Spots Global Cancer Trial Database for The Use of Artificial Intelligence to Predict Cancerous Lymph Nodes for Lung Cancer Staging During Ultrasound Imaging
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Trial Identification
Brief Title: The Use of Artificial Intelligence to Predict Cancerous Lymph Nodes for Lung Cancer Staging During Ultrasound Imaging
Official Title: Development and Validation of a Computer-aided Algorithm Using Artificial Intelligence and Deep Neural Networks for the Segmentation of Ultrasonographic Features of Lymph Nodes During Endobronchial Ultrasound
Study ID: NCT03849040
Interventions
Study Description
Brief Summary: This study aims to determine if a deep neural artificial intelligence (AI) network (NeuralSeg) can learn how to assign the Canada Lymph Node Score to lymph nodes examined by endobronchial ultrasound transbronchial needle aspiration(EBUS-TBNA), using the technique of segmentation. Images will be created from 300 lymph nodes videos from a prospective library and will be used as a derivation set to develop the algorithm. An additional100 lymph node images will be prospectively collected to validate if NeuralSeg can correctly apply the score.
Detailed Description:
Eligibility
Minimum Age: 18 Years
Eligible Ages: ADULT, OLDER_ADULT
Sex: ALL
Healthy Volunteers: No
Locations
St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
Contact Details
Name: Wael C Hanna
Affiliation: St. Josephs Healthcare Hamilton
Role: PRINCIPAL_INVESTIGATOR
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