Evidence map›Paper›PMID 39985723›Full record

ArticleEuropean radiology experimental2025

3D cinematic reconstructions of cardiovascular CT presented in augmented reality: subjective assessment of clinical feasibility and potential use cases.

Benjamin Böttcher, Marly van Assen, Roberto Fari, Philipp L von Knebel Doeberitz, Gabrielle Gershon, Felix G Meinel, Carlo N De Cecco

Abstract read
In one paragraph

Article in European radiology experimental, 2025. 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
–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.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Development of an optically emulated computed tomography scanner for college education.Visual computing for industry, biomedicine, and art · 2026
    Article
  6. Review
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

7 authors.

Benjamin BöttcherTranslational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, Atlanta, USA.
Marly van AssenTranslational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, Atlanta, USA.
Roberto FariTranslational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, Atlanta, USA.
Philipp L von Knebel DoeberitzTranslational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, Atlanta, USA.
Gabrielle GershonTranslational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, Atlanta, USA.
Felix G MeinelInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Centre Rostock, Rostock, Germany.
Carlo N De CeccoTranslational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, Atlanta, USA. carlo.dececco@emory.edu.ORCID http://orcid.org/0000-0002-2956-3101

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Augmented reality (AR) is a new technique enabling interaction with three-dimensional (3D) holograms of cinematic rendering (CR) reconstructions. Research in this field is in its very early steps, and data is scarce. We evaluated image quality, usability, and potential applications of AR in cardiovascular image datasets. Ten CR reconstructions of cardiovascular computed tomography (CT) datasets with complex anatomical abnormalities were presented to six radiologists and three cardiologists first on diagnostic screens and subsequently in AR. Subjective image quality and user experience were rated on 5-point Likert scales to assess usability and potential applications of AR. CR of CT datasets covering multiple images series of the same exam with differing kernels was performed in 143 ± 31 s (mean ± standard deviation); reconstruction of single CT image series took 84 ± 30 s. Mean subjective image quality was excellent, and observers showed high endorsement of the intuitive usability of the AR device and improvement of anatomical comprehensibility. AR devices were expected to have the greatest impact on patient and student education as well as multidisciplinary discussions, with less potential in clinical care. Clinical testing and preclinical implementation of AR seem feasible due to reasonable computation times and intuitive usability even for first-time users. RELEVANCE STATEMENT: The presentation of 3D cinematic rendering in augmented reality provides excellent image quality, facilitating the comprehension of anatomical structures in CT datasets. Concurrently, reasonable computation times and the intuitive usability of augmented reality devices make preclinical implementation and clinical testing feasible. KEY POINTS: 3D cinematic reconstructions presented in augmented reality improve the anatomical comprehensibility of chest CT scans. Augmented reality devices are expected to be highly beneficial in educational settings and multidisciplinary discussions. Usability and computation times are feasible for initial preclinical use cases.

Indexed as

Augmented RealityImaging, Three-DimensionalTomography, X-Ray ComputedFeasibility StudiesHumansAugmented realityCardiovascular systemEducation (medical)Imaging (three-dimensional)Tomography (x-ray computed)

Identifiers

PMID39985723
PMCPMC11846813

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Registered trials

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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.