Validation of Joint-AI in Diagnosing Pancreatic Solid Lesions

NCT06753318 | Not Yet Recruiting

• 1 other identifier: Joint-AI 2024
• Study Type: interventional
• Target: 716
• Locations: 1 country
• Sites: 1

Brief Summary

This clinical trial aims to learn if a multimodal artificial intelligence (AI) model can enhance the diagnosis of pancreatic solid lesions. The main questions it aims to answer are:

1. 1.Does the AI model enhance the diagnostic performance of endoscopists in diagnosing pancreatic solid lesions?
2. 2.Does the addition of interpretability analysis further improve the diagnostic performance of the assisted endoscopists? Researchers will compare the diagnostic performance of endoscopists with or without the assistance of the AI model.
3. 3.Their clinical data will be prospectively collected.
4. 4.They will be randomized to the AI-assist group and the conventional diagnosis group.

Conditions

Pancreatic Cancer; Pancreatitis; Pancreatic Neuroendocine Neoplasms (pNETs); Autoimmune Pancreatitis; Solid Pseudopapillary Neoplasm of the Pancreas

Keywords

pancreatic cancer; artificial intelligence; endoscopic ultrasound

Outcome Measures

Primary Outcomes (2)

• Rate of correct diagnostic classification with assistance of the Joint-AI Model

  The rate of correct diagnoses in discriminating pancreatic cancer from other non-cancer lesions, determined by comparing endoscopist diagnosis assisted by the Joint-AI model against the final histopathological diagnosis (reference standard).

  Through study completion, an average of 1 year

• Rate of correct diagnostic classification with assistance of the Interpretable Joint-AI Model

  The rate of correct diagnoses in discriminating pancreatic cancer from other non-cancer lesions, determined by comparing endoscopist assessments assisted by the Interpretable Joint-AI model against the final histopathological diagnosis (reference standard)

  Through study completion, an average of 1 year

Secondary Outcomes (3)

• Rate of correct diagnostic classification of the Joint-AI model and the interpretable Joint-AI model

  Through study completion, an average of 1 year

• Endoscopist-reported confidence score in diagnosis with AI assistance (the score is on a scale of 0%-100%, where 0 represents "not confident at all" and 100 represents "completely confident")

  Through study completion, an average of 1 year

• Rate of correct diagnostic classification of endoscopists without AI assistance

  Through study completion, an average of 1 year

Study Arms (3)

Conventional diagnosis

NO INTERVENTION

Endoscopists diagnose pancreatic solid lesions according to endoscopic ultrasound images and clinical data.

Joint-AI assisted diagnosis

EXPERIMENTAL

Endoscopists diagnose pancreatic solid lesions based on endoscopic ultrasound images, clinical data, and predictions made by the Joint-AI model.

Diagnostic Test: The assistance of the Joint-AI model

Interpretable Joint-AI assisted diagnosis

EXPERIMENTAL

Endoscopists diagnose pancreatic solid lesions based on endoscopic ultrasound images, clinical data, predictions given by the Joint-AI, and interpretability analysis results used to improve the transparency of the decision-making process of the Joint-AI model.

Diagnostic Test: The assistance of the interpretable Joint-AI model

Interventions

The assistance of the Joint-AI model DIAGNOSTIC_TEST

Predictions given by the Joint-AI model will be provided to the endoscopists during their diagnosis

Joint-AI assisted diagnosis

The assistance of the interpretable Joint-AI model DIAGNOSTIC_TEST

Predictions given by the Joint-AI model and the results of the interpretability analysis will be provided to the endoscopists during their diagnosis

Interpretable Joint-AI assisted diagnosis

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Imaging examinations (MRI, CT, B-ultrasound) show a solid mass in the pancreas, which requires endoscopic ultrasound guided-fine needle aspiration/biopsy (EUS-FNA/B) to clarify the nature of the lesion in patients.
• Written consent provided

You may not qualify if:

• Age under 18 years old

Sponsors & Collaborators

• Huazhong University of Science and Technology: lead
• Beijing Union Hosptial: collaborator
• Affiliated Drum Tower Hospital of Nanjing University Medical School: collaborator
• Shanghai Longhua Hospital: collaborator
• Beijing Friendship Hospital: collaborator
• Qilu Hospital of Shandong University: collaborator
• Sir Run Run Shaw Hospital: collaborator

Study Sites (1)

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, 430030, China

Location

MeSH Terms

Conditions

Pancreatic Neoplasms; Pancreatitis; Autoimmune Pancreatitis

Condition Hierarchy (Ancestors)

Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Endocrine Gland Neoplasms; Digestive System Diseases; Pancreatic Diseases; Endocrine System Diseases; Pancreatitis, Chronic; Autoimmune Diseases; Immune System Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Bin Cheng

CONTACT

86-13986097542; b.cheng@tjh.tjmu.edu.cn

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Masking Details: During the endoscopic ultrasound procedure, the allocation of participants will be masked to the endoscopists
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Model Details: 1. First, participants are randomized into three parallel groups: conventional diagnosis group, Joint-AI assistance group, and Interpretable Joint-AI assistance group. 2. For participants within the Joint-AI assistance group and Interpretable Joint-AI assistance group, their groups will be switched after a washout period.

Study Record Dates

• First Submitted: December 17, 2024
• First Posted: December 31, 2024
• Study Start: January 1, 2025
• Primary Completion: January 1, 2026
• Study Completion: January 1, 2026
• Last Updated: December 31, 2024

Record last verified: 2024-12

Locations

CN (1)