Active clinical trials for "Solitary Pulmonary Nodule"

To perform a multiple reader, multiple case (MRMC) observer study assessing the detection performance of VolumeRAD tomosynthesis of the chest in detecting lung nodules.

A Study to evaluate the utility of the ProLung China Test as an adjunct to CT scan in the diagnosis of lung cancer.

The purpose of the study is the identification of the efficacy of MDA Test to Differentiate of Benign and Malignant Pulmonary Nodules. In this study, the investigators are going to validate the efficacy of the MDA test for diagnosing early lung cancer by comparing results of the pre-surgery MDA test with the post-surgery pathology.

Medical The Internet of Things (IoT), a recent breakthrough in communication technology, could be helpful in improving health care delivery and saving medical costs, but regarding pulmonary nodule management it is still at the basic understanding. Investigators adopt "Internet of things medical three plus two type pulmonary nodule diagnosis" which chun-xue Bai put forward, used a developed a mobile phone-based IoT (mIoT) platform and initiated a randomized, multicenter, controlled trial to value clinical effectivity of "Internet of things medical three plus two type pulmonary nodule diagnosis" in the management of pulmonary nodules. In this study, at least 600 patients with pulmonary nodules (no typical symptoms, often single, clear boundary, increased density, soft tissue shadow surrounded by lung parenchyma with diameter ≤3 cm) will be randomly allocated to the control group, which receives routine follow-up, or the intervention group, which receives "Internet of things medical three plus two type pulmonary nodule diagnosis" management. Endpoints of the study include: (1) The positive diagnosis rate of lung cancer in I stage; (2) 5 year disease-free survival rate and overall survival rate; (3) direct medical costs per year. Results from this study should provide direct evidence for the suitability of "Internet of things medical three plus two type pulmonary nodule diagnosis" in pulmonary nodules patients management.

The ACRIN 7151 trial will use medical records abstraction data from participants with extracolonic findings (ECFs) reported from the ACRIN 6664 National CT Colonography Trial to: 1) measure incidence of diagnostic imaging, hospitalization, and interventional procedures associated with ECFs reported on computed tomography colonography (CTC), delineated by type of ECF; 2) determine potential predictors of follow-up diagnostic imaging, hospitalization, and interventional procedures, delineated by type of ECF; and 3) evaluate the clinical/pathologic diagnoses associated with indeterminate but potentially significant ECFs. These data can be used to incorporate ECFs into existing models on the cost-effectiveness of CTC in colorectal cancer screening and can potentially be used to develop guidelines for the reporting and management of ECFs.

By testing the CTC number of new solitary pulmonary nodule patient, evaluating the correlation of CTC number and benign and malignant lung nodules auxiliary diagnosis, the correlation of CTC number and the size of lung nodules of the malignant patients, the correlation between the CTC number and subtypes of malignant lung nodules patients.The CTC and tumor markers will be detected before the patient received treatment. Tumor markers include Pro-GRP, NSE, CEA, CYFRA211, SCC.

This study will collect retrospective CT scan images and clinical data from participants with incidental lung nodules seen in hospitals across London. The investigators will research whether machine learning can be used to predict which participants will develop lung cancer, to improve early diagnosis.

Lung cancer is one of the leading cause of cancer related death in China. Lung cancer screening with low-dose computed tomography was considered as a better approach than radiography. However, the role of Lung cancer screening with Low-dose CT (LDCT) among Chinese people remains unclear. With rapid development of artificial intelligence (AI),the application of AI in detection and diagnosis of diseases has become research focus. Moreover, patients' psychological status also plays an important role in diagnosis and treatment. This study focuses on detection and natural history management of lung nodule and lung cancer with AI assisted chest CT among people living in North China, and aims to investigate epidemiological results, patients' medical records and social psychological status.

Among the causes of the solitary pulmonary nodule (SPN), benign causes including tuberculosis was noted on 15 to 60 percents in various studies. Although the characteristics of chest imaging is helpful in diagnosis and percutaneous needle biopsy for pulmonary nodule has been represented high diagnostic yield in many reports, but still surgical biopsy has been needed in definite diagnosis of pulmonary nodules in many cases. The aim of this study is to evaluate the usefulness of interferon-gamma release assay in addition to the percutaneous needle biopsy, in diagnosis of pulmonary nodules.