CT Characteristics of Emphysema for Evaluation of Pulmonary Nodules

项目总结/摘要 K23项目的原始描述将不会更改-如下所述： 研究：国家肺筛查试验（NLST）表明，使用 的年度CT筛查，但由于对94%的 不是癌性的结节。该提案的目标是提高区分哪些 这些“不确定”结节中的一个是肺癌，通过使用与肺气肿相关的定量特征， 一次CT扫描就能得到我们的初步数据表明，中度小叶中心型肺气肿（MCE）， 及其相关的血管特征为新生肺的生长提供了一个小生境。创新的方法， 该建议是利用结节周围肺球中MCE的特征来提高检测的特异性 癌然而，增加特异性导致降低灵敏度。在肺癌筛查方面， 更多的“漏诊”癌症可能会增加肺癌死亡率。为了了解降低敏感性对 死亡率，我们将使用新的UVM肺癌模型，它准确地概括了肺癌死亡， CT筛查率，以确定一组最佳的生物标志物，用于在众多筛查中识别癌症。 检测到结节。 候选人：金赛博士的临床实践是在介入肺，一个专业，重点是处理 不确定结节的问题。他应用了他的公共卫生硕士流行病学和生物统计学培训，加上 随着定量CT成像的经验，开始解决不确定结节的问题， COPD基因数据集，并作为UVM分子、表观遗传学和放射学的主要研究者， 胸部癌症生物标志物（MEROPTIC）研究。然而，他需要进一步的培训， 开发CT特征作为成像生物标志物和计算机建模，这将使他了解 这些生物标志物的部署对肺癌死亡率的影响。为了解决这些关键差距， 他的主要导师杰森·贝茨博士设计了一个教学培训计划，并监督 这项研究将推动金赛博士成为肺癌诊断领域的独立研究者。 环境：Kinsey博士的主要导师Bates博士因其在肺部疾病方面的工作而受到国际认可。 生理学和计算机建模，并有培训研究人员和医生的良好记录 科学家共同导师乔治沃什科博士是定量成像分析专家， 与金赛博士建立了指导关系一个科学咨询委员会，具有以下方面的专业知识： 放射学、生物统计学、肺癌和生物标志物开发补充了这一杰出的指导团队。 博士金赛进一步支持的个人和资源的网络，在佛蒙特州的赞助下， 肺中心和佛蒙特大学癌症中心，即致力于发展初级 investigators.

PROJECT SUMMARY/ABSTRACT The original description of the K23 project will not change – as re-iterated below: Research: The National Lung Screening Trial (NLST) demonstrated a 20% reduction in mortality with the use of annual CT screening but with significant morbidity due to procedures performed for evaluation of the 94% of nodules that were not cancerous. The goal of this proposal is to improve the specificity for distinguishing which of these “indeterminate” nodules is lung cancer by using quantitative features associated with emphysema available from a single CT scan. Our preliminary data indicate that moderate centrilobular emphysema (MCE), and its associated vascular features, provide a niche for the growth of nascent lung. An innovative approach of this proposal is to use features of MCE in the sphere of lung around a nodule to improve specificity for detecting cancer. However, increasing specificity results in decreasing sensitivity. In the case of lung cancer screening more “missed” cancers may increase lung cancer deaths. To understand the effect of decreasing sensitivity on mortality we will use the novel UVM Lung Cancer Model, which accurately recapitulates lung cancer death and CT screening rates, to identify an optimal set of biomarkers for identifying cancer among the many screen detected nodules. Candidate: Dr. Kinsey's clinical practice is in Interventional Pulmonary, a specialty that focuses on dealing with the problem of indeterminate nodules. He has applied his MPH epidemiology and biostatistical training, coupled with experience in quantitative CT imaging, to begin to address the problem of indeterminate nodules in the COPD Gene data set and as the Principal Investigator of the UVM Molecular, Epigenetic, and Radiologic Biomarkers for Thoracic Cancers (MEROPTIC)study. However, he needs further training in the process of developing CT features as imaging biomarkers and in computer modeling, which will allow him to understand the effect of deployment of these biomarkers on lung cancer mortality. To address these critical gaps in knowledge his primary mentor, Dr. Jason Bates, has designed a program of didactic training and supervised research that will propel Dr. Kinsey to an independent investigator in the field of lung cancer diagnosis. Environment: Dr. Kinsey's primary mentor, Dr. Bates, is internationally recognized for his work in pulmonary physiology and computer modeling and has a proven track record of training investigators and physician scientists. The co-mentor, Dr. George Washko, is an expert in quantitative imaging analysis and has an established mentoring relationship with Dr. Kinsey. A scientific advisory committee with established expertise in radiology, biostatistics, lung cancer, and biomarker development complements this outstanding mentoring team. Dr. Kinsey is further supported by a network of individuals and resources, under the auspices of the Vermont Lung Center and University of Vermont Cancer Center, that is committed to the development of junior investigators.