Research of Pathological Imaging Diagnosis of Ocular Tumors Based on New Artificial Intelligence Algorithm

January 4, 2021 updated by: Chun Zhang, Peking University
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.

Study Overview

Status

Unknown

Conditions

Detailed Description

This study is a prospective study. Patients with common and representative ocular tumors in the Department of Ophthalmology, Peking University Third Hospital, will be selected and enrolled after informed consent to collect basic clinical information, preoperative blood samples, and ocular tumors Obtain pathological image annotation data and genomics-related data from ocular tumor tissue specimens, use blood samples for genomics information analysis, provide multi-dimensional data for the development of artificial intelligence algorithms, and establish artificial intelligence-assisted image data for eye tumors Standardize the process and establish a multi-modal ocular tumor standardized database of "clinical information-tissue samples-pathological images-genomics data". The database and the diagnosis system are correlated with each other to provide optimal image data for later machine learning and related algorithm establishment, and finally the investigators will be completed the design of a new artificial intelligence-assisted diagnosis system for eye tumors.

Study Type

Observational

Enrollment (Anticipated)

100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

patients from the Department of Ophthalmology, Peking University Third Hospital who has an eye tumor and undergoes surgery.

Description

Inclusion Criteria:

  1. Patients diagnosed with eye tumors and undergoing eye tumor surgery.
  2. Patients sign informed consent for sample collection and sample transfer agreement, and can cooperate with long-term regular follow-up requirements.

Exclusion Criteria:

  1. Patients who are unable to undergo tumor surgery or retain samples due to various reasons .
  2. Patients who are positive for hepatitis B, HIV, and syphilis.
  3. Patient compliance is poor.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
To compare the diagnostic accuracy of OPAL and IHC for melanoma and other tumors.
Time Frame: Up to 24 weeks.
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.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Peking University

Investigators

  • Principal Investigator: Chun Zhang, MD/PHD, Peking University Third Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

December 31, 2020

Primary Completion (Anticipated)

June 1, 2022

Study Completion (Anticipated)

June 1, 2022

Study Registration Dates

First Submitted

November 19, 2020

First Submitted That Met QC Criteria

January 4, 2021

First Posted (Actual)

January 5, 2021

Study Record Updates

Last Update Posted (Actual)

January 5, 2021

Last Update Submitted That Met QC Criteria

January 4, 2021

Last Verified

January 1, 2021

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • IRB00006761-M2020434

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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