Active clinical trials for "Lung Neoplasms"

This is a clinical trial using retrospective data of two different software devices developed by Riverain Medical Group: Softview and OnGuard 5.0. The two studies will be run concurrently. Riverain Medical Group's computer systems are designed to assist radiologists in their identification of lung cancer on chest radiographs. The current machine received FDA Pre-Market Approval. This is to test two new software approaches.

In this prospective study, the investigators will evaluate and compare the usefulness of functional and volumetric informations obtained by 18F-FDG PET and MRI before and after the palliative chemotherapy with the aim of predicting tumor response and prognosis in patients with advanced Non-small Cell Lung Cancer (NSCLC).

The purpose is to characterize tumour biological markers in brain metastases tissue from patients with different primary tumour by using ex vivo techniques as high-resolution magic angle spinning MR spectroscopy and micro array.

Occupational exposure to asbestos is known increase the risk of developing cancer of the lungs (bronchogenic carcinoma) or of the pleura (mesothelioma). Symptoms are subtle and non-specific, diagnosis is often late and the prognosis consequently is dismal. Currently there is no accepted non-invasive tool for the early diagnosis of mesothelioma or lung cancer in asbestos-exposed subjects. In the last decade, low-dose computed tomography (LDCT) has been successfully developed and validated for the early diagnosis of lung cancer in high-risk smokers. Malignant mesothelioma might, in an early stage, resemble a benign pleural plaque, which is a common finding after asbestos exposure. We target to develop low-dose CT as a tool to serially image the pleural plaques, quantify their individual and overall volume, compute the growth rate with time, and, as such, identify the presence of mesothelioma early, before symptoms occur.

This is a prospective study of surgically resected samples and lymph nodes of lung cancer patients. For histopathologically positive lymph nodes from a complete resection, the investigators would like to analyse tumor tissue by allelotyping and comparing these results with those observed in the primary lung tumor to establish a cartography of molecular alteration in resected lung cancer. For non histopathologically positive lymph nodes, the investigators would like to research the presence (or not) of micrometastasis by allele-specific PCR (polymerase chain reaction).

The purpose of this study is to learn more about the metabolic properties of lung cancer cells.

The investigators will develop a radiomics signature for immune checkpoint-induced pneumonitis in 40 patients with a pulmonary event under anti-PD1 or anti-PD-L1 (cases) and 40 patients without a pulmonary event under anti-PD1 or anti-PD-L1 (controls). On the basis of the case-control study of patients treated with anti-PD1 or anti-PD-L1, they will further optimise the model using reinforcement machine learning. The model will then be validated in 300 prospective patients.

Currently, publicly funded standard of care testing in Ontario for stage IV lung cancer patients uses individual gene tests to look for mutations in the EGFR and ALK genes. This testing broadens treatment options for patients, however there are other gene mutations with corresponding targeted treatments that are not routinely tested for. This study will evaluate the utility and added value of using a next generation sequencing (NGS) panel, the Oncomine Comprehensive Assay v3, to profile stage IV lung cancer patients.

Machine learn a predictive model from more than 20.000 non-small cell lung cancer patients from more than 5 health care providers from more than 5 countries.

The primary objective of this study is to obtain de-identified, clinically characterized, whole blood specimens for use in assessing new biomarkers for the detection of neoplasms of the lung. Subjects will be men and women, 35 years of age and older, with a CT confirmed nodule measuring 6-30 mm.