Revolutionizing Medical Imaging (ReImagine) through Ubiquitous, Low-Dose, Automated Computed Tomography Diagnostic Systems

想象一下，在这样一个世界里，每个人都可以以节省时间和安全的方式，定期、广泛地接受健康监测，而不必访问订阅量过大、访问和预约灵活性有限的集中式医疗中心。设想一种新的临床模式，其中早期诊断成为标准，即使在偏远地区、低收入人口和国际旅行中，这是因为无处不在的、模块化的、具有自动诊断和实时报告的高分辨率X射线成像系统；随着时间的推移，频繁的成像有助于对大量个人进行诊断(同时保持隐私)，基于人工智能(AI)的高级算法使用从人口中获取的这些匿名数据集来识别我们所知的转化疾病的预防性医学的极早期阶段。这是ReImagine将实现的2050年。我们将通过低剂量、高分辨率和廉价的计算机断层扫描(CT)扫描仪来革命性地使用X射线进行医学成像，其中高度创新的硬件和软件组件将并排开发，以实现自动化的一体化症状前诊断。我们的愿景将通过开发高灵敏度的X射线探测器来实现，该探测器使用可伸缩的卤化物钙钛矿(PVK)半导体-目前正在产生影响的破坏性光伏(PV)技术-用于相衬X射线成像，并结合人工智能驱动的图像重建、病变检测和分割算法。这将实现更快和更有效率的医疗保健服务，并通过极早发现疾病(例如，那些对未来大流行负有责任的人)和对肿瘤科患者的常规跟进(例如，癌症复发的早期发现)来防止疾病传播。为了实现这一极具挑战性的愿景-结合硬件、软件和最终用户应用方面的突破-我们独特地组建了一支来自剑桥大学、拉夫堡大学和莱斯特大学的世界领先的跨领域团队，与莱顿大学的学术合作伙伴以及通用电气医疗保健、Scintacor、Cheyney和材料实验室的行业合作伙伴一起，带来了涵盖材料合成和缩放、表征和建模、设备组装、探测器物理、数学、CT系统开发和临床放射学的综合专业知识。硬件将与软件和算法开发交织在一起，两者都以临床洞察力、行业和案例研究为指导，以确保适合最终用户。

Imagine a world in which every individual can be routinely and extensively health monitored, in a time-efficient and safe manner, without having to visit an oversubscribed, centralised medical centre with limited access and appointment flexibility. Imagine a new clinical paradigm where early diagnosis becomes the standard, even in remote areas, within low-income demographics and for international travel, due to ubiquitous, modular, high-resolution X-ray imaging systems with automated diagnosis and live reporting; where frequent imaging contributes to a large diagnostic portfolio of individuals over time (whilst maintaining privacy) and advanced artificial-intelligence (AI)-based algorithms use these anonymous data sets acquired across the population to identify extremely early stages of disease - transforming preventative medicine as we know it. This is the 2050 that ReImagine will enable. We will revolutionise the use of X-rays for medical imaging through low-dose, high-resolution and inexpensive computed tomography (CT) scanners, where highly innovative hardware and software components will be developed side-by-side to enable automated all-in-one pre-symptomatic diagnosis. Our vision will be enabled by developing highly sensitive X-ray detectors using scalable halide perovskite (PVK) semiconductors - materials currently making impact as disruptive photovoltaic (PV) technologies - for phase contrast X-ray imaging, in conjunction with AI-driven algorithms for image reconstruction, lesion detection and segmentation. This will realise quicker and more efficient healthcare delivery and prevent disease spread through extremely early detection of disease (e.g., those otherwise responsible for future pandemics) and for routine follow-up of oncology patients (e.g. early detection of cancer recurrence). To realise this extremely challenging vision - combining breakthroughs in hardware, software and end-user application - we have uniquely assembled a world-leading, cross-cutting team from the Universities of Cambridge, Loughborough and Leicester, together with academic partners at the University of Leiden and industry partners in GE Healthcare, Scintacor, Cheyney and Immaterials Labs, bringing combined expertise spanning materials synthesis and scaling, characterisation and modelling, device assembly, detector physics, mathematics, CT systems development, and clinical radiology. The hardware will be interweaved with the software and algorithm development, with both guided by clinical insight, industry and case studies to ensure fit for end users.