Development of a Novel Diagnostic Test for Pulmonary Embolism Based on Artificial Intelligence and Spectral Analysis of Blood

肺栓塞(PE)是一种潜在的危及生命的疾病，影响所有年龄的成年人，但也可能 出现无数的症状，从胸痛到呼吸急促、晕厥或癫痫。 目前，医生可以通过血液测试(D-二聚体)来评估这种情况，这种测试具有很高的敏感性，但 特异性很差，从而导致大量的假阳性。或者，或者在 D-二聚体阳性、CT肺血管造影(CTPA)或通风-灌注(VQ)扫描可以 这两种方法都很昂贵，而且会使患者暴露在大量的电离辐射中。至 开发一种更具特异性的PE血液测试，BioCogiv将应用最先进的人工智能(AI)来 现有血液生物标记物在两种商业多用途仪器上测量的聚集分析 免疫分析平台，其中之一目前用于医院实验室。一个足够准确、快速和 具有成本效益的测试可以被广泛应用(即，像心肌梗死的肌钙蛋白-I一样)以减少过度使用 CT，简化ED决策，并减少因无法识别的PE而死亡的人数。 在这项拟议的第一阶段单中心研究中，BioCogiv将与佛蒙特州医科大学合作 UVMMC中心(UVMMC)演示急诊科(ED)患者诊断PE的概念验证 对于那些对PE有足够关注的人来说，作为常规临床护理的一部分，有必要进行D-二聚体检测。特定的 目的一是采集UVMMC急诊科225名患者的血液，他们涉嫌 进行PE(包括CTPA确诊的75例PE患者)，并对血浆进行分析。 定量免疫分析为人工智能分析创建训练和验证数据集。免疫分析将是 包括一套并行执行的6种快速FDA清除的化学发光免疫分析，以及一种 靶向已知心血管和炎症相关标记物的20-plex珠基免疫分析板 患有急性PE。具体目标二是为两个预测测试群体开发人工智能数据模型-所有D-二聚体都进行了测试 患者和仅D-二聚体阳性患者-基于珠粒和护理点的免疫分析数据集 (单独分析)，然后评估每个数据模型在血浆数据子集上的性能 被扣留以待验证。作为AI数据模型性能评估的一部分，研究的潜在影响 数据模型准确性的大小将通过绘制作为训练样本数的函数的特异度来模拟 说明增加更多的样本可以提高测试结果。每种方法(即人工智能)的性能 应用于给定预试人群的给定免疫分析小组的方法)将被比较和使用 计划第二阶段多中心研究，并确定和吸引合适的仪器合作伙伴。 BioCogiv的最终目标是开发一种快速、高度特异和敏感的FDA批准的PE检测方法，将 成为潜在肺栓塞患者的初始诊断和分诊的标准护理， 颠覆每年20亿美元的D-二聚体市场，改善ED患者护理。

Pulmonary Embolism (PE) is a potentially life-threatening condition that affects adults of all ages yet can present with a myriad of symptoms, ranging from chest pain to shortness of breath, syncope, or seizure. Currently, physicians can assess for this condition with a blood test (D-dimer) which has high sensitivity but very poor specificity, thus resulting in a larger number of false positives. Alternatively, or in the case of a positive D-dimer, computed tomography pulmonary angiography (CTPA) or ventilation-perfusion (VQ) scan can be used, both of which are expensive and expose the patient to a significant amount of ionizing radiation. To develop a more specific blood test for PE, Biocogniv will apply state-of-the-art artificial intelligence (AI) to aggregate analysis of existing blood biomarkers measured on two commercially available multiplex immunoassay platforms, one of which is currently used in hospital labs. A sufficiently accurate, rapid and cost-effective test could be broadly applied (i.e., like troponin-I for myocardial infarction) to reduce overuse of CT, simplify ED decision making, and reduce the number of deaths from unrecognized PE. In this proposed Phase I single center study, Biocogniv will collaborate with the University of Vermont Medical Center (UVMMC) to demonstrate proof-of-concept for diagnosing PE in emergency department (ED) patients for whom there is sufficient concern for PE to warrant a D-dimer test as part of routine clinical care. Specific Aim I is to collect blood from 225 emergency department (ED) patients at UVMMC who were suspected of having PE (including 75 patients that are confirmed to have PE by CTPA), and analyze the blood plasma with quantitative immunoassays to create training and validation datasets for AI analysis. Immunoassays will be comprised of a set of 6 rapid FDA-cleared chemiluminescent immunoassays performed in parallel, and a 20-plex bead-based immunoassay panel targeting known cardiovascular and inflammatory markers associated with acute PE. Specific Aim II is to develop AI data models for two pretest populations—all D-dimer tested patients and just D-dimer positive patients—for bead-based and point-of-care immunoassay datasets (analyzed separately), then evaluate the performance of each data model on a subset of blood plasma data withheld for validation. As part of the evaluation of AI data model performance, the potential impact of study size on data model accuracy will be simulated by plotting specificity as a function of training sample number to show that adding more samples can improve test results. The performance of each approach (i.e., AI methodology applied to a given immunoassay panel for a given pretest population) will be compared and used to plan a Phase II multi-center study and to identify and attract a suitable instrumentation partner. Biocogniv’s end goal is to develop a rapid, highly specific and sensitive FDA cleared test for PE that will become the standard of care for initial diagnosis and triage of patients with potential pulmonary embolism, disrupting the $2B/year D-Dimer market and improving ED patient care.