Quality and Safety Monitoring of Clinical Computed Tomography Practice

摘要-50%的美国人受到的辐射来自医学成像，一半的人 这些数据来自每年进行的8000多万次计算机断层扫描。这一重大用途 引起了人们对使用成本、不适当的应用以及相关辐射的显著担忧 风险。最近的一项医疗保险报告称，全国数百家医院已经不必要地扫描了他们的 患者在同一天两次。不必要的重复扫描使患者暴露在额外的辐射中，同时增加 费用，减少报销，并增加提供者的责任。因此，立法和监管 组织鼓励并强制更严格地监督医学成像的使用及其相关 辐射。与更好地管理成像风险的任务同时进行的是确保其价值： 当前CT实践的典型但最低调的支柱是CT在治疗疾病和治疗方面的高价值 各个年龄段的人都会受伤。为了确保CT检查的这种好处，需要在以下几个方面仔细平衡 图像质量和辐射安全。质量差、剂量过低的检查对患者的护理是有害的 患者，而超过必要的辐射剂量的检查可能会破坏其安全性。因此，正确的CT 成像需要针对每个患者的综合质量和剂量监测计划 为正确了解、管理和减轻辐射风险奠定了基础。不幸的是，目前还没有这样的 市面上可同时监测CT辐射剂量及其对应剂量的软件 图像质量。 此快速通道项目的目标是开发第一个基于软件即服务(SaaS)的性能 可同时跟踪辐射剂量和图像质量的监测平台。该平台旨在提供 通过同时考虑患者安全和成像来提高CT性能的基本数据和洞察力 质量同步。具体地说，该项目将开发一种产品，提供1)强大的多基础设施 连接和收集临床CT质量和剂量相关数据的工作流程；2)一套针对患者的CT 辐射剂量和图像质量评估算法；3)任务管理器的实现，以链接和 自动计算用于CT性能评估的剂量和图像质量；4)综合SQL- 用于结构化和非结构化质量和剂量相关数据存储的NoSQL数据库系统；以及5)a 基于Web的仪表板，用于交互式且易于使用的数据分析和可视化。开发利用 机器学习方法，以设计健壮和可扩展的技术来提取有意义的知识 从成百上千的患者图像中。该系统量化了以价值为基础的实践的价值。它 作为一种基本工具，最大限度地减少实践中质量和剂量的变异性，以确保一致性 使用CT技术，并确保成像辐射剂量和质量水平与预期值匹配。这个 该系统将在医疗机构进行Beta测试，为有效的商业化铺平道路。

Abstract – Fifty percent of radiation exposure to the United States population is from medical imaging, half of which come from over 80 million computed tomography (CT) scans performed every year. This significant use has raised notable concerns regarding utilization costs, inappropriate applications, and the associated radiation risk. A recent Medicare reports hundreds of hospitals across the country have needlessly scanned their patients twice on the same day. Unnecessary repeated scans expose patients to extra radiation while increase expense, decrease reimbursement, and increase liability for the providers. Thus, the legislative and regulatory organizations have encouraged and mandated stricter oversight of medical imaging usage and its associated radiation. Concurrent to the mandate to better manage imaging risk is to ensure its value: One of the quintessential but most understated pillars of current CT practice is CT’s high value in caring for illness and injury across all ages. To ensure this benefit of CT examinations, there needs to be a careful balance between image quality and radiation safety. A poor quality, overly low dose exam is a disservice to the care of the patient while an exam with more radiation dose than necessary can undermine its safety. Therefore, proper CT imaging requires a comprehensive combined quality and dose monitoring program on a patient-by-patient basis to properly understand, manage, and mitigate radiation risk. Unfortunately, currently there is no such software available in the market that can simultaneously monitor CT radiation dose and its corresponding image quality. The objective of this fast-track project is to develop a first Software as a Service (SaaS)-based performance monitoring platform to track radiation dose and image quality concurrently. The platform aims to provide essential data and insight to improve CT performance through considering both patient safety and imaging quality simultaneously. Specifically, the project will develop a product that offers 1) a robust multi-infrastructure workflow to connect and collect clinical CT quality- and dose-relevant data; 2) a suite of patient-specific CT radiation dose and image quality assessment algorithms; 3) an implementation of a task manager to chain and automate dose and image quality calculations towards CT performance assessment; 4) a combined SQL- NoSQL database system for structured and un-structured quality- and dose-relevant data storage; and 5) a web-based dashboard for interactive and easy-to-use data analysis and visualization. The development utilizes machine-learning methodologies to devise robust and scalable techniques for extracting meaningful knowledge from hundreds of thousands of patient images. The system quantifies value for a value-based practice. It serves as an essential tool to minimize variability in quality and dose across a practice, to ensure consistent use of CT technology, and to ensure imaging radiation dose and quality levels match expected values. The system will be beta tested at healthcare facilities paving the way toward effective commercialization.