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NCT06369909

Study on AI-assisted Multimodal Diagnosis System of Autoimmune Pancreatitis

Recruiting now Last updated 25 November 2024
What this trial tests

trial testing EUS-FNA in Autoimmune Pancreatitis in 180 participants. Currently enrolling.

Timeline
31 January 2024
Primary endpoint
31 January 2025
31 January 2026

Quick facts

Lead sponsorPeking Union Medical College Hospital
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment180
Start date31 January 2024
Primary completion31 January 2025
Estimated completion31 January 2026
Sites1 location across China

Drugs / interventions tested

Conditions studied

Sponsor

Peking Union Medical College Hospital

Who can join

Adults 18 to 80, any sex, with Autoimmune Pancreatitis. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The existing comprehensive diagnostic system for autoimmune pancreatitis (AIP) is complex, with multidimensional clinical information including morphological changes and a lack of specific biomarkers. Endoscopic ultrasound (EUS) can provide all the elements for morphological diagnosis of AIP, but the long learning curve and large observer differences make it difficult to popularize and promote. The cooperation units of the three regions in this project have found in the early stage that Klebsiella pneumoniae (KP) induced follicular helper T cells (Tfh) activation is an important mechanism of AIP, but the identification of pathogenic components of the strain and clinical validation need to be explored. We have established a national multicenter AIP queue in the early stage and extracted EUS audio-visual features to establish a scoring model, but intelligent assistance is still needed to improve efficiency. Therefore, we plan to integrate gut microbiota, Tfh activation markers, and EUS imaging features to establish an AI assisted multimodal diagnostic system for AIP. This study will collaborate across multiple centers to identify and validate the components that induce Tfh activation in KP bacterial cells, to extract EUS pancreatic ultrasound features and optimize artificial intelligence assisted diagnostic algorithms, and to establish and validate an artificial intelligence assisted multimodal diagnostic system based on clinical information, biomarkers, and EUS. The aim of this study is to provide new diagnosis and treatment evaluation methods for AIP with high accuracy, convenience, and easy promotion for clinical practice.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other trials of EUS-FNA

Trials testing the same drug.

Other Peking Union Medical College Hospital trials

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Data sources for this page

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