Deep Radiomic Analysis of Coronary Heart Disease with Lung Screening CT

2015年，心血管疾病（CVD）导致1770万人死亡，占所有死亡人数的三分之一 在全球在2015年880万癌症死亡中，肺癌导致全球169万人死亡。 在美国，2018年肺癌将夺走154，050人的生命，占所有癌症死亡人数的四分之一。 心血管疾病和肺癌都有几个共同的风险因素，包括不健康的饮食模式，肥胖和烟草 使用.低剂量计算机断层扫描（LDCT）是一种有效的肺癌筛查技术， 在有大量吸烟史的人群中，癌症相关死亡率降低20%。这样的人，基本上 心血管疾病的风险高于肺癌。事实上，大多数接受LDCT肺癌筛查的受试者 心血管疾病的中度至高度风险。伴随CVD筛查将对这些受试者产生深远的获益 无需额外的时间、费用或对患者造成辐射剂量。 该项目的目标是开发一个心血管发病率和死亡率风险的自动化工作流程 （CARMOR）评估肺癌筛查LDCT数据，为高危受试者提供“无辐射”CVD 没有成本或时间限制的筛选。我们的中心假设是LDCT随访的深部放射组学 扫描和跨不同重建可以有效地提高CARMOR估计的性能。到 为了验证我们的假设，我们将使用肺癌筛查LDCT对CARMOR进行放射组学分析 扫描，然后进一步增强CARMOR功能与互补图像重建从 相同的扫描和连续LDCT扫描，以优化预后性能。CARMOR定量方法 在肺部筛查中，LDCT将针对多名患有冠状动脉疾病的亚专科放射科医生进行回顾性验证。 计算机断层扫描血管造影（CCTA）作为参考标准。这个项目要求我们 分析了连续LDCT检查和不同重建技术和设置。因此，少校 对于这种具有挑战性的深度放射组学分析任务，需要进行创新和改进。 由于心血管疾病和肺癌的危险因素与生活方式密切相关，因此该项目的研究结果可以 也可以用来为病人创造可教的时刻，改变健康的生活方式。的上下文中 医疗保险和医疗补助服务中心（CMS）报销LDCT用于肺癌筛查和压力 考虑到合并症的重要性，我们及时的项目将对医疗保健产生重大影响， 大量人口的。在项目结束时，我们将开发一个自动化的工作流程， CARMOR用于肺部筛查LDCT，增加了零辐射。我们还将获得研究结果， 个性化的患者教育，以解决不健康的生活方式造成的长期健康危机。我们的研究 将导致对CVD筛查中的深度放射组学的新理解，以及LDCT重建对CVD的影响。 临床实践

Cardiovascular diseases (CVDs) caused 17.7 million deaths in 2015, accounting for one third of all deaths globally. Amongst 8.8 million cancer-deaths in 2015, lung cancer contributed to 1.69 million deaths worldwide. In the United States, lung cancer will claim 154,050 lives in 2018, representing a quarter of all cancer deaths. Both CVDs and lung cancer share several risk factors, including unhealthy dietary patterns, obesity, and tobacco use. Low-dose Computed Tomography (LDCT), an effective lung cancer screening technique, reduces the cancer-related mortality rate by 20% in those with history of heavy smoking. Such subjects have substantially higher risk of CVDs than lung cancer. Indeed, most subjects undergoing lung cancer screening with LDCT have an intermediate to high risk for CVDs. Concomitant CVD screening will have profound benefits for these subjects at no additional time, cost, or radiation dose to the patient. The goal of the project is to develop an automated workflow of cardiovascular morbidity and mortality risk (CARMOR) evaluation with lung cancer screening LDCT data to provide high-risk subjects a “radiation-free” CVD screening without cost or time constraints. Our central hypothesis is that deep radiomics from LDCT follow-up scans and across different reconstructions can effectively improve the performance of CARMOR estimation. To validate our hypothesis, we will perform radiomics analysis on CARMOR with lung cancer screening LDCT scans, and then further enhance the CARMOR features with complementary image reconstructions from the same scan and serial LDCT scans for optimized prognostic performance. The CARMOR quantification methods in lung screening LDCT will be validated retrospectively against multiple subspecialty radiologists with Coronary Computed Tomography Angiogram (CCTA) as the standard of reference. The project requires us to perform analyses over serial LDCT exams and different reconstruction techniques and settings. Therefore, major innovations and improvements need to be made for this challenging deep radiomic analysis task. Since the risk factors of CVDs and lung cancer are closely related with lifestyle, the findings of the project can also be used to create teachable moments for patients to change towards healthier lifestyles. In context of the Center for Medicare & Medicaid Services (CMS) reimbursement of LDCT for lung cancer screening and stress on the importance of considering co-morbidities, our timely project will have a significant impact on the healthcare of a large population. At the end of the project, we will have developed an automated workflow of assessing CARMOR for lung screening LDCT with zero radiation added. We will also have acquired study results to enable personalized patient education to address the long-term health crisis caused by unhealthy lifestyles. Our studies will lead to new understanding of deep radiomics in CVD screening and the impact of LDCT reconstructions in clinical practice.