View clinical trials related to Pleural Diseases.
Filter by:This study aims to investigate the accuracy of using pleural ultrasound (USP) to identify pleural adhesions in patients who plan to receive video-assisted thoracoscopic surgery. It employs three-dimensional convolutional neural network (3D-CNN) technology to process USP-related images and video data for machine learning, and to establish a diagnostic model for identifying pleural adhesions using 3D-CNN-USP. The study will determine the sensitivity, specificity, positive predictive value, and negative predictive value of 3D-CNN-USP in identifying pleural adhesions. Additionally, it will explore the feasibility and effectiveness of using 3D-CNN-USP for preoperative identification of pleural adhesions in VATS, thereby supporting the implementation of day surgery in thoracic surgery and ultimately serving clinical practice.
1. To evaluate the diagnostic yield and safety of thoracoscopic pleural lavage and pleural brushing in cases of undiagnosed exudative pleural effusion.
High resolution computed tomography of the chest is the gold standard imaging modality for most pulmonary diseases. However, the associated high expenses, radiation exposure , and its limited possibility for bedside use are a limitation.