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Li Y, Gunasekeran DV, RaviChandran N, Tan TF, Ong JCL, Thirunavukarasu AJ, Polascik BW, Habash R, Khaderi K, Ting DSW. The next generation of healthcare ecosystem in the metaverse. Biomed J 2024; 47:100679. [PMID: 38048990 PMCID: PMC11245972 DOI: 10.1016/j.bj.2023.100679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 11/04/2023] [Accepted: 11/19/2023] [Indexed: 12/06/2023] Open
Abstract
The Metaverse has gained wide attention for being the application interface for the next generation of Internet. The potential of the Metaverse is growing, as Web 3·0 development and adoption continues to advance medicine and healthcare. We define the next generation of interoperable healthcare ecosystem in the Metaverse. We examine the existing literature regarding the Metaverse, explain the technology framework to deliver an immersive experience, along with a technical comparison of legacy and novel Metaverse platforms that are publicly released and in active use. The potential applications of different features of the Metaverse, including avatar-based meetings, immersive simulations, and social interactions are examined with different roles from patients to healthcare providers and healthcare organizations. Present challenges in the development of the Metaverse healthcare ecosystem are discussed, along with potential solutions including capabilities requiring technological innovation, use cases requiring regulatory supervision, and sound governance. This proposed concept and framework of the Metaverse could potentially redefine the traditional healthcare system and enhance digital transformation in healthcare. Similar to AI technology at the beginning of this decade, real-world development and implementation of these capabilities are relatively nascent. Further pragmatic research is needed for the development of an interoperable healthcare ecosystem in the Metaverse.
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Affiliation(s)
- Yong Li
- Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore; The Ophthalmology & Visual Sciences Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
| | - Dinesh Visva Gunasekeran
- Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore; The Ophthalmology & Visual Sciences Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Ting Fang Tan
- Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore
| | | | | | - Bryce W Polascik
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Ranya Habash
- Bascom Palmer Eye Institute, University of Miami, Florida, USA
| | - Khizer Khaderi
- Department of Ophthalmology, Stanford University, California, USA
| | - Daniel S W Ting
- Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore; The Ophthalmology & Visual Sciences Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore; Department of Ophthalmology, Stanford University, California, USA.
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Soriero D, Batistotti P, Malinaric R, Pertile D, Massobrio A, Epis L, Sperotto B, Penza V, Mattos LS, Sartini M, Cristina ML, Nencioni A, Scabini S. Efficacy of High-Resolution Preoperative 3D Reconstructions for Lesion Localization in Oncological Colorectal Surgery—First Pilot Study. Healthcare (Basel) 2022; 10:healthcare10050900. [PMID: 35628036 PMCID: PMC9141148 DOI: 10.3390/healthcare10050900] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/20/2022] [Accepted: 05/11/2022] [Indexed: 02/01/2023] Open
Abstract
When planning an operation, surgeons usually rely on traditional 2D imaging. Moreover, colon neoplastic lesions are not always easy to locate macroscopically, even during surgery. A 3D virtual model may allow surgeons to localize lesions with more precision and to better visualize the anatomy. In this study, we primary analyzed and discussed the clinical impact of using such 3D models in colorectal surgery. This is a monocentric prospective observational pilot study that includes 14 consecutive patients who presented colorectal lesions with indication for surgical therapy. A staging computed tomography (CT)/magnetic resonance imaging (MRI) scan and a colonoscopy were performed on each patient. The information gained from them was provided to obtain a 3D rendering. The 2D images were shown to the surgeon performing the operation, while the 3D reconstructions were shown to a second surgeon. Both of them had to locate the lesion and describe which procedure they would have performed; we then compared their answers with one another and with the intraoperative and histopathological findings. The lesion localizations based on the 3D models were accurate in 100% of cases, in contrast to conventional 2D CT scans, which could not detect the lesion in two patients (in these cases, lesion localization was based on colonoscopy). The 3D model reconstruction allowed an excellent concordance correlation between the estimated and the actual location of the lesion, allowing the surgeon to correctly plan the procedure with excellent results. Larger clinical studies are certainly required.
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Affiliation(s)
- Domenico Soriero
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
| | - Paola Batistotti
- Department of Integrated Surgical and Diagnostic Sciences, University of Genoa, 16132 Genoa, Italy;
| | - Rafaela Malinaric
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
- Urological Clinical Unit, San Martino Hospital, 16132 Genoa, Italy
| | - Davide Pertile
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
| | - Andrea Massobrio
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
| | - Lorenzo Epis
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
| | - Beatrice Sperotto
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
| | - Veronica Penza
- Biomedical Robotics Lab, Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genoa, Italy; (V.P.); (L.S.M.)
| | - Leonardo S. Mattos
- Biomedical Robotics Lab, Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genoa, Italy; (V.P.); (L.S.M.)
| | - Marina Sartini
- Department of Health Sciences, University of Genoa, Via Pastore 1, 16132 Genoa, Italy
- Operating Unit Hospital Hygiene, Galliera Hospital, Mura delle Cappuccine 14, 16128 Genoa, Italy
- Correspondence: (M.S.); (M.L.C.)
| | - Maria Luisa Cristina
- Department of Health Sciences, University of Genoa, Via Pastore 1, 16132 Genoa, Italy
- Operating Unit Hospital Hygiene, Galliera Hospital, Mura delle Cappuccine 14, 16128 Genoa, Italy
- Correspondence: (M.S.); (M.L.C.)
| | - Alessio Nencioni
- Section of Geriatrics, Department of Internal Medicine and Medical Specialties (DIMI), University of Genoa, 16132 Genoa, Italy;
- Gerontology and Geriatrics, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
| | - Stefano Scabini
- General and Oncologic Surgery, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (D.S.); (R.M.); (D.P.); (A.M.); (L.E.); (B.S.); (S.S.)
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Cheng Z, Lindberg Schwaner K, Dall'Alba D, Fiorini P, Savarimuthu TR. An electrical bioimpedance scanning system for subsurface tissue detection in Robot Assisted Minimally Invasive Surgery. IEEE Trans Biomed Eng 2021; 69:209-219. [PMID: 34156935 DOI: 10.1109/tbme.2021.3091326] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
In Robot Assisted Minimally Invasive Surgery, discriminating critical subsurface structures is essential to make the surgical procedure safer and more efficient. In this paper, a novel robot assisted electrical bio-impedance scanning (RAEIS) system is developed and validated using a series of experiments. The proposed system constructs a tri-polar sensing configuration for tissue homogeneity inspection. Specifically, two robotic forceps are used as electrodes for applying electric current and measuring reciprocal voltages relative to a ground electrode which is placed distal from the measuring site. Compared to the other existing electrical bioimpedance sensing technology, the proposed system is able to use miniaturized electrodes to measure a site flexibly with enhanced subsurfacial detection capability. In this paper, we present the concept, the modeling of the sensing method, the hardware design, and the system calibration. Subsequently, a series of experiments are conducted for system evaluation including finite element simulation, saline solution bath experiments and experiments based on ex vivo animal tissues. The experimental results demonstrate that the proposed system can measure the resistivity of the material with high accuracy, and detect a subsurface non-homogeneous object with 100% success rate. The proposed parameters estimation algorithm is able to approximate the resistivity and the depth of the subsurface object effectively with one fast scanning.
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