AUTOMATIC QUANTITATIVE CT IMAGING OF PERICARDIAL FAT: A NOVEL ISCHEMIA PREDICTOR

心包脂肪自动定量 CT 成像：一种新型缺血预测指标

• 批准号: 7588839
• 负责人: Damini Dey
• 金额: $ 19.64万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7588839
• 关键词: Abdomen; Algorithms; Automation; Biochemical; Blood specimen; C-reactive protein; Calcium; Cardiac; Cholesterol; Clinical; Clinical Markers; Computational algorithm; Computer software; Contrast Media; Coronary; Coronary Arteriosclerosis; Coronary artery; Data; Development; Diagnostic; Evaluation; Fatty acid glycerol esters; Glucose; Goals; Heart; Heart Diseases; Image; Imaging Device; Ischemia; Knowledge; Machine Learning; Manuals; Measurement; Measures; Methods; Myocardial Infarction; Patients; Pericardial body location; Physicians; Predictive Value; Radiation; Reproducibility; Research; Risk; Risk Assessment; Scanning; Screening procedure; Symptoms; Testing; Time; Visceral; X-Ray Computed Tomography; base; cardiovascular risk factor; clinical practice; experience; heart imaging; indexing; novel; public health relevance; sudden cardiac death; tool; waist circumference

DESCRIPTION (provided by applicant): Every year, 1 million people in the US will experience a heart attack or sudden cardiac death. A large percentage of these patients have no prior symptoms of any kind but suffer from silent heart disease (ischemia), which may cause a heart attack at any time. Currently there is no reliable screening method to identify people who may have silent heart disease and therefore are at risk of "heart attack". We seek to extract additional data from a non-invasive Computed Tomography (CT) scan of the heart (commonly used in most imaging centers), which will better identify patients who are "vulnerable" to sudden heart attack. These images are acquired without contrast agents, as a common screening test for measuring coronary calcium, another clinical marker of coronary artery disease. We will prove that additional information about cardiovascular risk can be obtained by quantifying pericardial fat surrounding the heart in these cardiac CT images. Although this information exists in the cardiac CT scans acquired today, it is ignored in clinical practice because currently there are no tools to measure it automatically and reliably, and no information regarding its significance for a given patient. We will develop fully automated, accurate, new computer software for quantitation of pericardial fat from cardiac CT images acquired for routine assessment of coronary calcium. We plan to achieve complete automation and accuracy, by applying a combination of robust and effective algorithms in machine learning with anatomical knowledge. We aim to prove that the developed automatic software will be as accurate, and more reproducible than experienced imaging physicians in quantifying pericardial fat, and will accomplish the measurement in a fraction of the time. Such software could be immediately made available worldwide to standard imaging workstations. For the first time, this will allow its use as a standard practical imaging tool for cardiovascular risk assessment, without requiring additional time, imaging or radiation risk to the patient. We will also show that this new quantitative information has important additional value compared to other clinical cardiovascular risk factors and information from blood samples (such as cholesterol, glucose and CRP), and the amount of calcium in the patient's coronary arteries seen on CT scans, and establish its significance in the prediction of silent heart disease. PUBLIC HEALTH RELEVANCE: This new research will allow accurate prediction of who might be more likely to have heart disease which may ultimately cause a heart attack. It will allow doctors to identify patients for whom appropriate treatment could be prescribed to avoid a heart attack, or more extensive testing, could be recommended, to confirm or rule out heart disease.

