Spots Global Cancer Trial Database for Augmented Endobronchial Ultrasound (EBUS-TBNA) With Artificial Intelligence

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Trial Identification

Brief Title: Augmented Endobronchial Ultrasound (EBUS-TBNA) With Artificial Intelligence

Official Title: Automatic Segmentation of Mediastinal Lymph Nodes and Blood Vessels in Endobronchial Ultrasound (EBUS) Images Using a Deep Neural Network

Study ID: NCT05739331

Conditions

Artificial Intelligence

Endobronchial Ultrasound

Lung Cancer

Interventions

machine learning algorithm

Study Description

Brief Summary: To evaluate the usefulness of Deep neural network (DNN) in the evaluation of mediastinal and hilar lymph nodes with Endobronchial ultrasound (EBUS). The study will explore the feasibility of DNN to identify lymph nodes and blood vessel examined with EBUS.

Detailed Description: Multi-center prospective feasibility study. The DNN model will be trained on ultrasound images with annotation to identifies lymph nodes and blood vessels examined with EBUS. The ability of the DNN to segment lymph nodes and vessels based on postoperative processing and static EBUS images will be evaluated in the first part of the study. In the second part of the study Real-time use of DNN in EBUS procedure will be evaluated.