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Clinical Study of Imaging Genomics Based on Machine Learning for BCIG

NCT04461990 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 1500

Last updated 2020-08-21

No results posted yet for this study

Summary

1. Identify the imaging features of breast cancer with different molecular types
2. Reveal the association between hormone receptor positive/HER2 negative breast cancer and imaging histology, Oncotype Dx recurrence score
3. Combine genomics and imaging to establish a predictive model for the sensitivity of HER2-positive breast cancer targeted therapy
4. Establish an imaging genomics prediction model for triple-negative breast cancer molecular subtypes, and clarify the imaging genomics characteristics of the therapeutic targets of each subtype

Conditions

Interventions

PROCEDURE

Multidisciplinary cooperative comprehensive treatment

Local surgery, radiation therapy, and systemic therapy such as chemotherapy, endocrine and molecular targeting.

Sponsors & Collaborators

  • RenJi Hospital

    collaborator OTHER

  • International Peace Maternity and Child Health Hospital

    collaborator OTHER

  • Fudan University

    lead OTHER

Principal Investigators

  • Gu Ya Jia · Fudan University

Eligibility

Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-12-01
Primary Completion
2022-12-30
Completion
2023-12-30

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

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 NCT04461990 on ClinicalTrials.gov