Finding undiagnosed ATTR-CM patients using AI technology in clinical settings

在临床环境中使用人工智能技术寻找未确诊的 ATTR-CM 患者

• 批准号: 10481909
• 负责人: Kelly D Myers
• 金额: $ 25.18万
• 依托单位: ATOMO, INC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-21 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10481909
• 关键词: Adoption; Amyloidosis; Cardiac; Cardiovascular Diseases; Clinical; Clinical Decision Support Systems; Data; Databases; Department chair; Development; Diagnosis; Disease; Environment; Familial Hypercholesterolemia; Genetic; Goals; Health Care Costs; Healthcare; Heart; Heart failure; Hypertrophic Cardiomyopathy; Individual; Inherited; Journals; Low Prevalence; Medicine; Modeling; Molecular Medicine; Myopathy; Patients; Peer Review; Pennsylvania; Performance; Phase; Phenotype; Prealbumin; Prevalence; Prognosis; Publications; Publishing; Radionuclide Imaging; Random Allocation; Research; Risk; Services; Small Business Innovation Research Grant; Symptoms; System; Technology; Testing; Training; Universities; Update; Work; aortic valve replacement; base; biobank; clinical decision support; clinical implementation; commercialization; design; effective therapy; experience; genetic testing; improved; insight; medical schools; mortality; personalized screening; professor; success; technical report

Project Summary: Transthyretin Amyloidosis with cardiac myopathy, ATTR-CM, represent a serious healthcare issue. ATTR-CM is involved in 13% of heart failure, 16% of transcatheter aortic-valve replacement, and 5% of individuals with presumed hypertrophic cardiomyopathy. The primary challenge is that most patients are undiagnosed or their diagnosis is delayed for multiple years. Since the damage ATTR-CM causes to the heart is progressive, diagnosis delays strongly impact prognosis and increase mortality. Diagnosis is problematic for two reasons: ATTR-CM has a variable presentation and the prevalence is not high. Thus, ATTR-CM is often not considered during diagnosis and a more common diagnosis with similar symptoms is given erroneously. Up to 98% of patients are not diagnosed due to the low prevalence and variable presentation. One study found that 32% of ATTR-CM patients had previously been misdiagnosed as having more common cardiovascular diseases. A readily-available genetic test can be used to detect hATTR and 99mTc-DPD-scintigraphy can be used to diagnose ATTR-CM (both hereditary and wild type). Fortunately, once diagnosed, ATTR is treatable. Thus, the main challenge for ATTR-CM is diagnosis, not therapy. An effective and economical precision screening system is needed to find the individuals most at risk of ATTR- CM. Those identified via precision screening could be tested and, treated with effective therapy resulting in saved lives and reduced healthcare costs. Atomo’s goal in this SBIR Fast-Track proposal is to create, optimize and implement an AI-based Clinical Decisions Support System (CDSS) to identify probable yet undiagnosed ATTR patients before they develop CM. For this work, we are partnering with Dr. Dan Rader and PENN Medicine. Dr. Rader is the Seymour Gray Professor of Molecular Medicine and Chair of the Department of Genetics at the Perelman School of Medicine of the University of Pennsylvania. Dr. Rader also directs the Penn Medicine Biobank. We would utilize the BioBank to identify True Positive patients to train and evaluate an AI model to find probable yet undiagnosed ATTR individuals. The model would be used in a pilot, most likely as a quality improvement initiative. To complete this work, Atomo will leverage its proven ML technologies that have been used and verified clinically, with published in peer-reviewed journals. The ATTR AI model would be commercialized as an Insights As A Service (IaaS) CDSS.

项目摘要：经甲状腺素淀粉样变性合并心肌病，ATTR-CM，是一种严重的 医疗保健问题。13%的心力衰竭、16%的经导管主动脉瓣置换术 5%的人被认为患有肥厚型心肌病。最主要的挑战是 患者没有得到诊断或他们的诊断被推迟了多年。由于Attr-CM造成的损坏 对心脏来说是进行性的，诊断延误严重影响预后并增加死亡率。诊断是 有问题有两个原因：ATTR-CM的表现多种多样，患病率不高。因此， 在诊断过程中通常不考虑ATTR-CM，而具有类似症状的更常见的诊断是 错误地给予。高达98%的患者由于低患病率和变量而未被诊断 演示文稿。一项研究发现，32%的ATTR-CM患者以前曾被误诊为 更常见的心血管疾病。一种容易获得的基因测试可以用来检测hAttr和 99mTc-DPD-核素显像可用于诊断遗传型和野生型ATTR-CM。幸运的是， 一旦确诊，ATTR是可以治疗的。因此，ATTR-CM面临的主要挑战是诊断，而不是治疗。一个 需要有效和经济的精确筛查系统来发现最有可能患非酒精性胃肠炎的个体。 厘米。那些通过精确筛查确诊的患者可以进行测试，并进行有效的治疗，从而导致 挽救了生命，降低了医疗成本。ATOM在这份SBIR快速通道计划中的目标是创建、优化 并实施基于人工智能的临床决策支持系统(CDSS)，以识别可能尚未诊断的 ATTR患者在发生CM之前。在这项工作中，我们与丹·雷德博士和宾夕法尼亚大学合作 医学。雷德博士是西摩·格雷分子医学教授和 宾夕法尼亚大学佩雷尔曼医学院的遗传学。雷德博士还执导了 宾夕法尼亚医学生物库。我们将利用生物库来识别真阳性患者，以进行培训和评估 一种人工智能模型，用于寻找可能但未诊断的ATTR个体。该模型将用于试点，MOST 很可能是一种质量改进举措。为了完成这项工作，Atom o将利用其经过验证的ML 已在临床上使用和验证的技术，并在同行评议的期刊上发表。《资产负债表》 人工智能模型将作为洞察即服务(IaaS)CDSS进行商业化。