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Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

Primary Purpose

Central Nervous System Neoplasms

Status
Unknown status
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Artificial Intelligence
Practicing Pathologists
Gold Standard
Sponsored by
Jinsong Wu
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Central Nervous System Neoplasms focused on measuring Artificial Intelligence, CNS Tumor, Surgical Pathology, Diagnostic Accuracy Study

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  1. Patients or their guardians understand the research process, agree to use their data, and sign the informed consent form;
  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:

  1. The patient has serious underlying diseases thus is not suitable for surgery;
  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.

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm 3

    Arm Type

    Experimental

    Active Comparator

    Other

    Arm Label

    Artificial Intelligence

    Practicing Pathologists

    Gold Standard

    Arm Description

    A deep learning based artificial intelligence diagnostic system(DOI:10.1093/neuonc/noaa163)

    One pathologist who has at least 5 years of experience

    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

    Outcomes

    Primary Outcome Measures

    Diagnostic Accuracy of Study Arms
    The number of correctly diagnosed participants by study arms divided by the total number of participants

    Secondary Outcome Measures

    Sensitivity and specificity of Study Arms
    Sensitivity and specificity of study arms for each type calculated by 2x2 tables
    Spearman Coefficient of Study Arms related to Gold Standard
    Spearman Correlation Analysis between Study Arms and Gold Standard

    Full Information

    First Posted
    December 4, 2020
    Last Updated
    December 15, 2020
    Sponsor
    Jinsong Wu
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    1. Study Identification

    Unique Protocol Identification Number
    NCT04671368
    Brief Title
    Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology
    Official Title
    A Multi-center, Prospective, Self-Controlled Diagnostic Accuracy Comparative Studies of Artificial Intelligence Diagnostic System for Surgical Neuropathology
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    December 2020
    Overall Recruitment Status
    Unknown status
    Study Start Date
    February 2021 (Anticipated)
    Primary Completion Date
    February 2022 (Anticipated)
    Study Completion Date
    February 2022 (Anticipated)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Sponsor-Investigator
    Name of the Sponsor
    Jinsong Wu

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No
    Data Monitoring Committee
    No

    5. Study Description

    Brief Summary
    This is a multi-center, prospective, self-controlled, diagnostic accuracy comparative study of Artificial Intelligence Diagnostic System for Surgical Neuropathology. The investigators will compare the diagnostic efficiency of Artificial Intelligence with that of practicing pathologists, and suppose that the diagnostic efficiency of artificial intelligence in prospective clinical data is no less than that of pathologists.
    Detailed Description
    In this study, 141 patients will be recruited. After being enrolled, the patients will accept surgery and specimens for pathological analysis will be taken according to the routine treatment process. 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.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Central Nervous System Neoplasms
    Keywords
    Artificial Intelligence, CNS Tumor, Surgical Pathology, Diagnostic Accuracy Study

    7. Study Design

    Primary Purpose
    Diagnostic
    Study Phase
    Not Applicable
    Interventional Study Model
    Parallel Assignment
    Model Description
    All patients will be diagnosed by both AI and ordinary pathologists, thus performing a self-controlled study
    Masking
    Outcomes Assessor
    Masking Description
    The AI group, ordinary pathologists and gold standard group will not be informed of each other's results
    Allocation
    Non-Randomized
    Enrollment
    141 (Anticipated)

    8. Arms, Groups, and Interventions

    Arm Title
    Artificial Intelligence
    Arm Type
    Experimental
    Arm Description
    A deep learning based artificial intelligence diagnostic system(DOI:10.1093/neuonc/noaa163)
    Arm Title
    Practicing Pathologists
    Arm Type
    Active Comparator
    Arm Description
    One pathologist who has at least 5 years of experience
    Arm Title
    Gold Standard
    Arm Type
    Other
    Arm Description
    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
    Intervention Type
    Diagnostic Test
    Intervention Name(s)
    Artificial Intelligence
    Intervention Description
    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.
    Intervention Type
    Diagnostic Test
    Intervention Name(s)
    Practicing Pathologists
    Intervention Description
    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
    Intervention Type
    Diagnostic Test
    Intervention Name(s)
    Gold Standard
    Intervention Description
    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
    Primary Outcome Measure Information:
    Title
    Diagnostic Accuracy of Study Arms
    Description
    The number of correctly diagnosed participants by study arms divided by the total number of participants
    Time Frame
    1 week after the last patient's diagnosis is completed
    Secondary Outcome Measure Information:
    Title
    Sensitivity and specificity of Study Arms
    Description
    Sensitivity and specificity of study arms for each type calculated by 2x2 tables
    Time Frame
    1 week after the last patient's diagnosis is completed
    Title
    Spearman Coefficient of Study Arms related to Gold Standard
    Description
    Spearman Correlation Analysis between Study Arms and Gold Standard
    Time Frame
    1 week after the last patient's diagnosis is completed

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    Inclusion Criteria: Patients or their guardians understand the research process, agree to use their data, and sign the informed consent form; Aged >=18 years; MRI shows intracranial spaceoccupying lesions; The clinical diagnosis is glioma, metastasis or lymphoma thus requiring surgical treatment; The patient is willing to accept the surgery. Exclusion Criteria: The patient has serious underlying diseases thus is not suitable for surgery; After further clinical evaluation, surgical treatment was not the best choice; The patient participate in clinical research of other drugs or devices; The researchers believe that there are other factors that will make the patients unable to complete the study.
    Central Contact Person:
    First Name & Middle Initial & Last Name or Official Title & Degree
    Lei Jin, DR
    Phone
    0086-13817841756
    Email
    ozlei91@126.com
    First Name & Middle Initial & Last Name or Official Title & Degree
    Yixin Ma, BA
    Phone
    0086-18001781531
    Email
    14301050150@fudan.edu.cn
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Cuiyun Wu, Ph.D
    Organizational Affiliation
    Huashan Hospital
    Official's Role
    Study Director

    12. IPD Sharing Statement

    Learn more about this trial

    Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

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