An observational study in Pancreatic Disease, sponsored by Ruijin Hospital. Recruiting at 2 sites in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-02-13.
Sponsored by Ruijin Hospital · Observational
The objective of this observational study is to investigate whether the self-developed whole slide scanning and artificial intelligence diagnostic system for pancreatic solid lesion puncture cytopathology (hereinafter referred to as the "Zhiying Shunxi" ROSE-AI diagnostic system) can promptly and accurately diagnose solid pancreatic lesions (SPLs). The main question it aims to answer is:
By utilizing optical imaging technology to capture RGB images of Diff-Quik stained smears from pancreatic punctures, can the development of artificial intelligence algorithms assist in differentiating solid pancreatic space-occupying diseases (such as pancreatic ductal adenocarcinoma, pancreatic neuroendocrine tumors, and non-neoplastic benign lesions)?
Researchers will compare the diagnoses of SPLs made by the ROSE-AI system with the actual pathological diagnoses of the SPLs themselves to determine whether the ROSE-AI system can effectively diagnose SPLs.
171 studies on the registry are indexed under Pancreatic Diseases; 64 are open to participants now.
This study's planned enrollment of 1,500 is above the median of 330 across 82 observational studies indexed under Pancreatic Diseases.
Browse Pancreatic Diseases studies →Ruijin Hospital is the lead sponsor of 668 studies on the registry; 377 are open to participants now.
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All patients were obtained due to the necessity for disease treatment and in accordance with routine clinical workflows, and finally were confirmed as pancreatic ductal adenocarcinoma, pancreatic neuroendocrine tumors, and non-neoplastic benign lesions.
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Exclusion Criteria:
Device: ROSE-AI diagnostic system
Device: ROSE-AI diagnostic system
Device: ROSE-AI diagnostic system
All samples were obtained due to the necessity for disease treatment and in accordance with routine clinical workflows. After the pathological diagnoses were confirmed by the pathology departments of the hospitals affiliated with the respective endoscopic centers, the eligible pancreatic puncture Diff-Quik stained smears were borrowed and transferred to Ruijin Hospital Affiliated to School of Medicine, Shanghai Jiao Tong University. There, the self-developed "Zhiying Shunxi" system was used to capture corresponding traditional light microscope RGB images. After the imaging was completed, all specimens were returned to the endoscopic centers from which they originated. Using the RGB images as input, an artificial intelligence algorithm was developed to assist in differentiating solid pancreatic lesions.
Accuracy
Accuracy = (TP + TN) / (TP + FP + FN + TN)
Time frame: through study completion, an average of 2 years
Plan to share: Undecided
No publications or documents are linked to this record.
Started Dec 2024 (actual). Primary completion is estimated for May 2027, 29 months after the start.
Of 45 observational studies under Pancreatic Diseases, half reached primary completion within 56 months of starting (the median), counting those still running; a quarter within 22 and three quarters within 119. This study's planned 29 months is below that.
How these figures are worked out, and which studies are left out of them.
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