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Pulmonary Nodules, Multiple clinical trials

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NCT ID: NCT06187935 Recruiting - Clinical trials for Pulmonary Nodules, Solitary

Early Adjuvant Diagnosis of Pulmonary Nodules Based on CTC.

Start date: March 1, 2018
Phase:
Study type: Observational

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.

NCT ID: NCT06075836 Active, not recruiting - Pleural Effusion Clinical Trials

AI Assisted Detection of Chest X-Rays

AID-CXR
Start date: October 31, 2023
Phase:
Study type: Observational

This study has been added as a sub study to the Simulation Training for Emergency Department Imaging 2 study (ClinicalTrials.gov ID NCT05427838). The Lunit INSIGHT CXR is a validation study that aims to assess the utility of an Artificial Intelligence-based (AI) chest X-ray (CXR) interpretation tool in assisting the diagnostic accuracy, speed, and confidence of a varied group of healthcare professionals. The study will be conducted using 500 retrospectively collected inpatient and emergency department CXRs from two United Kingdom (UK) hospital trusts. Two fellowship trained thoracic radiologists will independently review all studies to establish the ground truth reference standard. The Lunit INSIGHT CXR tool will be used to analyze each CXR, and its performance will be measured against the expert readers. The study will evaluate the utility of the algorithm in improving reader accuracy and confidence as measured by sensitivity, specificity, positive predictive value, and negative predictive value. The study will measure the performance of the algorithm against ten abnormal findings, including pulmonary nodules/mass, consolidation, pneumothorax, atelectasis, calcification, cardiomegaly, fibrosis, mediastinal widening, pleural effusion, and pneumoperitoneum. The study will involve readers from various clinical professional groups with and without the assistance of Lunit INSIGHT CXR. The study will provide evidence on the impact of AI algorithms in assisting healthcare professionals such as emergency medicine and general medicine physicians who regularly review images in their daily practice.

NCT ID: NCT04482114 Active, not recruiting - Clinical trials for Pulmonary Nodules, Multiple

Detection and Volumetry of Pulmonary Nodules on Ultra-low Dose Chest CT Scan With Deeplearning Image Reconstruction Algorithm (DLIR)

DLIRTHORAX
Start date: July 22, 2020
Phase: N/A
Study type: Interventional

evaluate the diagnostic performance of ultra-low dose CT using deep learning-based reconstruction in the detection of pulmonary nodules.