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Stephenson, N.* ; Pushparajah, K.* ; Wheeler, G.* ; Deng, S.* ; Schnabel, J.A. ; Simpson, J.M.*

Extended reality for procedural planning and guidance in structural heart disease - a review of the state-of-the-art.

Int. J. Cardiovasc. Imaging 39, 1405-1419 (2023)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Extended reality (XR), which encompasses virtual, augmented and mixed reality, is an emerging medical imaging display platform which enables intuitive and immersive interaction in a three-dimensional space. This technology holds the potential to enhance understanding of complex spatial relationships when planning and guiding cardiac procedures in congenital and structural heart disease moving beyond conventional 2D and 3D image displays. A systematic review of the literature demonstrates a rapid increase in publications describing adoption of this technology. At least 33 XR systems have been described, with many demonstrating proof of concept, but with no specific mention of regulatory approval including some prospective studies. Validation remains limited, and true clinical benefit difficult to measure. This review describes and critically appraises the range of XR technologies and its applications for procedural planning and guidance in structural heart disease while discussing the challenges that need to be overcome in future studies to achieve safe and effective clinical adoption.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Catheter Planning ; Extended Reality ; Procedure Guidance ; Structural Heart Disease ; Surgical Planning ; Virtual Reality; Virtual-reality; 3-dimensional Echocardiography; Augmented Reality; Beating-heart; Visualization; Display; Models; Feasibility; Navigation; Closure
Sprache englisch
Veröffentlichungsjahr 2023
HGF-Berichtsjahr 2023
ISSN (print) / ISBN 1569-5794
e-ISSN 1573-0743
Zeitschrift International Journal of Cardiovascular Imaging
Quellenangaben Band: 39, Heft: 7, Seiten: 1405-1419 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Dordrecht [u.a.]
Begutachtungsstatus Peer reviewed
Institut(e) Institute for Machine Learning in Biomed Imaging (IML)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-507100-001
DOI 10.1007/s10554-023-02823-z
WOS ID 000975742200001
Scopus ID 85153745901
PubMed ID 37103667
Erfassungsdatum 2023-10-06
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