Novel WEB Decision Support System for cardiac image interpretation and reporting

用于心脏图像解释和报告的新型 WEB 决策支持系统

• 批准号: 8427296
• 负责人: ERNEST V GARCIA
• 金额: $ 103.02万
• 依托单位: SYNTERMED, INC,
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-02-07 至 2015-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8427296
• 关键词: Accounting; Aging; Algorithms; Beds; Cardiac; Cardiology; Caring; Charge; Client; Clinical; Computer software; Coronary heart disease; Data; Databases; Decision Support Systems; Development; Diagnosis; Diagnostic; Electrocardiogram; Environment; Evaluation; Fees; Generations; Goals; Healthcare; Heart; Image; Internet; Ischemia; Knowledge; Learning; Left; Left ventricular structure; Licensing; Life; Link; Literature; Manufacturer Name; Medical; Methodology; Myocardial; Myocardial perfusion; Nomenclature; Nuclear; Nuclear Structure; Online Systems; Patients; Perfusion; Phase; Physicians; Probability; Process; Production; PubMed; Regional Perfusion; Reporting; Research; Research Infrastructure; Rest; Risk Factors; Running; Sales; Software Tools; Stress; Structure; System; Testing; Time; Update; Ventricular; Work; abstracting; base; clinical risk; cost; design; diagnostic accuracy; follow-up; impression; improved; innovation; instrumentation; knowledge base; novel; outcome forecast; prognostic; programs; public health relevance; reconstruction; single photon emission computed tomography; software development; tool

DESCRIPTION (provided by applicant): Today's cardiac imaging field requires diagnosticians to master an ever-expanding knowledge base (KB) while the time to master this knowledge, apply it to specific tasks and reimbursement are steadily shrinking. These constraints pose a serious healthcare problem that inevitably leads to physician's errors. Thus new tools are required to assist physicians to timely apply comprehensive, up-to-date objective knowledge and the available patient data to specific clinical problems. The long-term objective of our Fast-Track proposal is to improve the care of cardiac patients and reduce the cost of cardiac image interpretation by developing new tools for a WEB-accessible cardiac toolbox that provides decision support to increase the accuracy of detecting coronary heart disease (CHD). Specifically, we propose a WEB-based system where acquired ECG-gated myocardial perfusion SPECT (MPS) raw images are uploaded to be automatically reconstructed and analyzed to extract regional quantitative parameters of myocardial perfusion and function. These parameters are converted to certainty factors of abnormality and submitted to an imaging decision support system (DSS) that is continuously updated with the latest scientific/clinical knowledge to reach an impression of the patient's heart status. These conclusions reached by the DSS and justifications for each conclusion are used to automatically generate a web-based structured report for the diagnostician to easily review, learn from the justifications, and either modify and/or approve for optimal accuracy of the diagnosis and prognosis of CHD. Specifically we propose to: 1) develop a novel left ventricular (LV) quantitative algorithm that automatically extracts parameters of left LV regional perfusion and function used to diagnose CHD; 2) develop the LV expert (LVX) DSS and 3) design and implement the LV quantification and DSS algorithms using the .net platform so that they can be integrated into our Syntermed infrastructure and deployed over the web and/or used as conventional stand- alone work-stations. In Phase I we will develop a proof-of-principle system where LV perfusion information from MPS studies is analyzed and DSS interpreted for automatic report generation and physician review. In Phase II, the system will be: a) extended to include quantification and DSS of myocardial function, ischemia, viability and clinical risk factors, b) extended to include a methodology to continuously update LVX's KB, c) automated to link all the reconstruction, processing, quantification, interpretation, and reporting applications, and d) deployed in .net on the web with database and eCommerce accounting capability. Using this process we expect to confirm our primary hypothesis that diagnosticians using our decision support will provide a faster, more accurate diagnosis and prognosis of CHD than those provided by the same diagnosticians without the aid of this system. The system will be commercialized using Syntermed's successful strategy of other Emory software through: 1) licensing to major instrumentation manufacturers, 2) direct sales to clients that use PC workstations and 3) per WEB-access fee using the existing Syntermed Live network.

描述（由申请人提供）：当今的心脏成像领域要求诊断医生掌握不断扩展的知识库（KB），而掌握这些知识、将其应用于特定任务和报销的时间正在稳步缩短。这些限制造成了严重的医疗保健问题，不可避免地导致医生的错误。因此，需要新的工具来帮助医生及时地将全面的、最新的客观知识和可用的患者数据应用于特定的临床问题。我们的快速通道提案的长期目标是通过为可通过Web访问的心脏工具箱开发新工具来改善心脏病患者的护理并降低心脏图像判读的成本，该工具箱提供决策支持以提高检测冠心病（CHD）的准确性。具体来说，我们提出了一个基于WEB的系统，其中采集的心电门控心肌灌注SPECT（MPS）的原始图像上传自动重建和分析，以提取心肌灌注和功能的区域定量参数。这些参数被转换为异常的确定性因素，并提交给成像决策支持系统（DSS），该系统利用最新的科学/临床知识不断更新，以获得患者心脏状态的印象。DSS得出的这些结论和每个结论的理由用于自动生成基于网络的结构化报告，以供诊断医生轻松查看、从理由中学习，以及修改和/或批准CHD的诊断和预后的最佳准确性。具体而言，我们建议：1）开发一种新的左心室（LV）定量算法，其自动提取用于诊断CHD的左心室局部灌注和功能的参数; 2）开发LV专家（LVX）DSS和3）使用.net平台设计和实现LV量化和DSS算法，以便它们可以集成到我们的Syntermed基础设施中，并通过网络部署和/或用作传统的标准。独自工作站。在第一阶段，我们将开发一个原理验证系统，对MPS研究中的LV灌注信息进行分析，并对DSS进行解释，以自动生成报告和进行医生审查。在第II阶段，该系统将：a）扩展到包括心肌功能、缺血、存活力和临床风险因素的量化和DSS，B）扩展到包括持续更新LVX知识库的方法，c）自动连接所有重建、处理、量化、解释和报告应用程序，以及d）在具有数据库和电子商务核算功能的网络上的.net中部署。使用这个过程，我们希望证实我们的主要假设，即使用我们的决策支持的诊断医生将提供更快，更准确的诊断和CHD的预后比没有这个系统的帮助下，由相同的诊断医生提供。该系统将使用Syntermed的其他埃默里软件的成功战略进行商业化：1）许可给主要的仪器制造商，2）直接销售给使用PC工作站的客户，3）使用现有的Syntermed Live网络按WEB访问费用。

项目成果

Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging.

• DOI: 10.1007/s12350-018-1432-3
• 发表时间: 2020-10
• 期刊: Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
• 作者: Garcia EV;Klein JL;Moncayo V;Cooke CD;Del'Aune C;Folks R;Moreiras LV;Esteves F
• 通讯作者: Esteves F