Quality and Safety Monitoring of Clinical Computed Tomography Practice

临床计算机断层扫描实践的质量和安全监测

• 批准号: 10253256
• 负责人: Francesco Ria
• 金额: $ 24.97万
• 依托单位: METIS HEALTH ANALYTICS, LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-18 至 2022-09-17
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10253256
• 关键词: Address; Affect; Age; Algorithms; Architecture; Caring; Clinical; Collection; Computer software; Contrast Media; Country; Data; Data Analyses; Data Storage and Retrieval; Database Management Systems; Dental; Development; Devices; Diagnostic radiologic examination; Disease; Dose; Ensure; Equilibrium; Equipment; Exposure to; Fluoroscopy; Foundations; Goals; Health; Health Technology; Health care facility; Health system; Healthcare; Hospitals; Human; Image; Individual; Information Systems; Infrastructure; Injury; Insurance; Intuition; Knowledge; Mammography; Manufacturer Name; Medical Imaging; Medicare; Modeling; Monitor; Nuclear; Online Systems; Outcome; Patient Care; Patient imaging; Patients; Performance; Phase; Phase Transition; Population; Protocols documentation; Provider; Quality of Care; Radiation; Radiation Dose Unit; Radiation exposure; Radiology Specialty; Reporting; Research; Risk; Roentgen Rays; Safety; Scanning; Small Business Innovation Research Grant; Standardization; Structure; System; Techniques; Technology; Testing; United States; Universities; X-Ray Computed Tomography; base; beneficiary; clinical imaging; clinical implementation; clinical practice; commercialization; computer infrastructure; cost; dashboard; data exchange; data management; data visualization; design; graphical user interface; imaging modality; imaging system; improved; informatics infrastructure; innovation; insight; interoperability; machine learning method; operation; patient safety; profiles in patients; programs; prototype; radiation risk; repaired; software as a service; tool

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. 1

摘要 - 美国人群的辐射暴露的百分之五十是来自医学成像，一半 每年都有超过8000万个计算机断层扫描（CT）扫描。这种重要用途 对利用成本，不适当的应用和相关辐射提出了显着的担忧 风险。最近的医疗保险报道，全国数百家医院需要扫描他们的 患者在同一天两次。不必要的重复扫描使患者在增加的同时暴露于额外的辐射 费用，减少报销并增加提供者的责任。这是立法和监管 组织鼓励和强制要求严格对医学成像使用及其相关的监督 辐射。同时授权更好地管理成像风险的是确保其价值：其中之一 当前CT实践的典型但最低调的支柱是CT照顾疾病和 各个年龄段的伤害。为了确保CT考试的好处，需要在 图像质量和辐射安全。质量差，过度低剂量考试是对护理的损害 患者的辐射剂量超过必要的检查可能会破坏其安全性。因此，适当的ct 成像需要在患者的患者中进行全面的质量和剂量监测计划 依据适当理解，管理和减轻辐射风险。不幸的是，目前没有这样的 市场上可用的软件，可以轻松监视CT辐射剂量及其相应的软件 图像质量。 这个快速轨道项目的目的是开发第一个软件作为服务（SaaS）的性能 监视平台以同时跟踪辐射剂量和图像质量。该平台旨在提供 通过考虑患者安全和成像，可以提高CT性能的基本数据和见解 质量简单。特别是，该项目将开发一个提供1）强大的多基础结构的产品 连接和收集临床CT质量和剂量相关数据的工作流程； 2）一套患者特异性的CT 辐射剂量和图像质量评估算法； 3）实施任务经理到链和 自动化剂量和图像质量计算针对CT性能评估； 4）组合的SQL- NOSQL数据库系统，用于结构化和非结构化质量和剂量 - 相关数据存储；和5）a 基于Web的仪表板，用于交互式和易于使用的数据分析和可视化。开发利用 机器学习方法是设计出强大而可扩展的技术来提取有意义的知识的方法 来自数十万的患者图像。该系统量化基于价值的实践的价值。它 是最大程度地降低质量变异性和剂量的重要工具，以确保一致 使用CT技术，并确保成像辐射剂量和质量水平与预期值相匹配。 系统将在医疗机构进行Beta测试，为有效的商业化铺平道路。 1