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Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography

24. juli 2021 oppdatert av: Sun Ying-Shi, Peking University Cancer Hospital & Institute
This project aims to establish a comprehensive artificial intelligence system for detecting and qualitative diagnosing breast lesions. Mammary images will be used to construct a diagnosis method based on deep learning. The system is proposed to automatically analyze the type of mammary glands, automatically identify and mark all breast lesions on the mammography images, provide the malignancy probability judgment of the lesions, the BI-RADS classification and the clinical suggestion, and also automatically generate the structured diagnosis report.

Studieoversikt

Status

Fullført

Forhold

Intervensjon / Behandling

Detaljert beskrivelse

This is a multi-center study.The project contains a retrospective part(3000 samples anticipated) and a prospective part(7000 samples anticipated). In the retrospective part, investigators collected subjects with mammary images to design the deep learning method and construct a detective and diagnostic model for breast lesions. In the prospective part, investigators validate the accuracy of the constructed deep learning method, and established artificial intelligence system focusing on mammary diagnosis. Investigators will also explore the application pattern of the artificial intelligence system in clinical practice.

Studietype

Observasjonsmessig

Registrering (Faktiske)

5809

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiesteder

  • Kina
    • Beijing
      • Beijing, Beijing, Kina, 100142
        • Beijing Cancer Hospital
      • Beijing, Beijing, Kina
        • Beijing Chao Yang Women and Children's Health Hospital
      • Beijing, Beijing, Kina
        • Beijing Da Xing People's Hospital
      • Beijing, Beijing, Kina
        • Beijing Hang Tian Centre Hospital
      • Beijing, Beijing, Kina
        • Beijing Nan Jiao Cancer Hospital
      • Beijing, Beijing, Kina
        • Beijing Shi Jing Shan Hospital
      • Beijing, Beijing, Kina
        • Beijing Shun Yi Qu Hospital
      • Beijing, Beijing, Kina
        • Beijing Shun Yi Woman and Children Health Hospital

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

18 år og eldre (Voksen, Eldre voksen)

Tar imot friske frivillige

Nei

Kjønn som er kvalifisert for studier

Hunn

Prøvetakingsmetode

Sannsynlighetsprøve

Studiepopulasjon

Women with suspected Breast Lesion

Beskrivelse

Inclusion Criteria:

  • the X-ray images of the breast were complete
  • the results of pathological diagnosis or more than 2 years of mammography follow-up were available
  • subject signs informed consent(this item was only for prospective study cases)

Exclusion Criteria:

  • there exists pathological diagnosis of breast lesions when receiving mammography
  • there lacks pathological diagnosis or 2 years of mammography follow-up
  • subject withdraws(this item was only for prospective study cases)

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

Kohorter og intervensjoner

Gruppe / Kohort
Intervensjon / Behandling
mammography group
women who receives mammography because of suspected breast lesion(s)
Diagnostisk test: mammography
When a woman comes to the clinic to receive mammography. Then a radiologist will give a BI-RADS classification after reviewing the images. If a BI-RADS 4/5 is obtained, the woman will receive pathological biopsy to ensure there is a benign or malignant lesion. If a BI-RADS 3 is obtained, the woman will be followed up by a half-year interval until two year after the first mammography. At each follow up, she will receive mammography. If a BI-RADS 4/5 is obtained at follow up, she will receive pathological biopsy; if a BI-RADS 1/2/3 is obtained at follow up, she will be followed up by a half-year interval until two year. If a BI-RADS 1/2 is obtained at the first mammography, the woman will receive a second mammography after two year. During the study period, breast examination and results will be recorded for every subject. Radiologists will give the diagnosis with and without AI support.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
benign-malignant diagnosis accuracy
Tidsramme: from the first mammography to pathological result obtained(an average of 3 weeks if mammography BI-RADS 4 or 5 obtained)
the accuracy of the AI model, radiogist with AI support, radiologist alone for binary diagnosis of a benign or malignant breast lesion according to pathology. If either one mammography of BI-RADS 4/5 in the first examination or during the two year' follow up examination is obtained,a pathological examination is performed, the lesion is judged benign or malignant according to pathological results.
from the first mammography to pathological result obtained(an average of 3 weeks if mammography BI-RADS 4 or 5 obtained)
benign-malignant diagnosis accuracy
Tidsramme: from the first mammography to 2-year-after mammography
the accuracy of the AI model, radiogist with AI support, radiologist alone for binary diagnosis of a benign or malignant breast lesion according to follow up. If a 2-year mammography of BI-RADS 1/2/3 is obtained, the lesion is considered benign. If either one mammography of BI-RADS 4/5 during the two year is obtained,a pathological examination is performed to ensure the benign or malignant lesion
from the first mammography to 2-year-after mammography

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
lesion detection accuracy
Tidsramme: from the first mammography to radiologist diagnosis (within 3 days after the mammography taken)
the detection rate of the constructed deep learning method for detecting benign or malignant breast lesion according to radiologist's subjective diagnosis or follow up as reference. If a radiologist suggests existence of a lesion at the first mammography or at each follow-up mammography during the 2-year period, it is considered that a lesion exists
from the first mammography to radiologist diagnosis (within 3 days after the mammography taken)

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

Peking University Cancer Hospital & Institute

Samarbeidspartnere

Peking University

Etterforskere

  • Studiestol: Ying-Shi Sun, Professor, Peking University Cancer Hospital & Institute

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

5. april 2018

Primær fullføring (Faktiske)

4. mai 2020

Studiet fullført (Faktiske)

4. mai 2020

Datoer for studieregistrering

Først innsendt

17. april 2018

Først innsendt som oppfylte QC-kriteriene

12. oktober 2018

Først lagt ut (Faktiske)

17. oktober 2018

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

27. juli 2021

Siste oppdatering sendt inn som oppfylte QC-kriteriene

24. juli 2021

Sist bekreftet

1. juli 2021

Mer informasjon

Begreper knyttet til denne studien

Andre studie-ID-numre

  • BCA-AI

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

Denne informasjonen ble hentet direkte fra nettstedet clinicaltrials.gov uten noen endringer. Hvis du har noen forespørsler om å endre, fjerne eller oppdatere studiedetaljene dine, vennligst kontakt register@clinicaltrials.gov. Så snart en endring er implementert på clinicaltrials.gov, vil denne også bli oppdatert automatisk på nettstedet vårt. .

Kliniske studier på mammography

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Sponsorer og samarbeidspartnere

Medisinsk tilstand

Legemiddelintervensjoner

CROs by country

CROs in Vietnam

Forhold

Sjeldne sykdommer

Legemiddelintervensjoner

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Steder

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