Developing a Machine Learning Model to Predict Pleural Adhesion Preoperatively Using Pleural Ultrasound

Launched by PEKING UNION MEDICAL COLLEGE HOSPITAL · May 15, 2024

Keywords

ClinConnect Summary

This clinical trial is looking at how well a special type of ultrasound, called pleural ultrasound, can help doctors identify pleural adhesions in patients who are preparing for a surgery known as video-assisted thoracoscopic surgery (VATS). Pleural adhesions are areas where the layers around the lungs stick together, which can complicate surgery. The researchers are using advanced technology, called a 3D convolutional neural network, to analyze images from the ultrasound. Their goal is to see how accurately this method can detect pleural adhesions before surgery, which could make the process safer and more efficient for patients.

To be eligible for this study, patients need to be planning to undergo VATS surgery. However, those who cannot provide complete medical information or who have skin issues in the area being examined will not be able to participate. Participants in this trial can expect to undergo pleural ultrasound as part of the study, which will help researchers understand if this technology can improve surgical outcomes. The study is not yet recruiting participants, but it aims to support better patient care in thoracic surgery in the future.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • 1. Patients who plan to accept VATS surgery.
• Exclusion Criteria:
• • 1. Patients who can not obtain detailed clinical information;
• • 2. Patients or their family members who can not understand the conditions and objectives of the study or refuse to participate in the study;
• • 3. Patients with conditions affecting observation, such as skin lesions, infections, or scars in the area of the chest wall to be examined.