A diagnostic model for malignant pulmonary nodules

肺恶性结节的诊断模型

• 批准号: 9805358
• 负责人: Feng Jiang
• 金额: $ 20.16万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-02 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9805358
• 关键词: Benign; Biological Markers; Biometry; Biopsy; Cells; Cessation of life; Clinic; Clinical; Complement; Data; Development; Diagnosis; Diagnostic; Disease; Emerging Technologies; Ensure; Female; Future; Growth; Image; Image Analysis; Immunologic Markers; Immunotherapy; Lung nodule; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Marriage; Medical; MicroRNAs; Modeling; Molecular Genetics; Morbidity - disease rate; Pathology; Physics; Procedures; Prospective Studies; Pulmonology; Radiology Specialty; Resources; Sensitivity and Specificity; Smoker; Specimen; Target Populations; Testing; Time; Woman; X-Ray Computed Tomography; base; cohort; computed tomography screening; cost; cost effective; digital; effective therapy; follow-up; high dimensionality; low-dose spiral CT; lung cancer screening; male; men; microRNA biomarkers; molecular marker; mortality; multidisciplinary; never smoker; next generation sequencing; non-smoker; novel; oncology; peripheral blood; predictive modeling; radiological imaging; radiomics; screening program; success; whole genome

The early detection of lung cancer by low-dose computed tomography (LDCT) followed by effective treatments, including immunotherapy, can reduce the mortality. LDCT is now recommended for lung cancer screening in smokers. However, more than 25% of smokers screened by LDCT have indeterminate pulmonary nodules (PNs), of which only 4% are finally diagnosed to be lung cancers, whereas more than 95% are benign diseases, resulting in over-diagnosis. As a result, large numbers of smokers with indeterminate PNs are referred for invasive biopsies and expensive 2-year multiple follow-up examinations, which carry their own morbidity and mortality. Therefore, there is an unmet clinical need for accurately distinguishing malignant PN (lung cancer) from benign PN in smokers with LDCT-found PNs. However, none of biomarkers and radiological features of PNs provides sufficient diagnostic values required in the clinics for accurately identifying malignant PNs. The objective of this proposed project is to develop a test for specifically differentiating malignant from benign PN. The target population of this test will be smokers with LDCT-found PNs. Its future use in the clinics will spare smokers with benign PNs from invasive biopsies and expensive multiple follow-up examinations, while facilitating effective treatments to be instantly initiated for lung cancer. Therefore, the test could complement LDCT for the early detection lung cancer, and thereby reduce the mortality and cost.

通过低剂量计算机断层扫描（LDCT）早期发现肺癌， 包括免疫疗法在内的治疗可以降低死亡率。LDCT现在被推荐用于肺癌 吸烟者的筛查然而，超过25%接受LDCT筛查的吸烟者患有不确定的肺部疾病 结节（PN），其中只有4%最终被诊断为肺癌，而超过95%是良性的 疾病，导致过度诊断。因此，大量的吸烟者与不确定的PN被转介 用于侵入性活检和昂贵的2年多次随访检查，这些检查本身就有发病率 and mortality.因此，对于准确区分恶性PN（肺）存在未满足的临床需求。 癌症）与良性PN的吸烟者LDCT发现的PN。然而，没有生物标志物和放射性 PNs的特征提供了临床所需的足够诊断价值，用于准确识别恶性肿瘤， PN。本项目的目的是开发一种检测方法，用于特异性区分恶性肿瘤和 良性PN本试验的目标人群将是LDCT发现PN的吸烟者。它未来在临床上的应用 将使患有良性PN的吸烟者免于侵入性活检和昂贵的多次随访检查， 同时有助于立即开始对肺癌的有效治疗。因此，测试可以 与LDCT互补，早期发现肺癌，从而降低死亡率和费用。