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Real-time Digital Twin Assisted Surgery

Real-time Digital Twin Assisted Surgery
实时数字孪生辅助手术
批准号:
EP/X033686/1
负责人:
Will Wenmiao Shu
金额:
$508.35万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
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英文摘要
Surgery is a critical treatment delivered by NHS. Pre-COVID19 data (2004-2014) suggest a 27% increase in surgeries in England (>10 million operations performed). Despite >1.5 million cancelled or postponed surgeries in 2020 due to COVID19 (~33.6% reduction in England and Wales) and rocketed waiting lists for cancer surgery likely resulting in more deaths, tumour resection surgeries have recently resumed and remain high (e.g. ~51% of diagnoses received a kidney tumour resection in 2021). The total UK economic burden of surgery was ~£54.6 billion between 2009-2014 (£10.9 bn pa), amounting to 9.4% of the total NHS budget (£117 billion, 2013-2014). There is a clear clinical need for minimising surgical operations, healthcare costs, patient waiting lists, and associated patient complications.To address this need, we aim to digitally transform future surgery, particularly for cancer, by creating a ground-breaking real-time digital twin assisted surgery (DTAS) technology. The patient is at the core of this technology, with significant and measurable benefits for their quality of life and healthcare. DTAS can be applied to several types of surgery (open, minimally invasive, or robotic surgery), for high precision tumour removal even in a partial organ resection. A parallel goal is to revolutionise surgical training, offering a new paradigm of patient-centred personalised surgical rehearsal. This project is timely and will be delivered by an internationally competitive, highly experienced multidisciplinary team, capable of delivering our vision. Our team covers several disciplines, including the lived experience from patients; health technologies; bioengineering; digital twin (DT) technology; artificial intelligence (AI); mathematical science; numerical simulation.
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