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NCT Number: NCT05018663

Artificial Intelligence (AI) Cytopathology Trial

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.

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Key information

Conditions

Pancreatic Solid Lesions

Age range

18 year–100 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Have EUS finding of a PSL;
  • Do not have contraindications for FNA/FNB.

Exclusion criteria

  • Inability to provide informed consent for the procedure;
  • Contraindication for FNA/FNB eg coagulopathy, lack of avascular window for FNA.

Treatment and study plan

Artificial Intelligence software ROSE

Other

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.

Primary outcomes

  1. Detection the adequacy for diagnosis

    Time frame: During procedure

    The primary outcome of the study is to determine how AI compares with ROSE in determining if EUS FNA/FNB sample from PSLs is adequate for diagnosis. This will be interpreted as a percentage in each group. The main study parameter is on-site determination if an EUS FNA/FNB sample is adequate for interpretation and diagnosis

Secondary outcomes

  1. Comparing the accuracy between preliminary diagnosis

    Time frame: During procedure

    To compare the accuracy between AI and ROSE preliminary diagnosis versus the final pathology report.

    Interpretation of preliminary results will be divided into categories of benign vs malignancy, acinar cells vs ductal cells in benign, adenocarcinoma vs neuroendocrine tumor vs other in malignancy.

Study contacts

Contact information is provided by the study sponsor or research team.

Prithvi B Patil, MS

CONTACT

[email protected]

7135006456

Sponsors and collaborators

Lead sponsor

The University of Texas Health Science Center, Houston

Other

Registry information

Official study title

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

Important dates

Study start
2021
Primary completion
2024
Study completion
2028
First posted
Aug 24, 2021
Registry last updated
Feb 16, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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