Ignite Creation Date:
2024-06-16 @ 11:49 AM
Last Modification Date:
2024-10-26 @ 3:31 PM
Study NCT ID:
NCT06437652
Status:
RECRUITING
Last Update Posted:
2024-07-05
First Post:
2024-05-11
Brief Title:
An AI Algorithm for Lymphocyte Focus Score of Minor Salivary Gland Biopsy Samples for Diagnosing Sjogrens Syndrome
Sponsor:
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Organization:
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Study Overview
Official Title:
An Artificial Intelligence Algorithm for Lymphocyte Focus Score in Whole Slide Images of Minor Salivary Gland Biopsy Samples for Diagnosing Sjogrens Syndrome a Blinded Clinical Validation and Deployment Study
Status:
RECRUITING
Status Verified Date:
2024-07
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The aim of this research is to discover an artificial intelligence AI algorithm for lymphocyte focus score in whole slide images of labial minor salivary gland SG biopsy samples for diagnosing Sjogrens Syndrome in order to enhance the precision of pathological interpretation of labial minor SG biopsy samples in patients with suspected Sjogrens syndrome and aid clinicians make an accurate diagnose A remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG will be built for the global based on the research results The research will propose the AI-assisted pathological interpretation of lymphocyte focus score in labial minor SG biopsy samples in the future guidelines for the diagnosis and treatment of Sjogrens syndrome
The research will
1 Develop and debug the AI algorithm for lymphocyte focus score in whole slide images of labial minor SG biopsy samples for diagnosing Sjogrens Syndrome
2 Internal test of the AI algorithm
3 Clinical validation of the AI algorithm with blind method in multiple centers 4Built a remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG for the global and Explore its clinical application
The research will
1 Develop and debug the AI algorithm for lymphocyte focus score in whole slide images of labial minor SG biopsy samples for diagnosing Sjogrens Syndrome
2 Internal test of the AI algorithm
3 Clinical validation of the AI algorithm with blind method in multiple centers 4Built a remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG for the global and Explore its clinical application
Detailed Description:
1 Develop and debug the AI algorithm for lymphocyte focus score in whole slide images of labial minor SG biopsy samples for diagnosing Sjogrens Syndrome A total of 200 HE staining slides of labial minor SG biopsy samples are collected from Sun Yat-sen Memorial Hospital of Sun Yat-sen University and scanned into digital pathological images The ground truth of gland tissue area and lymphocyte foci numbers in each image is interpreted by three senior pathologists with over 5 years of related experience
2 Internal test of the AI algorithm A total of 500 additional digital pathological images of labial gland biopsy tissues are collected from Sun Yat-sen Memorial Hospital of Sun Yat-sen University The ground truth of gland tissue area and lymphocyte foci numbers in each images is interpreted by three senior pathologists with over 5 years of related experience The AI algorithms accuracy specificity sensitivity positive predictive value and negative predictive value in evaluating the area of labial gland and the number of lymphocyte foci are calculated Comparison of whether the image meets the criteria for Sjögrens syndrome focus score greater than 1 is also conducted between the AI algorithm and the ground truth
3 Clinical validation of the AI algorithm with blind method in multiple centers A total of 600 additional digital pathological images of labial gland biopsy tissues are collected from six external centers The ground truth of gland tissue area and lymphocyte foci numbers in each images is interpreted by three senior pathologists with over 5 years of related experience The AI algorithms accuracy specificity sensitivity positive predictive value and negative predictive value in evaluating the area of labial gland and the number of lymphocyte foci are calculated Comparison of whether the image meets the criteria for Sjögrens syndrome focus score greater than 1 is also conducted between the AI algorithm and the ground truth
4Built a remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG for the global and Explore its clinical application
Digital pathological images of labial gland biopsy tissue can be uploaded to the Labial Gland Pathological Focus Score Remoting platform AI-assisted pathological interpretation on gland tissue area lymphocyte foci numbers and whether meeting the criteria for Sjögrens syndrome focus score greater than 1 is compared with the ground truth
2 Internal test of the AI algorithm A total of 500 additional digital pathological images of labial gland biopsy tissues are collected from Sun Yat-sen Memorial Hospital of Sun Yat-sen University The ground truth of gland tissue area and lymphocyte foci numbers in each images is interpreted by three senior pathologists with over 5 years of related experience The AI algorithms accuracy specificity sensitivity positive predictive value and negative predictive value in evaluating the area of labial gland and the number of lymphocyte foci are calculated Comparison of whether the image meets the criteria for Sjögrens syndrome focus score greater than 1 is also conducted between the AI algorithm and the ground truth
3 Clinical validation of the AI algorithm with blind method in multiple centers A total of 600 additional digital pathological images of labial gland biopsy tissues are collected from six external centers The ground truth of gland tissue area and lymphocyte foci numbers in each images is interpreted by three senior pathologists with over 5 years of related experience The AI algorithms accuracy specificity sensitivity positive predictive value and negative predictive value in evaluating the area of labial gland and the number of lymphocyte foci are calculated Comparison of whether the image meets the criteria for Sjögrens syndrome focus score greater than 1 is also conducted between the AI algorithm and the ground truth
4Built a remote AI-assisted pathological interpretation platform for lymphocyte focus score in labial SG for the global and Explore its clinical application
Digital pathological images of labial gland biopsy tissue can be uploaded to the Labial Gland Pathological Focus Score Remoting platform AI-assisted pathological interpretation on gland tissue area lymphocyte foci numbers and whether meeting the criteria for Sjögrens syndrome focus score greater than 1 is compared with the ground truth
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None