Clinical Application Value of a Deep Learning Model Based on Breast Super-Resolution Microscopic Imaging in Predicting Sentinel Lymph Node Metastasis in Breast Cancer

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2500100873

Enrollment

Unknown

Registered

2025-04-16

Start date

2025-05-01

Completion date

Unknown

Last updated

2025-04-21

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

Conditions

breast cancer

Interventions

Gold Standard:The gold standard is based on the pathological results of the sentinel lymph node biopsy during surgery

Index test:Deep learning model based on superresolution microscopic imaging

Eligibility

Sex/Gender

Female

Age

18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.Female, over 18 years of age; 2.The lesions were mass type. 3.Patients diagnosed by puncture as primary invasive breast cancer with complete postoperative pathological findings; 4.He did not receive neoadjuvant chemotherapy or endocrine therapy before surgery;

Exclusion criteria

Exclusion criteria: 1.Patients with severe other systemic diseases cannot undergo CEUS; 2.History of allergy to ultrasound contrast agents; 3.Patients with a history of breast or axillary surgery, chemoradiotherapy;

Design outcomes

Primary

Measure	Time frame
Specificity;	—

Secondary

Measure	Time frame
sensitivity;	—

Countries

China

Contacts

Public ContactLinxue Qian

Beijing Friendship Hospital ,Capital Medical University

qianlinxue2002@163.com+86 10 63138217

Outcome results

None listed

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