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Research on the Combined Prediction of Molecular Typing of Breast Cancer by Ultrasound Artificial Intelligence

Application Research on Predicting Molecular Typing of Breast Cancer Based on Ultrasound Combined with Artificial Intelligence

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600118205
Enrollment
Unknown
Registered
2026-02-03
Start date
2025-08-01
Completion date
Unknown
Last updated
2026-02-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Luminal A breast cancer, Luminal B breast cancer, HER2-positive breast cancer, triple-negative breast cancer

Interventions

Gold Standard:Immunohistochemistry (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, Ki-67 proliferation index)
Index test:Radiomics Deep Learning Model

Sponsors

Gongli Hospital of Shanghai Pudong New Area
Lead Sponsor

Eligibility

Sex/Gender
Female

Inclusion criteria

Inclusion criteria: 1.The patient is female. 2.Conventional ultrasound, UE and CEUS examinations were all performed before the operation; 3.Postoperative pathology confirmed it to be a malignant breast tumor, and there are complete clinical data; 4.No neoadjuvant chemotherapy or other treatments were received before the ultrasound examination;

Exclusion criteria

Exclusion criteria: 1.Received anti-cancer treatment before the ultrasound examination; 2.The postoperative pathology lacks complete immunohistochemical results; 3.The image quality is poor;

Design outcomes

Primary

MeasureTime frame
Receiver operating characteristic curve;

Secondary

MeasureTime frame
Area under the curve;Sensitivity;Negative predictive value;Specificity;Positive predictive value;

Countries

China

Contacts

Public ContactXiaohong Fu

Gongli Hospital of Shanghai Pudong New Area

fuxiaohong66@163.com+86 189 1615 7425

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 15, 2026