RecruitingNCT05018663

Artificial Intelligence (AI) Cytopathology Trial

Artificial Intelligence for Rapid On-site Evaluation (AI-ROSE) for Endoscopic Ultrasound-guided Fine-needle Aspiration (EUS-FNA) Biopsy of Pancreatic Solid Lesions: A Prospective Double Blinded Study


Sponsor

The University of Texas Health Science Center, Houston

Enrollment

50 participants

Start Date

Jul 21, 2021

Study Type

OBSERVATIONAL

Conditions

Summary

Purpose The primary objective of the study is to compare interpretation of EUS FNA/FNB samples for adequacy between ROSE and AI at bedside. To compare accuracy of preliminary diagnosis results between ROSE and AI at bedside versus final pathology report. Research design This is a prospective single center study to compare performance characteristics in the interpretation of EUS FNA/FNB samples between AI and ROSE. Procedures to be used Eligible patients will undergo EUS guided FNA/FNA of PSLs using standard of care. Sample slides are prepared by a cytopathologist at bedside and observed under a microscope. At the same time, the slides are scanned using a slide scanner and those images are saved for interpretation by AI at a later time.


Eligibility

Min Age: 18 YearsMax Age: 100 Years

Plain Language Summary

Simplified for easier understanding

This clinical trial is studying Artificial Intelligence software ROSE for people with pancreatic solid lesions. The study is currently recruiting participants at 1 location.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

OTHERArtificial Intelligence software ROSE

Rapid on-site evaluation (ROSE) of Endoscopic Ultrasound (EUS) guided FNA/FNB (Fine Needle Aspirate/Fine Needle Biopsy) of pancreatic solid lesions (PSLs) has been shown in improve diagnostic yield. The availability and performance of ROSE at EUS performing centers is variable. With strides in Artificial Intelligence (AI) capabilities over the years, the University of Texas at Health Sciences Center at Houston in collaboration with Haystac is developing an artificial intelligence based proprietary system to analyze slides from EUS FNA/FNB samples at bedside.


Locations(1)

Memorial Hermann Hospital

Houston, Texas, United States

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NCT05018663