Artificial Intelligence (AI) Cytopathology Trial
Study Details
Study Description
Brief 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.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Prospective enrollment 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.
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Outcome Measures
Primary Outcome Measures
- Detection the adequacy for diagnosis [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 Outcome Measures
- Comparing the accuracy between preliminary diagnosis [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.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Have EUS finding of a PSL;
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Do not have contraindications for FNA/FNB.
Exclusion Criteria:
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Inability to provide informed consent for the procedure;
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Contraindication for FNA/FNB eg coagulopathy, lack of avascular window for FNA.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Memorial Hermann Hospital | Houston | Texas | United States | 77030 |
Sponsors and Collaborators
- The University of Texas Health Science Center, Houston
Investigators
- Principal Investigator: Nirav Thosani, MD, MHA, The University of Texas Health Science Center, Houston
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- HSC-MS-21-0051