Non-invasive evaluation of indeterminate pulmonary nodules

不确定肺结节的无创评估

• 批准号: 9753730
• 负责人: PIERRE P. MASSION
• 金额: $ 37.61万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-03 至 2020-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9753730
• 关键词: Address; Anxiety; Autoantibodies; Benign; Biological Markers; Biopsy; Blood; Cessation of life; Characteristics; Clinical; Clinical Management; Clinical Trials; Community Hospitals; Data; Data Set; Diagnostic; Discrimination; Disease; Epidemic; Evaluation; Goals; Health Care Costs; Healthcare; Image; Image Analysis; Individual; Intervention; Investigation; Knowledge; Laboratories; Lung; Lung nodule; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Modeling; Molecular; Molecular Profiling; Molecular Structure; Morbidity - disease rate; Nodule; Patients; Peptides; Performance; Population; Probability; Radiation; Research; Risk; Risk Estimate; Scanning; Structure; Techniques; Technology; Testing; Thoracotomy; Time; Validation; X-Ray Computed Tomography; automated image analysis; base; blood-based biomarker; candidate marker; chest computed tomography; cohort; computed tomography screening; cost; diagnostic accuracy; follow-up; high risk; imaging biomarker; improved; innovation; low-dose spiral CT; lung cancer screening; molecular marker; noninvasive diagnosis; novel; personalized care; predictive modeling; predictive tools; prospective; public health relevance; quantitative imaging; radiomics; screening; screening program; specific biomarkers

 DESCRIPTION (provided by applicant): We are facing an epidemic of indeterminate pulmonary nodules (IPNs), not only those found incidentally, but also through the proliferation of CT screening programs targeting high-risk individuals for lung cancer following the encouraging results of the National Lung Screening Trial (NLST). Although the large majority of IPNs are benign, there are currently no effective predictive tools to discriminate benign from malignant nodules, leading to a large number of follow-up CTs, unnecessary invasive biopsies, anxiety, and wasted healthcare spending. Our project addresses this deficiency in knowledge, which we expect will result in improved non-invasive testing and paradigm-shifting prediction models in the clinical management of patients with IPNs. This project has the potential to transform the management of individuals presenting with IPNs. We aim at obtaining significant gains in non-invasive diagnostic accuracy of screening-detected and incidentally-detected IPNs by integrating clinical variables, innovative quantitative structural CT variables with novel blood-based biomarker candidates of IPNs. We will produce actionable diagnostic prediction models to personalize care and identify the small subset of individuals who will need a definitive intervention for lung cancer, and conversely, others who are at very low risk and do not require extensive follow-up. Based on findings from this project, we anticipate 1) using longitudinal data to improve our prediction accuracy for IPNs over time; 2) reduction in the rate of unneeded thoracotomies, the burden of unnecessary follow-up including anxiety; 3) ultimately increase the rate of cure and reduction of unnecessary radiation and healthcare cost.

 描述（由适用提供）：我们面临着不确定的肺结核（IPN）的流行，不仅是偶然发现的，而且还通过针对国家肺肺筛查试验的令人鼓舞的肺癌的CT筛查计划的扩散（NLST）。尽管绝大多数IPN都是良性的，但目前尚无有效的预测工具来区分良性与恶性结节，导致大量随访CT，不必要的入侵活检，焦虑和浪费的医疗保健支出。我们的项目解决了Knowle的这种缺陷，我们期望这将导致IPN患者临床管理中的非侵入性测试和范式转移预测模型。该项目有可能改变与IPN的个人的管理。我们旨在通过将临床变量，创新的定量结构CT变量与新型血液基于IPN的生物标志物候选者相结合，从而获得筛查检测和偶然检测IPN的非侵入性诊断准确性的显着增长。我们将生成可行的诊断预测模型，以个性化护理，并确定需要对肺癌进行明确干预的个人的小部分，相反，其他患有非常低风险并且不需要大量随访的人。根据该项目的发现，我们预计1）使用纵向数据来提高我们对IPN的预测准确性，随着时间的流逝。 2）降低不需要的胸部的率，包括焦虑的不必要随访的燃烧； 3）最终提高治愈率和降低不必要的放射和医疗保健成本。