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

Evaluation of a linear measurement tool in virtual reality for assessment of multimodality imaging data-A phantom study.

J. Imaging 8:304 (2022)
Verlagsversion DOI
Open Access Gold
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This study aimed to evaluate the accuracy and reliability of a virtual reality (VR) system line measurement tool using phantom data across three cardiac imaging modalities: three-dimensional echocardiography (3DE), computed tomography (CT) and magnetic resonance imaging (MRI). The same phantoms were also measured using industry-standard image visualisation software packages. Two participants performed blinded measurements on volume-rendered images of standard phantoms both in VR and on an industry-standard image visualisation platform. The intra- and interrater reliability of the VR measurement method was evaluated by intraclass correlation coefficient (ICC) and coefficient of variance (CV). Measurement accuracy was analysed using Bland-Altman and mean absolute percentage error (MAPE). VR measurements showed good intra- and interobserver reliability (ICC ≥ 0.99, p < 0.05; CV < 10%) across all imaging modalities. MAPE for VR measurements compared to ground truth were 1.6%, 1.6% and 7.7% in MRI, CT and 3DE datasets, respectively. Bland-Altman analysis demonstrated no systematic measurement bias in CT or MRI data in VR compared to ground truth. A small bias toward smaller measurements in 3DE data was seen in both VR (mean -0.52 mm [-0.16 to -0.88]) and the standard platform (mean -0.22 mm [-0.03 to -0.40]) when compared to ground truth. Limits of agreement for measurements across all modalities were similar in VR and standard software. This study has shown good measurement accuracy and reliability of VR in CT and MRI data with a higher MAPE for 3DE data. This may relate to the overall smaller measurement dimensions within the 3DE phantom. Further evaluation is required of all modalities for assessment of measurements <10 mm.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter 3d Measurement Tools ; Computed Tomography ; Echocardiography ; Magnetic Resonance Imaging ; Measurement Accuracy ; Preoperative Imaging ; Virtual Reality
ISSN (print) / ISBN 2313-433X
e-ISSN 2313-433X
Zeitschrift Journal of Imaging
Quellenangaben Band: 8, Heft: 11, Seiten: , Artikelnummer: 304 Supplement: ,
Verlag MDPI
Begutachtungsstatus Peer reviewed
Institut(e) Institute for Machine Learning in Biomed Imaging (IML)
Förderungen National Institute for Health Research
Evelina London Children's Charity
British Heart Foundation