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Automatic Detection in MRI of Prostate Cancer: DAICAP

NCT05513820 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1250

Last updated 2024-05-20

No results posted yet for this study

Summary

Prostate cancer is the most common cancer in France and the 3rd most common cancer death in humans. The introduction of pre-biopsy MRI has considerably improved the quality of prostate cancer (PCa) diagnosis by increasing the detection of clinically significant PCa , and by reducing the number of unnecessary biopsies.However the diagnostic performance of Prostate MRI is highly dependent on reader experience that limits the population based delivery of high quality multiparametricMRI (mpMRI) driven PCa diagnosis. The main objective of this study is the development and the test of diagnostic accuracy of an AI algorithm for the detection of cancerous prostatic lesions from mpMRI images.

The secondary objective is the development and the test of diagnostic accuracy of an AI algorithm to predict tumor aggressiveness from mpMRI images.

Conditions

  • Detection and Characterization of Prostate Cancer Based on Artificial Intelligence

Sponsors & Collaborators

  • University Hospital, Strasbourg, France

    collaborator OTHER

  • University Hospital, Bordeaux

    collaborator OTHER

  • University Hospital, Lille

    collaborator OTHER

  • The Civil Hospitals, Lyon

    collaborator UNKNOWN

  • Institut National de Recherche en Informatique et en Automatique

    collaborator OTHER

  • INCEPTO

    collaborator UNKNOWN

  • Assistance Publique - Hôpitaux de Paris

    lead OTHER

Eligibility

Min Age
18 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-06-21
Primary Completion
2024-12-31
Completion
2024-12-31

Countries

  • France

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05513820 on ClinicalTrials.gov