Cardiovascular risk from comprehensive evaluation of the CT calcium score exam

CT钙评分检查综合评估心血管风险

基本信息

批准号：
10667803
负责人：
Sanjay Rajagopalan
金额：
$ 79.92万
依托单位：
CASE WESTERN RESERVE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-03-15 至 2027-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10667803
关键词：
Adherence Adipose tissue African American population Agatston Score Age Agonist Anticoagulants Aorta Archives Atherosclerosis Big Data Blood Platelets Blood Vessels Brown Fat Cadaver Calcium Cardiometabolic Disease Cardiovascular Diseases Cardiovascular system Cause of Death Charge Chest Classification Clinical Clinical Data Clinical Trials Cohort Studies Computer software Coronary Coronary Artery Risk Development in Young Adults Study Coronary artery Counseling Data Data Reporting Data Set Decision Making Diabetes Mellitus Disease Elasticity Engineering Evaluation Event Fatty acid glycerol esters Future GCG gene Genes Grouping Heart Heart Diseases Hepatic Image Individual Inferior Inflammation Institution Knowledge Link Machine Learning Mediastinal Metabolic Methodology Methods Modeling Morphology Obesity Oncology Participant Pathologic Patients Pharmaceutical Preparations Phenotype Preventive therapy Psoriasis Race Recommendation Reproducibility Research Risk Risk Factors Risk Marker Role Scanning Screening procedure Shapes Site Socioeconomic Status Surface Technology Transfer Testing Texture Therapeutic Tissues University Hospitals Work X-Ray Computed Tomography abdominal fat artificial intelligence method calcification cardioprotection cardiovascular disorder risk cardiovascular risk factor clinical risk cohort commercialization comorbidity coronary artery calcification cost data repository deep learning density disease phenotype dosage high risk imaging modality improved inhibitor innovation interest large datasets metabolomics neural network novel personalized medicine programs radiomics research study risk prediction risk stratification side effect socioeconomics statistics success time use

项目摘要

Cardiovascular risk from comprehensive evaluation of the CT calcium score exam Summary Using a comprehensive machine learning analysis of coronary artery calcifications and thoracic fat depots in CT calcium score images, we will predict future major adverse cardiovascular events. Improved characteriza- tion of cardiovascular risk will advance knowledge of cardiometabolic disease phenotypes and support clinical therapeutic decision-making and patient counseling for improved adherence. With improved risk prediction and identification of high-risk phenotypes, there will be an opportunity to guide precision preventive therapies, where guidance is needed given the cost and side effects associated with some of these therapies. The Agat- ston calcium score is the leading predictor of a future major adverse cardiovascular event, better than any oth- er single assessment. Epicardial fat volume and HU values are independent risk factors. We will combine analyses of fat and calcifications in CT calcium score exams in an unprecedented way. For coronary calcifica- tions, pathological observations and preliminary results suggest that examining other features (calcium-omics) can improve prediction as compared to whole-heart Agatston. Our assessments will characterize small, spotty, low-density calcifications, providing a better surrogate of disease vulnerability than Agatston, which is numeri- cally dominated by large, likely stable, calcifications. In addition to fat volumes, we will examine quantitative texture and shape features (fat-omics). Elevated HU values and tissue textures are indicative of fat inflamma- tion. All these observations suggest significant value in a combined fat-omics and calcium-omics analysis. We will use large archives of CT calcium score exams from different sites, including University Hospitals of Cleve- land, which is an institution with the largest no-charge CT calcium scoring program (>13,000 scans per year). These big data repositories provide a unique machine-learning opportunity. Numerous technical innovations are planned, including novel features, data representations, and machine learning approaches. In addition to clinical risk prediction, our CT calcium score analyses will dovetail in the future with many research interests, including the role of genes, metabolomics, co-morbidities (e.g., diabetes and psoriasis), socio-economic status, and cardio-oncology on cardiovascular risk.

CT钙评分检查综合评估心血管风险概括对冠状动脉钙化和胸部脂肪库进行全面的机器学习分析 CT钙评分图像，我们将预测未来主要的心血管不良事件。改进的特性心血管风险的认识将增进对心脏代谢疾病表型的了解并支持临床治疗决策和患者咨询以提高依从性。通过改进的风险预测和识别高风险表型，将有机会指导精准的预防性治疗，考虑到与其中一些疗法相关的成本和副作用，需要指导。阿加特- ston 钙评分是未来重大不良心血管事件的主要预测指标，比任何其他指标都要好呃单一评估。心外膜脂肪量和 HU 值是独立的危险因素。我们将结合以前所未有的方式分析 CT 钙评分检查中的脂肪和钙化。对于冠状动脉钙化—— 病理学观察和初步结果表明检查其他特征（钙组学）与全心 Agatston 相比，可以提高预测能力。我们的评估将描述小、参差不齐、低密度钙化，比 Agatston 提供了更好的疾病易感性替代指标，Agatston 是数值主要以大的、可能稳定的钙化为主。除了脂肪量之外，我们还将检查定量质地和形状特征（脂肪组学）。 HU 值和组织纹理升高表明存在脂肪炎症 - 。所有这些观察结果表明，脂肪组学和钙组学的综合分析具有重要价值。我们将使用来自不同地点（包括克利夫大学医院）的大量 CT 钙评分检查档案 land，这是一家拥有最大的免费 CT 钙评分项目的机构（每年超过 13,000 次扫描）。这些大数据存储库提供了独特的机器学习机会。多项技术创新正在计划中，包括新颖的功能、数据表示和机器学习方法。此外临床风险预测，我们的 CT 钙评分分析未来将与许多研究兴趣相吻合，包括基因的作用、代谢组学、合并症（例如糖尿病和牛皮癣）、社会经济地位、和心脏肿瘤学对心血管风险的影响。