Clinical Research Directory

Using Biomarkers for Diagnosis, Risk Stratification of Post -Treatment Recurrence and Long-Term Surveillance of Lung Cancer

This study is an observational study of blood and tissue biomarkers. Investigators plan to evaluate the accuracy of lung cancer biomarkers found in the blood in determining if a lung nodule is cancer or benign. Investigators also plan to examine another biomarker found in the tumor tissue to identify participants after lung cancer surgery who have a high risk for recurrent cancer. Finally, investigators plan to determine if one of the blood-based biomarkers can be used to detect any late cancer recurrence.

InAdvance: Surveillance, Prevention, and Interception in a Population at Risk for Cancer

This research study is creating a way to collect and store specimens and information from participants who may be at an increased risk of developing cancer, or has been diagnosed with an early phase of a cancer or a family member who has a family member with a precursor condition for cancer. * The objective of this study is to identify exposures as well as clinical, molecular, and pathological changes that can be used to predict early development of cancer, malignant transformation, and risks of progression to symptomatic cancer that can ultimately be fatal. * The ultimate goal is to identify novel markers of early detection and risk stratification to drive potential therapeutic approaches to intercept progression to cancer.

Using e-Nose Technology to Identify Early Lung Cancer

The purpose of this study is to test the ability of a new technology called breathprinting, or electronic nose (e-nose), to detect early-stage lung cancer. Additionally, researchers also want to see if the e-nose technology is more effective at diagnosing lung cancer if the tumor size is larger.

Development and Demonstration of Intelligent Assessment Based on Multi-modal Information Fusion for Tumor Risk and Diagnosis and Treatment

To improve the accuracy of risk prediction, screening and treatment outcome of cancer, we aim to establish a medical database that includes standardized and structured clinical diagnosis and treatment information, image features, pathological features, and multi-omics information and to develop a multi-modal data fusion-based technology system using artificial intelligence technology based on database.

From Benchmark to Surgical Activity: the Role of Endobronchial Fiducial Markers for Ground Glass Lung Nodules Resection.

With the risen popularity of low-dose computed tomography (LDCT) for lung cancer screening, many patients present with peripheral pulmonary ground-glass nodules (GGNs) with a suspicious solid part. The appropriate diagnostic and management strategy for those lesions can be questionable. If malignancy is suspected, a surgical biopsy with the guidance of various localization methods available is recommended. Each localization method has its advantages and disadvantages. Therefore, it may not be possible to establish a gold standard for localizing indeterminate lung nodules since comparative clinical trials are lacking.

Molecular Analysis of Endoscopic Cytology Samples Supernatant in Pulmonary Nodules

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

Prospective rAndomized sTudy efficaCy tHree-dimensional rEconstructions Segmentectomy

With this project we want to study the effectiveness of 3D reconstruction of preoperative CT to reduce operating times, blood loss and conversions after segmentectomy performed in thoracoscopy / robotics.

Artificial Intelligence System for Assessment of Tumor Risk and Diagnosis and Treatment

To improve the accuracy of risk prediction, screening and treatment outcome of cancer, we aim to establish a medical database that includes standardized and structured clinical diagnosis and treatment information, image features, pathological features, and multi-omics information and to develop a multi-modal data fusion-based technology system using artificial intelligence technology based on database.