Study on AI-assisted Multimodal Diagnosis System of Autoimmune Pancreatitis Based on the Mechanism of Tfh Activation by Intestinal Bacteria and Endosonographic Features
Trial ID: NCT06369909
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2024-01-31
Completion date: 2026-01-31
Sponsor: Peking Union Medical College Hospital
Collaborators: Tianjin Medical University General Hospital; The Second Hospital of Hebei Medical University
Conditions: Autoimmune Pancreatitis
Interventions: EUS-FNA
Locations: Peking Union Medical College Hospital, Chinese Academy of Medical Sciences
Countries: China
Enrollment: 180
Age range: 18 Years - 80 Years
Sex: ALL

Summary:
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.

Eligibility criteria:
Inclusion Criteria:

* From the beginning of the study to the end of the study, patients with pancreatic solid lesions suspected or diagnosed with AIP were treated at Peking Union Medical College Hospital and related research centers.
* The patients themselves and their families understood and were willing to participate in this study, and signed an informed consent form.
* The diagnosis of AIP must comply with the criteria of the Chinese Guidelines for the Diagnosis and Treatment of Autoimmune Pancreatitis (2022).

Exclusion Criteria:

* Individuals who are not suitable for endoscopic examination, including but not limited to: generally poor condition, severe cardiovascular and pulmonary diseases, and difficulty tolerating the examination, coagulation disorders and those who are deemed unsuitable for endoscopic examination by an endoscopist after a face-to-face consultation.
* Patients or family members are unable to understand the conditions and objectives of this study.

Outcomes:
Tfh level in blood; Microbiota composition measured by 16S rRNA sequencing; AI-EUS differentiation; Cytokine level in blood; Single cell sequencing