发表机构
Charles Sturt University; Western NSW Local Health District; The University of Queensland（查尔斯特大学; 新南威尔士州西部地方卫生区; 昆士兰大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本综述评估移动CT、远程医疗和监管授权AI在偏远地区的应用现状，指出三者各自成熟但整合不足，并强调未来需进行前瞻性多中心验证。
AI 中文摘要
计算机断层扫描（CT）在临床工作流程中发挥着重要作用，以改善患者预后。然而，获得CT成像和专家解读的机会仍然有限，特别是在农村、区域、偏远（RRR）以及其他资源受限的环境中。近年来，移动CT、远程医疗和人工智能（AI）的进展为将先进成像服务扩展到RRR环境中的人群提供了机会。本综述考察了：1）部署在卡车、拖车、救护车和其他移动平台上的移动CT系统；2）支持基于CT的医疗保健的远程医疗技术；以及3）已获得监管授权或目前在临床实践中部署的用于CT的AI。应用在四个临床功能方面进行评估：筛查与诊断、患者监测、风险预测以及干预或治疗决策支持。本综述涵盖神经、胸部、心血管、腹部、肿瘤、肌肉骨骼和介入成像，特别关注卒中、癌症和其他图像引导治疗。其他因素如监管状态、部署状态和估计的技术就绪水平（TRL）也进行了比较。当前证据表明，移动CT、远程医疗和用于常规CT的AI各自相对成熟，但这些技术的完全整合在临床环境中的部署和验证仍然较少。主要障碍包括监管差异、域偏移、连接要求、成本、工作流程整合、网络安全以及患者层面获益证据有限。未来研究应优先在现实世界和医疗服务不足的临床环境中对整合CT系统进行前瞻性、多中心评估。
英文摘要
Computed tomography (CT) plays an essential role in clinical workflow to improve patient outcomes. However, access to CT imaging and specialist interpretation remains limited, particularly in rural, regional, remote (RRR), and other resource-limited settings. Recent advances in mobile CT, telehealth, and artificial intelligence (AI) provide opportunities to extend advanced imaging services to populations in RRR settings. This review examines: 1) mobile CT systems deployed in trucks, trailers, ambulances, and other mobile platforms; 2) telehealth technologies supporting CT-based healthcare; and 3) AI for CT that has received regulatory authorisation or is currently deployed in clinical practice. Applications are evaluated across four clinical functions: screening and diagnosis, patient monitoring, risk prediction, and intervention or therapeutic decision support. The review covers neurological, thoracic, cardiovascular, abdominal, oncological, musculoskeletal, and interventional imaging, with particular attention to stroke, cancer, and other image-guided treatment. Other factors such as regulatory status, deployment status, and estimated technology readiness (TRL) level are compared. Current evidence indicates that mobile CT, telehealth, and AI for conventional CT are individually relatively mature, but fully integration of these technologies remains less widely deployed and validated in the clinical settings. Key barriers include regulatory variation, domain shift, connectivity requirements, cost, workflow integration, cybersecurity, and limited evidence of patient-level benefit. Future research should prioritise prospective, multicentre evaluation of integrated CT systems in real-world and underserved clinical settings.
Comments18 pages, 3 figures, 4 tables
