NCT04816981: AI-EBUS-E

AI-EBUS-Elastography for LN Staging

Completed NA Last updated 18 January 2024

What this trial tests

NA trial testing EBUS-Elastography in Artificial Intelligence in 100 participants. Completed in 1 May 2022.

Timeline

1 September 2021

Primary endpoint
1 May 2022

1 May 2022

Quick facts

Lead sponsor	St. Joseph's Healthcare Hamilton
Phase	NA
Status	Completed
Study type	INTERVENTIONAL
Allocation	na
Design	single group
Masking	none
Primary purpose	diagnostic
Enrollment	100
Start date	1 September 2021
Primary completion	1 May 2022
Estimated completion	1 May 2022
Sites	1 location across Canada

Drugs / interventions tested

• EBUS-Elastography

Conditions studied

• Artificial Intelligence — all drugs for Artificial Intelligence →
• Endobronchial Ultrasound — all drugs for Endobronchial Ultrasound →
• Elastography — all drugs for Elastography →
• NSCLC — all drugs for NSCLC →

Sponsor

St. Joseph's Healthcare Hamilton — full company profile →

Who can join

18 and older, any sex, with Artificial Intelligence or Endobronchial Ultrasound. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Before any treatment decisions are made for patients with lung cancer, it is crucial to determine whether the cancer has spread to the lymph nodes in the chest. Traditionally, this is determined by taking biopsy samples from these lymph nodes, using the Endobronchial Ultrasound Transbronchial Needle Aspiration (EBUS-TBNA) procedure. Unfortunately, in 40% of the time, the results of EBUS-TBNA are not informative and wrong treatment decisions are made. There is, therefore, a recognized need for a better way to determine whether the cancer has spread to the lymph nodes in the chest. The investigators believe that elastography, a recently discovered imaging technology, can fulfill this need. In this study, the investigators are proposing to determine whether elastography can diagnose cancer in the lymph nodes. Elastography determines the tissue stiffness in the different parts of the lymph node and generates a colour map, where the stiffest part of the lymph node appears blue, and the softest part appears red. It has been proposed that if a lymph node is predominantly blue, then it contains cancer, and if it is predominantly red, then it is benign. To study this, the investigators have designed an experiment where the lymph nodes are imaged by EBUS-Elastography, and the images are subsequently analyzed by a computer algorithm using Artificial Intelligence. The algorithm will be trained to read the images first, and then predict whether these images show cancer in the lymph node. To evaluate the success of the algorithm, the investigators will compare its predictions to the pathology results from the lymph node biopsies or surgical specimens.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Clinical utility of artificial intelligence-augmented endobronchial ultrasound elastography in lymph node staging for lung cancer.
   Patel YS, Gatti AA, Farrokhyar F, Xie F, et al · · 2024 · cited 6× · PMID 39478913 · DOI 10.1016/j.xjtc.2024.06.024