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Visualization study of Ultrasonic Deep Learning radiomics in predicting Molecular markers of Breast Cancer

Visualization study of Ultrasonic Deep Learning radiomics in predicting Molecular markers of Breast Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400090587
Enrollment
Unknown
Registered
2024-10-09
Start date
2024-10-10
Completion date
Unknown
Last updated
2024-10-15

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

Conditions

Breast related diseases

Interventions

High expression group/ low expression group of breast cancer related biomarkers:None

Sponsors

Shanghai Sixth People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to 100 Years

Inclusion criteria

Inclusion criteria: ?Collect cases admitted to our hospital from September 2021 to September 2024 and confirmed to be breast cancer by puncture or surgical pathology; ?Informed consent for this study; ?Predominantly solid breast cancer can be detected on conventional ultrasound Breast tumors; ?Age =18 years old.

Exclusion criteria

Exclusion criteria: ? Those who have received surgery, radiotherapy, and chemotherapy in the past; ? Those who are combined with other malignant tumors except breast cancer; ? Those who are combined with serious systemic diseases; ? Others who are not suitable for inclusion in the study.

Design outcomes

Primary

MeasureTime frame
tumor markers;—

Countries

China

Contacts

Public ContactShi Lin

Shanghai Sixth People's Hospital

shilin_love@163.com+86 180 1757 9682

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026