View clinical trials related to Solitary Pulmonary Nodule.
Filter by:The goal of this observational study is to learn how a physician uses the results of the Percepta® Nasal Swab test to manage people with a newly identified pulmonary nodule. The main questions it aims to answer are: - Does the use of the Percepta Nasal swab test reduce the number of invasive procedures in people with a low-risk result and whose nodule is benign? - Does the use of the Percepta Nasal swab test decrease the time to treatment in people with a high-risk result and whose nodule is cancer? Participants will be randomly assigned to either a group where the test result is provided to the physician (test arm) or to a group where the test result is not provided (control arm). Researchers will compare management of participants in the two groups.
Multi-center randomized controlled study designed to compare the diagnostic yield of ION™ Endoluminal System with electromagnetic navigation bronchoscopy in patients undergoing transbronchial sampling procedure of peripheral pulmonary nodules.
The goal of this observational clinical trial is to evaluate the value of circulating tumor cell detection in the early diagnosis of malignant pulmonary nodule. The main questions it aims to answer is: the sensitivity and specificity of peripheral blood circulating tumor cell detection in differentiating benign and malignant pulmonary nodules (<3cm). Participants will be asked provide 4mL of peripheral blood for the test.
This is a pragmatic clinical trial that will study the effect of a radiomics-based computer-aided diagnosis (CAD) tool on clinicians' management of pulmonary nodules (PNs) compared to usual care. Adults aged 35-89 years with 8-30mm PNs evaluated at Penn Medicine PN clinics will undergo 1:1 randomization to one of two groups, defined by the PN malignancy risk stratification strategy used by evaluating clinicians: 1) usual care or 2) usual care + use of a radiomics-based CAD tool.
Since the beginning of lung screening program in the different countries around the world by chest CT scan, numerous lung nodules and masses of unknown etiology are diagnosed. Usually, the pathological diagnosis is obtained by bronchoscopy. However, peripheral bronchi cannot be seen after the fifth bronchial division as the diameter of the broncoscope is greated than the diameter of the bronchi. Therefore, the Iriscope was developed. It consists in a thin catheter with a mini-camera at its distal extremity. The aime of this study is to evaluate the diagnostic yield of bronchoscopy guided by Iriscope in the setting of peripheral lung nodules and masses supect of malignancy, to compare the Iriscope to endobronchial radial ultrasonography (which is a validated technique to guide bronchoscopy in the setting of peripheral lung nodules and masses) and to evaluate the added value on the diagnostic yield by combining these 2 techniques.
Lung cancer is the first cancer in China in terms of morbidity and mortality. The problem of early diagnosis/treatment has always been concerned. The popularization of chest CT (electronic computed tomography) screening makes it possible to detect lung cancer early. However, the diagnosis still needs pathological evidence. It is an ideal choice to obtain pathological evidence through bronchoscope and other minimally invasive means before surgical resection. However, the positive rate of tracheoscopy is still unsatisfactory, which is related to the difficulty of traditional pathological detection in detecting small specimens obtained by tracheoscopy. Liquid biopsy technology based on methylation detection has been used in early cancer screening, but its advantages have not been fully exploited due to the low content of ctDNA (circulating tumor DNA) in the current detection samples. Therefore, through prospective clinical research, the investigators plan to combine the methylation detection technology based on "Whole genome methylation sequencing(GM-seq)" with tracheoscopy, compare the traditional pathological methods with methylation detection on the bronchoscopic samples of lung nodule subjects suspected of early lung cancer, and take the postoperative pathology as the gold standard for judging benign and malignant, to confirm the feasibility and advantages of the new technology.
This study is a multi-centre prospective observational cohort study recruiting patients with 5-30mm solid and part-solid pulmonary nodules that have been detected on CT chest scans performed as part of routine practice. The aim is to determine whether physician decision making with the AI-based LCP tool, generates clinical and health-economic benefits over the current standard of care of these patients.
Background Transthoracic computed tomography (CT)-guided procedures are the current gold Standard for obtaining diagnostic biopsies of solitary pulmonary nodules (SPN) in the peripheral lung. Novel endobronchial techniques, such as electromagnetic navigation bronchoscopy (ENB) or Virtual bronchoscopic navigation (VBN) are considered safer to approach SPNs. The newest technique combines VBN with calculating the access to a SPN via a transparenchymal route. In contrast to the gold Standard transthoracic approach, also small lesions, and lesions which cannot be reached transthoracicaliy, located in the innertwo thirdsof the lung can be approached. Main research question To assess diagnostic yield of the novel Standard of care 'Virtual bronchoscopy navigation" procedure. Design (including population, confounders/outcomes) A single centre, prospective, observational study of patients undergoing the novel Standard of care Virtual bronchoscopy navigation procedure to assess a pulmonary nodule. Clinical data of at least 100 consecutive patients will be collected.
This study evaluates the viability and accuracy of preoperative mixed reality technique combined with three-dimensional printing navigational template guided localizing pulmonary small nodules.
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.