Artificial Intelligence (AI) Cytopathology Trial
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|ClinicalTrials.gov Identifier: NCT05018663|
Recruitment Status : Recruiting
First Posted : August 24, 2021
Last Update Posted : September 16, 2021
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.
|Condition or disease||Intervention/treatment|
|Pancreatic Solid Lesions||Other: Artificial Intelligence software ROSE|
|Study Type :||Observational|
|Estimated Enrollment :||50 participants|
|Official 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|
|Actual Study Start Date :||July 21, 2021|
|Estimated Primary Completion Date :||July 31, 2024|
|Estimated Study Completion Date :||January 30, 2028|
All subjects will be enrolled prospectively. Subjects will be included in the study after eligibility is assessed and informed consent is obtained. The slide scanner will scan the slides on site and the images will be securely saved and sent for interpretation by the AI software at a different location. The results of the AI interpretation of the slides will be blinded to the on-site procedure team including the endoscopist and cytopathologist until the final pathology report is complete.
Other: Artificial 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.
- 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
- 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.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05018663
|Contact: Prithvi B Patil, MSemail@example.com|
|United States, Texas|
|Memorial Hermann Hospital||Recruiting|
|Houston, Texas, United States, 77030|
|Contact: Prithvi B Patil 713-480-1179 firstname.lastname@example.org|
|Contact: Prithvi Patil, MS 7135006456 email@example.com|
|Principal Investigator: Nirav Thosani, MD,MHA|
|Principal Investigator:||Nirav Thosani, MD, MHA||The University of Texas Health Science Center, Houston|