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CT Characteristics of Emphysema for Evaluation of Pulmonary Nodules

肺气肿CT特征评价肺结节

基本信息

批准号：
9753352
负责人：
Charles Matthew Kinsey
金额：
$ 17.02万
依托单位：
UNIVERSITY OF VERMONT & ST AGRIC COLLEGE
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2021-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9753352
关键词：
Address Advisory Committees Affect Benign Biological Assay Biological Markers Biometry Blood Vessels Blood Volume Caliber Cancer Center Cancer Death Rates Cancer Detection Cancer Model Cancerous Cessation of life Characteristics Chiroptera Clinical Complement Computer Simulation Coupled Data Data Set Death Rate Detection Development Diagnosis Diagnostic Diagnostic radiologic examination Enrollment Environment Epidemiology Epigenetic Process Evaluation Foundations Goals Growth Image Image Analysis Individual International Intervention K-Series Research Career Programs Knowledge Lead Lobular Location Lung Lung nodule Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Malignant neoplasm of thorax Measures Mentors Modeling Molecular Morbidity - disease rate Morphology Nodule Pathologic Performance Physicians Physiology Positioning Attribute Principal Investigator Procedures Process Pulmonary Emphysema Radial Radiology Specialty Research Research Personnel Resources Risk Risk Factors Scanning Scientist Smoker Specificity Structure of parenchyma of lung Supervision System Testing Tissues Training Universities Vermont Work X-Ray Computed Tomography arm biomarker development cancer diagnosis carcinogenicity career development clinical practice cohort computed tomography screening cost density design experience imaging biomarker improved innovation investigator training lung acinus structure lung cancer screening medical specialties mortality multidisciplinary novel novel strategies preservation programs quantitative imaging screening screening program skills tumor virtual clinical trial

项目摘要

PROJECT SUMMARY/ABSTRACT 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 COPDGene 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.

项目摘要/摘要研究：国家肺部筛查试验 (NLST) 表明，使用该药物可使死亡率降低 20% 每年进行 CT 筛查，但由于评估 94% 的患者所执行的程序，发病率很高非癌性结节。该提案的目标是提高区分哪些内容的特异性通过使用与肺气肿相关的定量特征，这些“不确定”结节是肺癌通过单次 CT 扫描即可获得。我们的初步数据表明，中度小叶中心肺气肿 (MCE)，及其相关的血管特征，为新生肺的生长提供了一个利基。创新方法该建议是利用结节周围肺球体中 MCE 的特征来提高针对结节的特异性检测癌症。然而，增加特异性会导致灵敏度降低。以肺癌为例筛查更多“遗漏”的癌症可能会增加肺癌死亡率。了解减少的影响为了提高对死亡率的敏感性，我们将使用新颖的 UVM 肺癌模型，该模型准确地再现了肺癌癌症死亡率和 CT 筛查率，以确定一组最佳的生物标志物，用于识别癌症许多屏幕检测到的结节。候选人：Kinsey 博士的临床实践是介入肺科，这是一个专注于治疗的专业不确定结节的问题。他应用了 MPH 流行病学和生物统计学培训，结合定量 CT 成像经验，开始解决不确定结节的问题在 COPDGene 数据集中，并作为 UVM 分子、表观遗传学和放射学的首席研究员胸部癌症 (MEROPTIC) 研究的生物标志物。然而，他在这个过程中需要进一步的训练开发 CT 特征作为成像生物标志物和计算机建模，这将使他能够理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进行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：金赛博士的主要导师贝茨博士因其在肺病领域的工作而获得国际认可生理学和计算机建模，并拥有培训研究人员和医生的良好记录科学家。共同导师 George Washko 博士是定量成像分析领域的专家，拥有与金赛博士建立了指导关系。具有成熟专业知识的科学咨询委员会放射学、生物统计学、肺癌和生物标志物开发领域的研究补充了这一出色的指导团队。金赛博士在以下机构的支持下得到了个人和资源网络的进一步支持佛蒙特州肺中心和佛蒙特大学癌症中心，致力于青少年的发展调查人员。