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Stephenson N, Pushparajah K, Wheeler G, Deng S, Schnabel JA, Simpson JM. Extended reality for procedural planning and guidance in structural heart disease - a review of the state-of-the-art. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2023:10.1007/s10554-023-02823-z. [PMID: 37103667 DOI: 10.1007/s10554-023-02823-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 02/22/2023] [Indexed: 04/28/2023]
Abstract
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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Affiliation(s)
- Natasha Stephenson
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- Department of Congenital Heart Disease, Evelina Children's Hospital, London, UK.
- St Thomas' Hospital, 3rd Floor, Lambeth Wing, SE1 7EH, London, UK.
| | - Kuberan Pushparajah
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Congenital Heart Disease, Evelina Children's Hospital, London, UK
| | - Gavin Wheeler
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Shujie Deng
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Julia A Schnabel
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Technical University of Munich, Munich, Germany
- Institute of Machine Learning in Biomedical Imaging, Helmholtz Center Munich, Munich, Germany
| | - John M Simpson
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Congenital Heart Disease, Evelina Children's Hospital, London, UK
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Stephenson N, Pushparajah K, Wheeler G, Deng S, Schnabel JA, Simpson JM. Evaluation of a Linear Measurement Tool in Virtual Reality for Assessment of Multimodality Imaging Data-A Phantom Study. J Imaging 2022; 8:jimaging8110304. [PMID: 36354877 PMCID: PMC9696690 DOI: 10.3390/jimaging8110304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/28/2022] [Accepted: 11/03/2022] [Indexed: 11/09/2022] Open
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.
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Affiliation(s)
- Natasha Stephenson
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
- Department of Congenital Heart Disease, Evelina Children’s Hospital, London SE1 7EH, UK
- Correspondence:
| | - Kuberan Pushparajah
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
- Department of Congenital Heart Disease, Evelina Children’s Hospital, London SE1 7EH, UK
| | - Gavin Wheeler
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
| | - Shujie Deng
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
| | - Julia A. Schnabel
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
- Faculty of Informatics, Technical University of Munich, 80333 Munich, Germany
- Institute of Machine Learning in Biomedical Engineering, Helmholtz Centre Munich, 85764 Munich, Germany
| | - John M. Simpson
- Department of Congenital Heart Disease, Evelina Children’s Hospital, London SE1 7EH, UK
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An impact of three dimensional techniques in virtual reality. Int J Health Sci (Qassim) 2022. [DOI: 10.53730/ijhs.v6ns4.6481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Three dimensional (3D) imaging play a prominent role in the diagnosis, treatment planning, and post-therapeutic monitoring of patients with Rheumatic Heart Disease (RHD) or mitral valve disease. More interactive and realistic medical experiences take an advantage of advanced visualization techniques like augmented, mixed, and virtual reality to analyze the 3D models. Further, 3D printed mitral valve model is being used in medical field. All these technologies improve the understanding of the complex morphologies of mitral valve disease. Real-time 3D Echocardiography has attracted much more attention in medical researches because it provides interactive feedback to acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary for intraoperative ultrasound examinations. In this article, three dimensional techniques and its impacts in mitral valve disease are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms with clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail.
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Deng S, Wheeler G, Toussaint N, Munroe L, Bhattacharya S, Sajith G, Lin E, Singh E, Chu KYK, Kabir S, Pushparajah K, Simpson JM, Schnabel JA, Gomez A. A Virtual Reality System for Improved Image-Based Planning of Complex Cardiac Procedures. J Imaging 2021; 7:151. [PMID: 34460787 PMCID: PMC8404926 DOI: 10.3390/jimaging7080151] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 12/03/2022] Open
Abstract
The intricate nature of congenital heart disease requires understanding of the complex, patient-specific three-dimensional dynamic anatomy of the heart, from imaging data such as three-dimensional echocardiography for successful outcomes from surgical and interventional procedures. Conventional clinical systems use flat screens, and therefore, display remains two-dimensional, which undermines the full understanding of the three-dimensional dynamic data. Additionally, the control of three-dimensional visualisation with two-dimensional tools is often difficult, so used only by imaging specialists. In this paper, we describe a virtual reality system for immersive surgery planning using dynamic three-dimensional echocardiography, which enables fast prototyping for visualisation such as volume rendering, multiplanar reformatting, flow visualisation and advanced interaction such as three-dimensional cropping, windowing, measurement, haptic feedback, automatic image orientation and multiuser interactions. The available features were evaluated by imaging and nonimaging clinicians, showing that the virtual reality system can help improve the understanding and communication of three-dimensional echocardiography imaging and potentially benefit congenital heart disease treatment.
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Affiliation(s)
- Shujie Deng
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Gavin Wheeler
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Nicolas Toussaint
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Lindsay Munroe
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Suryava Bhattacharya
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Gina Sajith
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Ei Lin
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Eeshar Singh
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Ka Yee Kelly Chu
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
| | - Saleha Kabir
- Department of Congenital Heart Disease, Evelina London Children’s Hospital, Guy’s and St Thomas’ National Health Service Foundation Trust, London SE1 7EH, UK;
| | - Kuberan Pushparajah
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
- Department of Congenital Heart Disease, Evelina London Children’s Hospital, Guy’s and St Thomas’ National Health Service Foundation Trust, London SE1 7EH, UK;
| | - John M. Simpson
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
- Department of Congenital Heart Disease, Evelina London Children’s Hospital, Guy’s and St Thomas’ National Health Service Foundation Trust, London SE1 7EH, UK;
| | - Julia A. Schnabel
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
- Department of Informatics, Technische Universität München, 85748 Garching, Germany
- Helmholtz Zentrum München—German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Alberto Gomez
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EU, UK; (S.D.); (G.W.); (N.T.); (L.M.); (S.B.); (G.S.); (E.L.); (E.S.); (K.Y.K.C.); (K.P.); (J.M.S.); (J.A.S.)
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