描述（由申请人提供）：每年，美国有 100 万人会经历心脏病发作或心源性猝死。其中很大一部分患者既往没有任何症状，但患有无症状心脏病（缺血），随时可能导致心脏病发作。目前还没有可靠的筛查方法来识别可能患有隐性心脏病并因此面临“心脏病发作”风险的人。 我们寻求从心脏的非侵入性计算机断层扫描 (CT) 扫描（大多数成像中心常用）中提取更多数据，这将更好地识别“容易”突发心脏病的患者。这些图像是在没有造影剂的情况下获得的，作为测量冠状动脉钙（冠状动脉疾病的另一种临床标志物）的常见筛查测试。我们将证明，通过量化这些心脏 CT 图像中心脏周围的心包脂肪，可以获得有关心血管风险的更多信息。尽管这些信息存在于今天获得的心脏 CT 扫描中，但在临床实践中却被忽略，因为目前没有工具可以自动可靠地测量它，也没有关于其对特定患者的重要性的信息。 我们将开发全自动、准确的新型计算机软件，用于从用于常规评估冠状动脉钙的心脏 CT 图像中定量心包脂肪。我们计划通过将机器学习中稳健有效的算法与解剖知识相结合，实现完全自动化和准确性。我们的目标是证明所开发的自动软件在量化心包脂肪方面与经验丰富的影像医生一样准确且更具可重复性，并且将在很短的时间内完成测量。此类软件可以立即在全球标准成像工作站上使用。这将首次允许其用作心血管风险评估的标准实用成像工具，而不需要额外的时间、成像或对患者造成辐射风险。 我们还将证明，与其他临床心血管危险因素和血液样本信息（如胆固醇、葡萄糖和 CRP）以及 CT 扫描中看到的患者冠状动脉钙含量相比，这一新的定量信息具有重要的附加价值，并确立其在预测无症状心脏病中的意义。 公共卫生相关性：这项新研究将能够准确预测谁更有可能患有心脏病，最终可能导致心脏病发作。它将允许医生识别可以为哪些患者开出适当的治疗以避免心脏病发作，或者可以建议进行更广泛的测试，以确认或排除心脏病。

项目成果

Relationship of epicardial fat volume to coronary plaque, severe coronary stenosis, and high-risk coronary plaque features assessed by coronary CT angiography.

• DOI: 10.1016/j.jcct.2013.02.003
• 发表时间: 2013-03
• 期刊: Journal of cardiovascular computed tomography
• 影响因子: 5.4
• 作者: Rajani R;Shmilovich H;Nakazato R;Nakanishi R;Otaki Y;Cheng VY;Hayes SW;Thomson LE;Friedman JD;Slomka PJ;Min JK;Berman DS;Dey D
• 通讯作者: Dey D

Not all body fat weighs equally in the acceleration of coronary artery disease.

并非所有身体脂肪都会同等程度地加速冠状动脉疾病。

• DOI: 10.1016/j.jcmg.2010.08.002
• 发表时间: 2010
• 期刊: JACC. Cardiovascular imaging
• 作者: Berman,DanielS;Cheng,VictorY;Dey,Damini
• 通讯作者: Dey,Damini

Automated algorithm for atlas-based segmentation of the heart and pericardium from non-contrast CT.

• DOI: 10.1117/12.844810
• 发表时间: 2010-03-01
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Dey D;Ramesh A;Slomka PJ;Nakazato R;Cheng VY;Germano G;Berman DS
• 通讯作者: Berman DS

Pericardial fat burden on ECG-gated noncontrast CT in asymptomatic patients who subsequently experience adverse cardiovascular events.

• DOI: 10.1016/j.jcmg.2009.12.013
• 发表时间: 2010-04
• 期刊: JACC-CARDIOVASCULAR IMAGING
• 影响因子: 14
• 作者: Cheng, Victor Y.;Dey, Damini;Tamarappoo, Balaji;Nakazato, Ryo;Gransar, Heidi;Miranda-Peats, Romalisa;Ramesh, Amit;Wong, Nathan D.;Shaw, Leslee J.;Slomka, Piotr J.;Berman, Daniel S.
• 通讯作者: Berman, Daniel S.

Towards cardiovascular risk stratification using imaging data.

使用影像数据进行心血管风险分层。

• DOI: 10.1109/iembs.2009.5335388
• 发表时间: 2009
• 期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
• 作者: Kakadiaris,IA;Kurkure,U;Mendizabal-Ruiz,EG;Naghavi,M
• 通讯作者: Naghavi,M