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Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

15. december 2020 opdateret af: Jinsong Wu

A Multi-center, Prospective, Self-Controlled Diagnostic Accuracy Comparative Studies of Artificial Intelligence Diagnostic System for Surgical Neuropathology

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.

Studieoversigt

Status

Ukendt

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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.

Undersøgelsestype

Interventionel

Tilmelding (Forventet)

141

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

  • Navn: Lei Jin, DR
  • Telefonnummer: 0086-13817841756
  • E-mail: ozlei91@126.com

Undersøgelse Kontakt Backup

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

18 år og ældre (Voksen, Ældre voksen)

Tager imod sunde frivillige

Ingen

Køn, der er berettiget til at studere

Alle

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Diagnostisk
  • Tildeling: Ikke-randomiseret
  • Interventionel model: Parallel tildeling
  • Maskning: Enkelt

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: Artificial Intelligence
A deep learning based artificial intelligence diagnostic system(DOI:10.1093/neuonc/noaa163)
Diagnostisk test: 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.
Aktiv komparator: Practicing Pathologists
One pathologist who has at least 5 years of experience
Diagnostisk test: 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
Andet: 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
Diagnostisk test: 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

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Diagnostic Accuracy of Study Arms
Tidsramme: 1 week after the last patient's diagnosis is completed
The number of correctly diagnosed participants by study arms divided by the total number of participants
1 week after the last patient's diagnosis is completed

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Sensitivity and specificity of Study Arms
Tidsramme: 1 week after the last patient's diagnosis is completed
Sensitivity and specificity of study arms for each type calculated by 2x2 tables
1 week after the last patient's diagnosis is completed
Spearman Coefficient of Study Arms related to Gold Standard
Tidsramme: 1 week after the last patient's diagnosis is completed
Spearman Correlation Analysis between Study Arms and Gold Standard
1 week after the last patient's diagnosis is completed

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Jinsong Wu

Efterforskere

  • Studieleder: Cuiyun Wu, Ph.D, Huashan Hospital

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Forventet)

1. februar 2021

Primær færdiggørelse (Forventet)

1. februar 2022

Studieafslutning (Forventet)

1. februar 2022

Datoer for studieregistrering

Først indsendt

4. december 2020

Først indsendt, der opfyldte QC-kriterier

15. december 2020

Først opslået (Faktiske)

17. december 2020

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

17. december 2020

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

15. december 2020

Sidst verificeret

1. december 2020

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • PAAI2020

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

Studerer et amerikansk FDA-reguleret lægemiddelprodukt

Ingen

Studerer et amerikansk FDA-reguleret enhedsprodukt

Ingen

Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

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