Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology
NCT ID: NCT04671368
Last Updated: 2020-12-17
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
141 participants
INTERVENTIONAL
2021-02-28
2022-02-28
Brief Summary
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Detailed Description
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The histopathologic slides will then be digitized by a whole-slide scanner. The images will be reviewed by gold standard committee for evaluation of ground truth. And then be separately diagnosed by Artificial Intelligence Diagnostic System and practicing pathologists. So the investigators can compare the diagnostic efficiency of Artificial Intelligence with that of pathologists, thus understand the gap between artificial intelligence and actual clinical practice.
Conditions
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Keywords
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Study Design
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NON_RANDOMIZED
PARALLEL
DIAGNOSTIC
SINGLE
Study Groups
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Artificial Intelligence
A deep learning based artificial intelligence diagnostic system(DOI:10.1093/neuonc/noaa163)
Artificial Intelligence
The investigators will use the Artificial Intelligence Diagnostic System to review the H＆E stained slide of each patient and then report the classification of the tumor on a 10-type scale.
Practicing Pathologists
One pathologist who has at least 5 years of experience
Practicing Pathologists
The ordinary pathologist will review the H＆E stained slide of each patient(without additional informations such as: Immunohistochemistry et al.) and then report the classification of the tumor on a 10-type scale only bases on the slide images
Gold Standard
A committee composed of two expert pathologists who has at least 10 years of experience and one expert pathologist who has at least 15 years of experience
Gold Standard
Firstly, the two expert pathologist(\>=10 years of experience) will review the H＆E stained slide of each patient on their own (with additional informations such as: Immunohistochemistry et al.) and then report the classification of the tumor on a 10-type scale.If they report the same opinion, that opinion will perform as the ground truth; while if their opinion clash with each other, the expert pathologist(\>=15 years of experience) will get involved and the agreement of three experts will perform as the ground truth
Interventions
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Artificial Intelligence
The investigators will use the Artificial Intelligence Diagnostic System to review the H＆E stained slide of each patient and then report the classification of the tumor on a 10-type scale.
Practicing Pathologists
The ordinary pathologist will review the H＆E stained slide of each patient(without additional informations such as: Immunohistochemistry et al.) and then report the classification of the tumor on a 10-type scale only bases on the slide images
Gold Standard
Firstly, the two expert pathologist(\>=10 years of experience) will review the H＆E stained slide of each patient on their own (with additional informations such as: Immunohistochemistry et al.) and then report the classification of the tumor on a 10-type scale.If they report the same opinion, that opinion will perform as the ground truth; while if their opinion clash with each other, the expert pathologist(\>=15 years of experience) will get involved and the agreement of three experts will perform as the ground truth
Eligibility Criteria
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Inclusion Criteria
2. Aged \>=18 years;
3. MRI shows intracranial spaceoccupying lesions;
4. The clinical diagnosis is glioma, metastasis or lymphoma thus requiring surgical treatment;
5. The patient is willing to accept the surgery.
Exclusion Criteria
2. After further clinical evaluation, surgical treatment was not the best choice;
3. The patient participate in clinical research of other drugs or devices;
4. The researchers believe that there are other factors that will make the patients unable to complete the study.
18 Years
ALL
No
Sponsors
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Jinsong Wu
OTHER
Responsible Party
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Jinsong Wu
Chief Physician of Neurosurgery Department, Vice-director of Neurosurgery Institute, Member of Ethics Committee, Clinical Professor of Surgery
Principal Investigators
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Cuiyun Wu, Ph.D
Role: STUDY_DIRECTOR
Huashan Hospital
Central Contacts
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Other Identifiers
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PAAI2020
Identifier Type: -
Identifier Source: org_study_id