CompletedNCT06437652

An Artificial Intelligence Algorithm for Lymphocyte Focus Score in Whole Slide Images of Minor Salivary Gland Biopsy Samples for Diagnosing Sjogren's Syndrome : a Blinded Clinical Validation and Deployment Study

Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Trial Details

Condition	Sjogren's Syndrome
Status	Completed
Participants	1,000
Est. Completion	30 Aug 2024
Last Updated	30 Apr 2026

Primary Outcome

The accuracy of pathological interpretation of focal index of labial gland tissue

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria: * The original format of digital pathological images of labial gland biopsy tissue from patients with suspected Sjögren's Syndrome uploaded to the designated platform. Exclusion Criteria: 1. Overlapping layers of cells due to excessively thick sections; 2. Excessive tissue defects caused by incomplete sectioning or poor staining on slides; 3. Absence of labial gland; 4. Insufficient clarity in the image.

Trial Sites

Countries

China

View Registry Entry

Related Analysis

Completed Clinical Validation Study: AI Algorithm for Sjögren's Syndrome Diagnosis via Salivary Gland Biopsy Analysis — Implications for Pathology Practice

A completed 1,000-patient validation study demonstrates promising results for an AI algorithm that calculates lymphocyte focus scores in salivary gland biopsies for Sjögren's syndrome diagnosis. This technology could standardise pathological interpretation and improve diagnostic accuracy for this challenging autoimmune condition.

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