Evidence map›Paper›PMID 36354877›Full record

ArticleJournal of imaging2022

Evaluation of a Linear Measurement Tool in Virtual Reality for Assessment of Multimodality Imaging Data-A Phantom Study.

Natasha Stephenson, Kuberan Pushparajah, Gavin Wheeler, Shujie Deng, Julia A Schnabel, John M Simpson

Abstract read
In one paragraph

Article in Journal of imaging, 2022. 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

6 authors.

Natasha StephensonSchool of Biomedical Engineering and Imaging Sciences, King's College London, London WC2R 2LS, UK.ORCID 0000-0002-5278-5271
Kuberan PushparajahSchool of Biomedical Engineering and Imaging Sciences, King's College London, London WC2R 2LS, UK.
Gavin WheelerSchool of Biomedical Engineering and Imaging Sciences, King's College London, London WC2R 2LS, UK.
Shujie DengSchool of Biomedical Engineering and Imaging Sciences, King's College London, London WC2R 2LS, UK.
Julia A SchnabelSchool of Biomedical Engineering and Imaging Sciences, King's College London, London WC2R 2LS, UK.
John M SimpsonDepartment of Congenital Heart Disease, Evelina Children's Hospital, London SE1 7EH, UK.

Funding

British Heart Foundation TA/F/20/210021Evelina London Children's Charity N/ANational Institute for Health Research II-LA-0716-20001
6 · The paper itself

Abstract

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.

Indexed as

3D measurement toolscomputed tomographyechocardiographymagnetic resonance imagingmeasurement accuracypreoperative imagingvirtual reality

Identifiers

PMID36354877
PMCPMC9696690

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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.