View clinical trials related to Multiple Pulmonary Nodules.
Filter by:Lung cancer screening is based on low dose CT scan (LDCT), a highly sensitive but poorly specific tool. Complementary specific approaches are thus strongly needed, among which cell-free DNA (cfDNA) genotyping has been proven highly specific but of low sensitivity (25 to 50% for stage I diseases) due to inconstant tumor shed. Tumor biopsy is thus often required and radial endobronchial ultrasound (rEBUS) bronchoscopy is a minimally invasive approach (<3% complications) but of limited sensitivity in cases of nodules < 20 mm. The investigators hypothesized that methylation analysis on cfDNA floating in supernatant derived from rEBUS specimens could improve rEBUS sensitivity
A monocentric prospective and randomized trial aiming to compare the diagnostic yield and safety of electromagnetical-guided bronchoscopy (ENB) procedures coupled to trans-bronchial lung cryobiopsies for the diagnosis of pulmonary nodule when performed either in a "standard" bronchoscopy suite or in a hybrid room with CBCT guidance and the use of the CrossCountry technique as required.
In pulmonary oncology, the diagnosis of medium-sized pulmonary nodules (10 to 20 mm), too distal to be reached by standard bronchial fibroscopy but remaining proximal, is difficult. There are 2 techniques: transthoracic puncture-biopsy under CT scan, usually performed by radiologists, and distal sampling guided by radial ultrasound mini-probe. The limitations of the last technique could be overcome by the use of cryoprobes for sampling, as they would take more tissue by freezing.
This study aimed to develop a deep-learning model to automatically classify pulmonary nodules based on white-light images and to evaluate the model performance. Besides, suitable operation could be chosen with the help of this model, which could shorten the time of surgery.
Correlate performance of LungLB Test with outcome of a scheduled biopsy.
With the popularization of CT screening, the detection rate of small lung nodules has greatly increased. Therefore, the clinical thoracoscopic lung nodule biopsy and sub-lobectomy for radical resection of lung cancer are greatly required. Accurate resection of lung nodule depends on precise localization of pulmonary nodules. However, preoperative CT-guided Hook-wire positioning under local anesthesia, which is the current primary localization method, requires high equipment and expense, and may cause physical and mental trauma to the patient. Augmented reality (AR) is an innovative technology that superimpose a virtual scene into the real environment by fusing images, videos, or computer-generated models with patients during surgical operations. It can visually display the anatomical structures of organs or lesions, which significantly improves surgical efficiency. This project intends to use AR technology to localize the solitary pulmonary nodule (SPN) before surgery, compared with CT-guided Hook-wire localization. Compared with the localization of SPNs under CT guidance, AR-assisted localization technology apparently is less time-consuming and can be performed immediately before surgery under general anesthesia, lessening pain, reduce costs of time and equipment, increase the success rate of sub-lobectomy, and improve the overall efficiency of surgical treatment of pulmonary nodules.
This study is a retrospective multi-center chart review of patients who underwent an attempted biopsy of one or more pulmonary lesion(s) with the Ion Endoluminal System with the aim of assessing the overall performance of the system.
Early diagnosis of LC in the asymptomatic stage through intentional screening programs and/or incidental pulmonary nodule identification and follow-up are known to improve outcomes significantly. There are large gaps in the screening and early detection of LC, especially in LMIC - driven by multifactorial aspects, including a variety of socioeconomic and infrastructural factors, mainly due to limitations in the required network of specialized human resources and technical capacity. Identifying LC at an early stage allows for treatment that is more likely to be curative, thereby improving survival. The present study aims to characterize the lung nodule journey in different hospitals/clinics across Latin America, describing the use of health resources, time to diagnosis, stage at diagnosis, and time to treatment depending on the source of nodule identification in two different cohorts (retrospective and prospective).
Computed tomography (CT) is critical for the diagnosis of lung nodules as well as for therapeutic management. Repeated CT examinations will raise the issue of the cumulative radiation dose and subsequent risk of cancer, thus pushing the need for imaging techniques using low or no radiation dose. Magnetic Resonance Imagery (MRI) with ultrashort echo time (UTE) pulse sequences with high signal-to-noise and spatial resolution is a promising alternative for lung nodules imaging.The purpose of the study is to evaluate the value of dynamic contrast-enhanced MR imaging (DCE-MRI) to discriminate of malignant from benign lesions.
The purpose of this study is to determine if a liquid biopsy, a method of detecting cancer from a blood draw, combined with a PET/CT scan, a type of radiological scan, is better at determining whether a lung nodule is cancerous when compared to a PET/CT scan alone. A PET/CT scan is already used for diagnosis of lung nodules, but its efficacy is uncertain in nodules 6-20 mm in size. Therefore, the PET/CT will be evaluated for its diagnostic ability in lesions this size alone and in combination with a liquid biopsy. Secondarily, a machine learning model will be created to see if the combination of the PET/CT imaging data and the liquid biopsy data can predict the presence of cancer.