Research of Pathological Imaging Diagnosis of Ocular Tumors Based on New Artificial Intelligence Algorithm
1 other identifier
observational
100
0 countries
N/A
Brief Summary
The purpose of this study is to establish a standardized process for obtaining digital pathological image information of ocular tumors; use modern pathological techniques to obtain the co-expression information of multiple biomarkers in the pathological tissues of ocular tumors, and finally construct standardized digital ocular tumors with biomarkers Pathology image database.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started Dec 2020
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
November 19, 2020
CompletedStudy Start
First participant enrolled
December 31, 2020
CompletedFirst Posted
Study publicly available on registry
January 5, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 1, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
June 1, 2022
CompletedJanuary 5, 2021
January 1, 2021
1.4 years
November 19, 2020
January 4, 2021
Conditions
Outcome Measures
Primary Outcomes (1)
To compare the diagnostic accuracy of OPAL and IHC for melanoma and other tumors.
The result of OPAL automatic analysis will be compared with IHC manual counting analysis.The accuracy of the study will be declared "success" if OPAL automatic analysis meet more than 85% of the manual count for all antibody.
Up to 24 weeks.
Study Arms (2)
Melanoma and Nevus
Patients diagnosed with melanoma or/and nevus on the skin around the eye before surgery.
Basal cell carcinoma;Squamous cell carcinoma;Sebaceous gland carcinoma
Patients diagnosed with basal cell carcinoma, squamous cell carcinoma, sebaceous gland carcinoma before surgery.
Eligibility Criteria
patients from the Department of Ophthalmology, Peking University Third Hospital who has an eye tumor and undergoes surgery.
You may qualify if:
- Patients diagnosed with eye tumors and undergoing eye tumor surgery.
- Patients sign informed consent for sample collection and sample transfer agreement, and can cooperate with long-term regular follow-up requirements.
You may not qualify if:
- Patients who are unable to undergo tumor surgery or retain samples due to various reasons .
- Patients who are positive for hepatitis B, HIV, and syphilis.
- Patient compliance is poor.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Biospecimen
After the blood samples are treated with EDTA anti coagulation, the second-generation sequencing is performed from the DNA level and the RNA level to collect relevant genomics information, and establish an ocular tumor fusion genome database. Investigators will establish a complete sequencing data annotation database based on the existing tumor sequencing data annotation and analysis of soft nail sets and tumor sequencing data related public databases (such as the cosmic database).
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Chun Zhang, MD/PHD
Peking University Third Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE CONTROL
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- professor
Study Record Dates
First Submitted
November 19, 2020
First Posted
January 5, 2021
Study Start
December 31, 2020
Primary Completion
June 1, 2022
Study Completion
June 1, 2022
Last Updated
January 5, 2021
Record last verified: 2021-01