image. Results from different pathologic states or cases are rarely compared in real-time, and supplementary data are seldom included. Therefore, only a fraction of CFD results are typically studied in detail, and associations between mechanical stimuli and biological response may be overlooked. Virtual and augmented reality facilitate stereoscopic viewing that may foster extraction of more information from CFD results by taking advantage of improved depth cues, as well as custom content development and interactivity, all within an immersive approach. Our objective was to develop a straightforward, semi-automated workflow for enhanced viewing of CFD results and associated data in an immersive virtual environment (IVE). The workflow supports common CFD software and has been successfully completed by novice users in about an hour, demonstrating its ease of use. Moreover, its utility is demonstrated across clinical research areas and IVE platforms spanning a range of cost and development considerations. We are optimistic that this advancement, which decreases and simplifies the steps to facilitate more widespread use of immersive CFD viewing, will foster more efficient collaboration between engineers and clinicians. Initial clinical feedback is presented, and instructional videos, manuals, templates and sample data are provided online to facilitate adoption by the community.

Indexed as

Extended reality (XR)fluid structure interaction and CFDhemodynamicspatient-specific 3D modelsimulation - computers

Identifiers

PMID36908292
PMCPMC9996009

What Socratic 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 Socratic graph.